# About
Treasury funding resources overview
Contributors are often able to request funding from an ecosystems treasury through a funding process. A Web3 ecosystem could adopt many different funding processes to help with allocating treasury assets towards initiatives that can generate impact for the ecosystem. These resources explore some of the ways that a Web3 funding process could be approached and developed. These resources cover the key parts of the funding process, what approaches could be the most promising to adopt and numerous other factors that could be considered when implementing a funding process.
# Funding process
Overview of the different processes involved in treasury funding
The [general purpose operating process](https://docs.treasuries.io/web3-treasuries/operating-process) can be applied more directly to the treasury funding process. Applying this process can help with thinking about how each of the processes involved in funding could be improved over time and how funding and each of its processes can play an important role in helping an ecosystem achieve its priorities and generate impact for the ecosystem.
Each part of the funding process is covered in more detail in the following documentation:
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[Knowledge process](/knowledge/adoption-of-knowledge-systems)
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[Priority process](/priorities/independent-priority-process)
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[Idea process](/ideas/idea-process)
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[Contributor process](/contributors/independent-contributor-process)
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## **Funding process comparisons**
Each of the funding processes can be compared with each other to better understand the amount of information that is involved, the rates of change, how important each one is for funding, how responsibilities could be delegated in each of the processes and the overall complexity of each process:
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[Process information](/process/disbursement-operating-process/process-information)
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[Process rate of change](/process/disbursement-operating-process/process-rate-of-change)
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[Process rankings of importance](/process/disbursement-operating-process/process-rankings-of-importance)
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[Delegating process decisions](/process/disbursement-operating-process/delegating-process-decisions)
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[Process complexity](/process/disbursement-operating-process/process-complexity)
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# Process information
Exploring what information is involved in each step of the funding process
A lot of information will often be needed to effectively operate a funding process. Voters need to be well informed when making decisions on how to effectively disburse treasury assets to generate impactful outcomes. A variety of different information is needed across each step of the funding process, voters will need to review this information to be sufficiently informed when making any decisions.
There is a vast amount of information that can be gathered prior to making any funding decisions. It is the application of this information that will heavily influence an ecosystem's decision on what to prioritise, which ideas are the most promising and which contributors should help execute those ideas. Ideas will also include a wide range of information, a sufficient level of depth will often be needed to properly articulate how any suggested solution idea can effectively address a priority. The amount of information needed to understand the skills and experience of a contributor is also fairly sizable, along with the ongoing information gathered about how those contributors operate together and the measured outcomes from executed ideas. Priorities may not require the same quantity of information as some of the other funding steps, but priorities could still see a moderate amount of information being gathered, this could come in the form of community responses that help highlight overall sentiment and feedback about the current priorities as they are being addressed over time.
**Potential information gathered in this process**
Any information relevant to the ecosystem that could help with making more well informed funding decisions could be included in this process of aggregating information for the ecosystem to consider.
* **Current state of an ecosystem** - On-chain data covering usage and performance, historical funded initiatives and the impact they generated, security audits covering ecosystem protocols and applications, current user sentiment and feedback, SDKs, tools and libraries available for software development, available products & services in the ecosystem with their current usage, adoption, problems and opportunities and performance and metrics for current execution approach.
* **External ecosystem information** - Competitor on-chain data covering usage and performance, other approaches used for technical infrastructure, protocol design or security audits, products and services launched in other ecosystems, latest industry technical advancements along with any reports and insights, industry overall sentiment and adoption data, economic data with any current forecasts and any regulatory changes.
**Other information relevant to this process**
* **Execution** - Any progress or outcomes generated from the execution of ideas will help to create new information that can be fed back into the funding process as new knowledge. Measuring the impact of outcomes generated will be an important approach for improving future prioritisation, idea selection and the approaches that get adopted for executing those ideas.
**Potential information gathered in this process**
* **Priority information:**
* Title - Short sentence outlining the priority.
* Description - The rationale behind why the priority is important and which of the relevant information made available has led to the suggestion of the priority.
* Relevant knowledge - List of the relevant pieces of information that support why this priority is important at the moment.
* Authors - Who created the priority, this could be a person, wallet address or it could be untracked and remain anonymous.
* Community feedback & comments - Any feedback or comments provided by the community towards how the priority could be improved and what information might be missing or lacking to properly justify why the priority is important at the moment.
* Voter sentiment - Community responses about the priority which could be around urgency or any other opportunities and concerns.
* Current progress - Evidence of any current progress in achieving the priority or community responses indicating how much progress they believe has been made towards addressing the priority. Progress responses could help with identifying when priorities have already been addressed or when they are becoming less relevant or redundant.
* Metadata - Date when the priority was submitted and any other dates and related information.
**Other information relevant to this process**
* **Knowledge** - The priority setting process benefits from participants knowing as much of the information as possible that came out of the knowledge aggregation process. The more information that participants have about the ecosystem the more they are able to effectively analyse it and apply that information when thinking about what the current problems and opportunities are. The application of ecosystem knowledge will lead to thinking about many areas of the ecosystem before then trying to determine which areas may create the most impact if they were to receive more resources and attention. Some example areas and leading questions might include:
* Protocols & infrastructure - Are they any flaws in the current system design? How is it currently scaling against competition? Are more security audits needed? Should any recent advancements in cryptography or available software libraries be integrated?
* Applications & services - What are the missing applications and services in the ecosystem that can be found elsewhere? What feature sets are missing in any of the existing applications? Can the amount of interoperability be increased to accommodate other ecosystems? What applications or services will help increase overall adoption?
* Software libraries - Are there any missing software SDKs, frameworks, libraries or scripts that would make it easier for developers to create solutions? Is there anything that can be improved with the existing libraries? Do any of these need better security guarantees? Should any of them be rewritten in other programming languages?
* Ecosystem education - Do people understand how to participate and use all of the solutions and tools made available? Are any of the applications, services, libraries or pieces of infrastructure too difficult to understand for their intended audience? Are resources available in enough languages to increase the diversity of participation in the ecosystem?
**Potential information gathered in this process**
* **Idea information:**
* Title - Short name for the idea.
* Summary - Brief overview of what the idea is about.
* Relevant priorities - List of the priorities the idea would help with addressing.
* Goals & objectives - Intended scope of idea outlining what outcomes the idea could help with for addressing ecosystem priorities.
* Plan for measuring outcomes - What existing or new approach could be used to measure the outcomes of the executed idea when measuring the impact it generated.
* Research & analysis - Any supporting evidence for why the idea could be effective at addressing the relevant priorities
* Detailed description - A full breakdown of what the idea is including how it would operate, how it could be made (e.g. tech stack), what’s included in the idea (e.g. list of application features).
* Technical & non-technical requirements - Breakdown of the requirements involved for the idea to be executed as intended.
* Existing solution comparison - List of any existing similar ideas that have been executed and the similarities and differences this idea has with those other ideas. Rationale provided towards why the idea being suggested is relevant and useful compared to the alternatives that have been identified.
* Opportunities & risks - The opportunities and risks that may emerge or that already exist when executing the idea.
* Dependencies - List of any external dependencies that the idea relies on for it to be effectively executed.
* Authors - Who created the idea.
* Execution breakdown & milestones - A breakdown of the tasks involved in executing the idea which could be grouped by skill or task. Milestone based groupings could be made to better identify when key parts of an idea will be executed that can help with demonstrating progress.
* Total cost - A breakdown of the total cost to execute the idea based on the execution breakdown and milestones. Costings would only be needed if the funding decisions for idea selection are the point where compensation is awarded.
* Voter sentiment - Community responses to an idea that help to highlight any concerns, problems or opportunities worth consideration.
* Community feedback & comments - Any feedback or comments provided by the community towards how an idea could be improved or requests for further clarification about certain areas.
* Tags & categorisations - Tags or categorisations that make it easier to traverse and find this idea when it is amongst many others.
* Metadata - Date the idea was created or updated along with any other relevant information.
* Resources - Links to external resources that are relevant for helping explain the idea further or for justifying the ideas potential to address ecosystem priorities.
* **Impact measuring information** - The outcomes from executed ideas can be recorded and analysed to better understand what impact is being generated. Data could include usage and system metrics or qualitative feedback about people's experience when using or participating in the events, resources, applications or any other executed outcome.
**Other information relevant to this process**
* **Knowledge** - All of the available knowledge in the ecosystem could be useful for thinking about how ideas are created and selected. Some example areas for consideration would include whether that idea has been executed inside or outside the ecosystem before? If it has, was it executed fully, what impact did it make and what risks or opportunities might exist for executing that idea based on the historical evidence?
* **Priorities** - When ideas are created they will need to articulate what priorities the idea is addressing, is it a problem in the ecosystem or an opportunity to improve something or try something new? Is this idea currently a priority set by the ecosystem or is it a completely new priority that the author is suddenly suggesting? An understanding of the current priorities can help with inspiring people to think about what ideas might be suitable to help address them.
**Potential information gathered in this process**
* **Contributor information**:
* Personal information - Full name, nationality, date of birth, wallet address, proof of being human, national identity. Some or most of this information such as full name, date of birth or nationality may not be required for many ecosystems, however in certain circumstances it may be useful or required.
* Passions & preferences - Details about what the contributor is passionate about working on and what their current preferences are in terms of how they work and focus areas. This could also include why they might want to work in certain environments and ecosystems.
* Compensation request - The expected amount of compensation that a contributor is looking for when working in the ecosystem. This may also include some justifications and rationale towards why this compensation value is reasonable.
* Education - A list of any educational credentials from schools, colleges, universities or online educational platforms. This could also include any other relevant forms of education such as from internships or apprenticeships.
* Professional background - The roles and responsibilities a contributor has previously had in other organisations and ecosystems. This could include their responsibilities, any achievements whilst in the role and the total amount of time they were working there for.
* Historical contributions - Evidence of any previous contributions made to different ecosystems that are relevant.
* Historical participation - Evidence of where a contributor has participated previously such as events, conferences, hackathons or anything else that might be relevant.
* Resources - Links to any resources that help provide more evidence about a contributors background, participation, contributions, skills and experience.
* Community feedback & comments - Any feedback or comments provided by the community towards how a contributor could improve the information provided or requests to further clarify certain areas.
* **Operating process information** - When executing ideas a group of contributors can gather a range of information when using tools and adopting different processes.
* Collaboration tools - Any tools being used to collaborate, schedule and organise a group of contributors execution efforts can help with creating insights and information that could be useful for making considerations about how to improve future execution efforts.
* Progress and audit data - Any tools used to track progress and completion can help with creating insights and information about how well execution efforts are going and also help with providing auditable information that ecosystem members can consider in future decisions.
**Other information relevant to this process**
* **Knowledge** - Understanding how different ecosystems are executing their own ideas, operating as a group of contributors and measuring their own outcomes will provide useful information that existing contributors can reflect on when improving their own processes. Changes in technology, security best practices and the available software and libraries are all example areas of new information that could benefit future execution efforts, contributors could consider and integrate any of this emerging information into how they operate in the future.
* **Priorities** - Understanding the current priorities will help with thinking about what range of skills and experience might be useful to effectively help address those priorities during execution.
* **Ideas** - Suggesting or understanding the current ideas preferred by an ecosystem will give a better indication of the exact skills and experience required to execute them. The more complex an idea is the more important it will be that the contributors involved in execution have the relevant skills and experience.
# Process rate of change
Making suggestions towards what rates of change could apply to each of the funding operating processes
Understanding how fast different factors can change which impact the funding process will help with thinking about how any adopted systems and processes can be made to be sufficiently flexible and capable of handling any fast changing information or environments.
The most prominent step in the funding process that influences all other areas is the knowledge that an ecosystem is applying to generate and select its priorities, ideas and contributors for execution. The information made available to an ecosystem for making decisions will change on a daily basis. Some of this information can then influence changes to the priorities, ideas and contributors being selected to execute the most promising ideas.
Ideas are likely the next major area in the funding process that could see frequent changes due to the range of ways that a solution can be defined to solve a certain priority. A wide range of information from internal and external sources could influence how ideas are updated and introduced over time to better address the current priorities. Execution could also likely see a slow to moderate rate of change when any of the contributors involved in the execution of ideas changes or how they operate and collaborate together. Finally an ecosystem's high level priorities would be another step in the funding process that would gradually change over time as the ecosystem starts to achieve its existing priorities or when existing priorities become less important than other ones.
Applying some approximate suggestions to think about these rates of change helps to highlight how important it is to consider how any treasury funding process is able to handle environments that have fast changing amounts of knowledge available. Any ecosystem will want to consider and respond to this knowledge when making funding decisions. If ideas are likely to change fairly frequently then the question to ask is how will the adopted systems and processes for funding cater for those changes? Can those changes to ideas be performed easily and effortlessly by the contributors responsible so they are better aligned with addressing ecosystem priorities?
**What changes and how often?**
Knowledge about an ecosystem can include information such as any on-chain and usage data from any network, performance and measured impact data, preference and sentiment data, available tools, libraries and SDKs, market data, industry technical advancement research, reports and insights and any other relevant data for Web3 ecosystems. Any of this data could change on a daily basis due to the breadth of information being covered. Much of this data would change automatically as it is recorded on the networks themselves daily, other areas such as the software libraries and networks being deployed would still change regularly and could be verified through public code commits. All of this aggregated information represents knowledge that any ecosystem can use to improve what they are prioritising, what ideas will be the most effective to execute and can also help with providing a better understanding of how to approach effectively executing those ideas.
**What implications does this have on the process?**
The implications of knowledge on the selecting priorities, ideas and contributors is profound. The knowledge applied by an ecosystem is what gives its members an understanding of what’s working and isn’t working, what problems exist and what new areas and opportunities have the most promising potential outcomes based on historical data and case studies. This and many other areas of information that impact the available knowledge help with making more well informed decisions. The members of an ecosystem who have the most accurate and up to date information will be able to more effectively be well informed when picking impactful priorities, ideas and contributors for execution. Due to this the implications of a fast changing amount of knowledge is that the priorities, ideas and contributor selection process will need to be flexible enough to handle a fast changing environment of information made available. The ecosystem will want to be able to respond to new information. The better an ecosystem can do this the more they will be able to align themselves with more impactful priorities, better ideas and improved approaches to execute them.
**What changes and how often?**
Setting high level priorities within an ecosystem can help to identify the biggest problems and opportunities that exist at a given moment in time. An ecosystem will benefit from coming to some form of consensus on the general preference and direction the community wants to take. Some example high level priorities could be to make it more effortless to build in the ecosystem, to have a range of secure and scalable DeFi applications or to adopt and integrate more self sovereign identity solutions across the ecosystem. Setting high level priorities such as these examples will help a community communicate its current preferences. Priorities that have a larger scope and that are more generally applicable across most of an ecosystem would more often than not take a longer time to achieve than smaller more targeted priorities. For higher level priorities it would be difficult for an ecosystem to achieve these priorities if they were constantly changing day to day or week to week. New knowledge could be an influencing reason that these priorities change over time however for the most part this is unlikely to happen on a daily or weekly basis. Changing priorities is to be expected as bigger problems and opportunities present themselves to the wider ecosystem.
**What implications does this have on the process?**
If priorities had a fast rate of change in an ecosystem then it would be paramount that a funding process is able to respond to those changes and start redirecting funding to initiatives that are addressing these new priorities. The idea and contributor selection process would need to be sufficiently flexible to handle these changes as these priorities change. One implication of changing priorities could be that certain teams of contributors may need to migrate to a completely new area of focus to continue working on areas that better address current priorities. For other ecosystems where the rate of change is more gradually paced then a slower and more gradual change in allocation of treasury assets to different initiatives over time could be expected. Due to the longer amount of time needed to achieve any high level priorities we could expect the slower rate of change being more likely and preferable if possible.
**What changes and how often?**
There are many different parts and elements that make up a complete idea which is trying to address ecosystem priorities. At a high level the idea could be to create a lending and borrowing protocol to address a need for more DeFi applications in the ecosystem. However within that idea are many other elements including the tech stack, mathematical formulas or algorithms, user experience and interface design, application features being provided, security practices and audit processes amongst many other aspects. All of these are important parts of the overall solution idea that can all be updated and changed over time as new information or resources become available. Factors that could influence the need for ideas to be updated over time could include new software libraries and packages, new adoption or usage data from similar applications, changes in security best practices or approaches and many other forms of relevant information.
**What implications does this have on the process?**
If some part of an overall idea needs to be changed or improved to respond to new information or learnings from the execution of that idea a redirection of execution effort may be needed towards other ideas or focus areas to better address existing priorities. In some of these cases this may mean that contributors need to learn new skills or that different contributors are needed with different skill sets. Sometimes these changes could also mean introducing a change in how the team operates when executing an idea. One example of this could be a new security tool is identified as something worth integrating into the solution being developed meaning the group of contributors will update how they are securing the software they are deploying.
**What changes and how often?**
Execution focuses on which contributors are being selected to execute the most promising ideas. How they operate as a team and execute an idea is also part of the execution process. The contributors who are involved in the execution of an idea could change moderately often as existing contributors move to other areas of work and new contributors join over time. The ecosystem may also decide to select different contributors for certain areas of work based on their historical performance or when different skill sets are required. How contributors collaborate together to execute ideas could also change over time as new best practices emerge around software development, security audits, collaboration, organisation, community building and any other relevant area that influences how a group of contributors operate together.
**What implications does this have on the process?**
Changing the contributors involved in the execution of ideas doesn’t mean that any of the knowledge, priorities or ideas would need to change. In some cases a change of contributors could result in those contributors influencing new ideas and priorities through their own suggestions or they might help with identifying new and useful information to consider. Changing how contributors operate and collaborate together would also not necessarily mean any changes are required for the knowledge, priorities or ideas parts of the funding process. As contributors learn about how to improve their own processes and operations this can lead to new knowledge which could then influence future priorities, ideas and execution.
# Process rankings of importance
A suggested importance ranking of each part of a funding process
Knowledge is the most important part of the funding process as it influences every single other process and how effectively decisions are made in those processes. Making good priorities are also fundamental for an ecosystem so they can create achievable and impactful outcomes. Poor prioritisation can reduce the probability that contributors generate impactful outcomes if they are not executing the most important and promising. The contributors involved in the execution of any ideas will directly determine the actual outcomes that are generated. Ideas are also important for the process however there can be many ideas that are relevant and effective for addressing ecosystem priorities. The execution of those ideas and what gets learnt whilst executing them will generate more learnings to improve any of the initial ideas that get selected. The quality and speed of the operating process for executing ideas along with how the ongoing progress is measured and reviewed will create new learnings that can be highly insightful and important for updating any existing ideas or introducing new ones. A group of contributors will apply those ongoing learnings to help with better addressing an ecosystem's priorities over time.
**Impact on other processes**
* **Priorities** - The more well informed an ecosystem is with any relevant information about what they’re trying to achieve the more accurately they will be able to create sensible priorities that are impactful and achievable. Knowledge such as products and services available in the market, competitor performance, feasibility of ideas, adoption and usage data, economic and market trends, user sentiments and preferences and many other relevant forms of information would all help to influence what priorities might be the most suitable for an ecosystem to focus on.
* **Ideas** - Knowledge helps an ecosystem with better understanding how solutions could be created to address an ecosystem's priorities. Information such as available products & services in the market, competitor adoption and usage data, available software and libraries, industry technical advancements and progress and many other relevant areas will help to improve the overall quality of ideas.
* **Execution** - Knowledge will help with identifying what working processes and best practices, skills, working structures, incentive models and other areas of relevant information can be used to help improving how a group of contributors operates to work on the most promising ideas and also help with the making decisions on which contributors are most suitable to help with execution.
**Overall importance**
Knowledge has a monumental impact on every part of the funding process. Due to this it can be seen as one of the processes with the highest importance for an ecosystem to constantly reflect on and improve over time. Improving the correctness of information and accessibility to any knowledge in an ecosystem along with making that knowledge easy to understand and digest will directly help with improving the funding process such as the priorities and ideas being created and selected. Quality knowledge will also help with selecting which contributors will be the most effective for addressing any priorities and executing the most promising ideas.
**Impact on other processes**
* **Ideas** - The priorities selected will directly influence and help determine which ideas get generated and which ones are selected as the most promising. Ideas will rely on having well set priorities so that executing those ideas can help with achieving high impact for the ecosystem.
* **Execution** - Priorities will heavily influence what skills and experience is needed for addressing those priorities effectively. For instance if an ecosystem's priority was to give users more self sovereign control and access to their identity data then this could influence the need for more professionals that understand self sovereign identity technology and that can help with generating or contributing towards any promising ideas.
**Overall importance**
Good prioritisation will play a vital role in which ecosystems stagnate or thrive over the long term. An ecosystem can have fantastic ideas and highly professional and capable contributors but if they are addressing low impact priorities then their chance of success decreases. Good prioritisation will be an essential part of an ecosystem executing the right ideas and making a high impact.
**Impact on other processes**
* **Execution** - Ideas will influence which contributors are suitable for the execution of those ideas. For example if an idea is about creating a software application then finding software developers and product designers would be a sensible outcome. Changing ideas only requires new contributors for execution if the scope of the idea changes significantly enough. If an idea was changed from being about executing a new application to running a community event then the skills needed for that idea would have changed who is likely most suitable for executing the idea. However if it was an idea for an application that changes its intended feature set then the contributors needed would likely remain the same, unless the skill sets required for those features were significantly different enough than the existing contributors skill sets.
**Overall importance**
Generating and selecting the right ideas is an important part of being able to address ecosystem priorities. Although ideas are important it must be noted there can be many ideas and variations of ideas that all can help with addressing the priorities of an ecosystem. Some will be more effective than others and some will have trade offs between one approach and another. The potential impact of executing ideas is highly influenced by impactful and achievable priorities that are influenced by the knowledge an ecosystem applies.
**Impact on other processes**
* **Knowledge** - The execution of a solution idea leads to creating an ongoing amount of new insights, data and new information which can then be fed back into the funding process as new knowledge. For example, on-chain adoption data for a recently launched application would create useful knowledge for an ecosystem to consider about how it is performing and how it could be potentially improved in the future by comparing it with other similar applications elsewhere. Another area of new information could come from during any execution where it becomes more clear that the complexity to execute a certain idea is higher than expected. This insight and new knowledge about the higher complexity for execution can then feed into the other processes and improve decision making around how the idea could evolve and improve or how the execution approach could be changed to better resolve this complexity.
* **Ideas** - As contributors continue to execute ideas they will continuously learn where improvements can be made and how they can better execute the idea through that experience. This outcome emerges due to the execution improving the available knowledge the ecosystem has which then informs improvements to the solution idea itself.
**Overall importance**
The execution of promising ideas is the primary way an ecosystem will be able to address its priorities. The skill level and quality of the contributions involved in any of the execution of these ideas will be of paramount importance to ensure the ideas are executed as planned and to a high quality. The outcomes of high quality execution will lead to more insightful information that can be fed back into the funding process as new knowledge. This knowledge will influence existing and future priorities, ideas and execution. Bringing together and incentivising skilful and competent teams that can consistently execute is difficult and requires ongoing commitment and contribution. Generating good ideas for what solutions could help to address the priorities can be achieved with far less time than the time required to fully execute an idea. Due to this the importance of having the right contributors in place to support an ecosystem will be of higher importance than the initial ideas that they start executing. High quality contributors will be more easily able to identify and update ideas that are not working through the learning process of executing any ideas. It won’t matter how good the ideas are in an ecosystem if those ideas don’t have a sufficient amount of quality contributors to execute them that can learn and evolve those ideas over time during execution.
# Delegating process decisions
Discussing the implications and importance of voter delegation for the different funding processes
Understanding the importance of voting delegation is the acceptance that not everyone in an ecosystem has to fully participate in every decision that gets made. Delegation is an important part of giving voters a choice in how they want to participate and making it easier for complex ecosystems to scale through making it easier and more flexible to vote.
Community members should be able to participate in the areas they care about which could be areas they have are most interested in or that they have the most expertise or knowledge in. For areas that someone is less interested in, have less capacity for or don’t have the same levels of experience or knowledge those same community members may decide to delegate their vote to other people in the community.
You cannot prevent people from delegating their vote to other people as the ability to delegate could be achieved independent of any existing system or process. For instance, one community member may have a good understanding of finance and what is happening in that area of the ecosystem but have little understanding of what is happening in the gaming area of the market. In this event the community member may decide to simply identify anyone they trust or respect in the ecosystem and find out what their opinion online is or ask for it on how they would allocate their vote for gaming related funding decisions. This person would then vote for those options themselves, however the decision itself was actually delegated to someone else who helped them make it for them. A systemised version of delegation would instead allow the voter to delegate their voting power to these other peoples digital voting account or wallet. The benefit of this approach is then it is very clear how people are participating in the ecosystems governance and help highlight what percentage people are participating in the decisions made versus delegating them to other community members.
## Example differences in community member participation
The above example helps to illustrate how different people may want to participate in an ecosystems funding decisions:
* **Person A** - Person A has little capacity or interest in participating in the governance decisions that are involved in a funding process. They have other interests and commitments outside of the ecosystem. They are part of the ecosystem and care about its future but simply don’t have the time available to commit to making well informed decisions. Person A does have some knowledge and opinions towards what priorities are most important for the ecosystem based on their own involvement and knowledge, these areas are all Person A votes on themself. For the remainder of the funding decisions person A prefers to delegate their vote to other community members whom they trust.
* **Person B** - Person B actively contributes to the ecosystem and because of this has a thorough understanding of what ideas are feasible and impactful for the areas of work they are contributing towards. They participate in some of the priority selection that is relevant to that work and delegate the rest to other people who they know have a good understanding of the other areas in the ecosystem. As Person B interacts with many of the contributors in the ecosystem they have experience working with many of them meaning they are well informed and like to participate in selecting which contributors are most suitable and effective for the ecosystem.
* **Person C** - Person C spends a lot of time understanding what is happening in the ecosystem and the key problems and opportunities that are emerging across the industry, in technology generally and within the ecosystem itself. They apply this depth of understanding to help with comparing and voting on every different suggested priority in the ecosystem and then spend the remainder of their time looking at which contributors would be the most suitable for achieving the priorities which are most important. Person C is not part of the execution itself and doesn’t currently have the capacity to fully understand the implications of each of the ideas that get presented. For any idea decision areas they have instead delegated most of that responsibility to the contributors that they identified and selected due to their skill sets and experience.
**What could be delegated?**
The knowledge available within an ecosystem is what will get used and applied by community members to all of the funding processes. On its own knowledge is not a process that is delegated. Instead it is more of a combination of delegating the process of understanding and applying an ecosystem's knowledge with one of the other funding processes of selecting and voting on which priorities, ideas or contributors are most important or suitable.
**Why might people delegate?**
It will be difficult to expect every person in an ecosystem to spend the time required to learn and apply all of the information available to make well informed decisions that cover the entire funding process. If people want to have more control and agency over how they use their time and how they want to participate it will make sense for those people to have the choice to delegate some or all of that responsibility of understanding different knowledge areas to apply to the funding process decisions to someone else when this is necessary.
**Who could people delegate to?**
Ecosystem members would be delegating their vote to other community members for situations where those community members can effectively help with selecting suitable priorities, ideas or contributors.
**Overall likelihood of delegation**
For larger ecosystems the likelihood of people needing to delegate their vote for some of the different areas of the ecosystem is very high due to the sheer amount of information they would have to consume and apply to understand what is happening in the wider ecosystem. Due to this high complexity it might be likely that people decide to delegate some or all of their vote towards people who can handle some or all of the priority, idea and contributor selection processes for certain knowledge areas they are less interested in or have less capacity to contribute towards.
**What could be delegated?**
Creating and selecting good priorities revolves around understanding and applying the available information in an ecosystem to make more informed decisions on what the most pressing problems and opportunities are for the ecosystem to address.
**Why might people delegate?**
A community member may decide to delegate some or all of this responsibility to someone else in the community due to their lack of time or experience in different areas of knowledge required. The reasons to delegate priority creation and selection would be because of the need to have a thorough understanding of different ecosystem areas to make well informed prioritisation decisions. Some people may want to participate in this entire process however others may only want to participate in a subset of areas that they want to allocate their time to due to their own personal interests or experience. Others may not be interested in participating at all but do have a preference on who is suitable for helping with setting priorities.
**Who could people delegate to?**
Community members would delegate their vote to other community members which are contributing towards priority creation and selection.
**Overall likelihood of delegation**
The larger and more complex an ecosystem becomes the more likely it will be that people do not have the full capacity or interest to fully understand the knowledge required to make well informed priority setting decisions that take into account the current situation across the wider ecosystem. In this scenario many voters may decide to delegate some or all of their vote to other individuals that can effectively handle the prioritisation process in each of these important areas.
**What could be delegated?**
Ideas are created to help address the different priorities. The process of creating ideas is already delegated to whomever decides to contribute towards creating solution ideas that could help with addressing any of the ecosystems current priorities. The selection of which ideas are the most promising would be the decisions that are potentially suitable for being delegated to someone else.
**Why might people delegate?**
The ideas generated to address priorities could cover a range of possible ideas. Each of these ideas could be applying a vast variety of skill sets, technology and approaches. Due to this there could be a moderate to high amount of complexity and depth of understanding required to actually understand whether an idea would actually work and how it would help the ecosystem. If someone has never created a software application before it would make it more difficult for them to assess the feasibility and quality of the technical aspects of these ideas. A skills or experience gap would be a key reason people might decide to delegate their vote to another community member who is more suitable to assess those types of idea.
**Who could people delegate to?**
Community members could delegate their vote to either other voting community members or to the contributors who are executing these ideas.
**Overall likelihood of delegation**
Ecosystems that have a higher complexity of ideas that go through the funding process could expect a larger need for voters to be able to delegate some or all of their vote to people that have the required expertise and knowledge to understand the potential impact and feasibility of those different ideas. Another reason for potential delegation is because of the sheer amount of ideas that could be suggested to address different priorities. In this event it would likely be that a high amount of participation would be needed to compare and understand the full potential of these ideas suggested. Either of these scenarios increases the likely need for delegation due to the scale of participation required or the overall complexity.
**What could be delegated?**
The execution of ideas is already delegated to contributors that get selected by the ecosystem. The main area of focus is whether the contributor selection process is delegated or not that determines which contributors are compensated to execute the most promising ideas.
**Why might people delegate?**
Community members need to understand the priorities that get selected, at least roughly understand the most promising ideas in the ecosystem and then also have a sufficient enough understanding of the skills and experience required in these different areas to make well informed decisions on which contributors would be most suitable. Community members may not have the capacity or interest in understanding the available knowledge, priorities and ideas enough to then select the right contributors for the ecosystem.
**Who could people delegate to?**
Community members may decide to delegate some or all of their vote to other community members to help with deciding who should be selected as a contributor.
**Overall likelihood of delegation**
Community members don’t necessarily need to have a large depth of understanding of the wider ecosystem knowledge to participate in contributor selection. If a community member is sufficiently happy with the execution of the priority setting process then they could simply decide to just participate in voting on which contributors would be suitable for addressing those priorities. The higher the complexity of the ideas required to address these priorities the more there would be a need for the voters involved to understand the surrounding knowledge and possible ideas so they can apply this knowledge more rigorously for determining which contributors would be effective at executing those more complex ideas.
# Process complexity
Discussing some of the complexities involved in the funding process
Disbursing treasury assets to create impactful outcomes is a complex task that has a number of processes and factors to consider at each stage of the process. The pace in which Web3 ecosystems change, such as how they operate or what applications and services are available, only increases the complexity of treasury funding further due to the fact that each process will need to be able to respond and react to these constantly changing environments.
Each of the knowledge, priority, idea and execution steps involved in the funding process share a number of complexities that make it more difficult to allocate treasury assets and scale the process:
* **Information complexity** - Each part of the process highly benefits from participants having a strong grasp of the relevant information in the ecosystem to make informed decisions. Learning this information and handling the quantity of information that is available makes for a highly complex process to scale due to the time commitment that would be required by many community members. The more time it takes for community members to participate in a funding process the more you could expect to see voter apathy or disengagement in the process due to the high complexity and time commitment.
* **Decision complexity** - The funding process requires voters to make a number of important decisions around selecting priorities, ideas and contributors which each will influence the resulting impact achieved by the treasury funding process. Each of these process decisions can have multiple options each with different opportunities and tradeoffs. The depth of information required to make well informed decisions only increases this complexity further.
* **Game theory complexity** - When funding is being disbursed to help operate the treasury and fund different initiatives there is usually an incentive to try and game the system for personal gain. This complexity exists for any part of the funding process. Bad actors may try to introduce information that negatively influences the available knowledge in an ecosystem with incorrect, misleading or exaggerated information to support their own narrative. The incentives available can also influence community members to make priorities and ideas that aren’t in the best interest of the ecosystem. They may also try to select contributors that benefit themselves or their own agenda more than it benefits the wider ecosystem. The systems and processes used for treasury funding will need to take into account the incentives that exist in these systems and try to understand and prevent the potential negative outcomes those systems could produce where possible.
* **Participation complexity** - Without enough direct incentives to participate it might be difficult to achieve sufficiently high participation for important ecosystem decisions. The questions that will need to be answered are how much participation is needed to be representative of the communities preferences? What level of participation or delegation from the community is realistic and achievable? What is the total time cost for each individual to participate in each of the funding processes?
**Complexities**
* **Information complexity** - An ecosystem will need to be able to aggregate a vast amount of information and think about its importance when going through the funding process. As an ecosystem grows the amount of available information only continues to grow with it. There is complexity in being able to understand and apply all of this information through the funding process and also difficulty in determining the correctness of every source and how relevant that information is. Another complexity around the scale of the information involved is how to easily present all of this information so that it is easy to understand and digest. Some of this complexity could be reduced through automation such as with software that brings together on-chain data about how an ecosystem is currently being used or for other competing ecosystems.
* **Decision complexity** - Community members who participate in the funding process must determine which information they believe is the most important and relevant for any upcoming decisions. The quality of this information will often become the foundational part of many funding decisions. Deciding which areas of the available knowledge are the most important will take time to determine. Many funding processes might be operating on the fact that most voters will only know a fraction of the potential information required to make informed decisions. The issue with this situation is that it means that voters involved in making funding decisions are doing so based on potentially very limited information.
* **Game theory complexity** - If an ecosystem is using a range of informational sources to help make better funding decisions then there is an incentive for people to try and game that system by creating information sources which are incorrect, exaggerated or misleading. These information sources could benefit themselves in some way or simply be added with malicious intent.
* **Participation complexity** - The sheer amount of information that a community member would need to learn about to be well informed in an ecosystem could take a considerable amount of time. This tie commitment would also be ongoing due to how fast information can change in an ecosystem. The level of commitment required to be well informed is a complex problem to solve. This complexity could easily lead to increases in voter apathy and disengagement. A lack of sufficient understanding is a key reason some community members may choose to delegate their decision making to other people who have presented a sufficiently informed opinion and rationale. Some community members may ultimately lack the capacity or interest to understand and apply all of the available information to make funding decisions.
**Complexities**
* **Information complexity** - Voting community members will need to read and understand a diversity of priorities and any evidence and rationale that supports those priorities. The complexity for priority setting is that voters need to have a sufficient understanding of the available knowledge in the ecosystem about what is currently happening and then also have the complex task of applying that information to think about what problems and opportunities exist.
* **Decision complexity** - The decision complexity for priority setting is determining which of the identified problems and opportunities are the most important for an ecosystem at that given point in time. This means voters need to take into account the current state of the ecosystem, how that priority might be impactful now and what knock on effects it may have compared to selecting other potential priorities.
* **Game theory complexity** - Bad actors are incentivised to make priorities that mislead an ecosystem to areas that are less impactful or towards priorities that are directed towards their own self interest over the interests of the wider community.
* **Participation complexity** - The amount of ecosystem knowledge that community members need to know about to make informed decisions for the priority setting could make it increasingly difficult to get a large amount of participation as an ecosystem scale.
**Complexities**
* **Information complexity** - Articulating an idea with why it is potentially impactful and feasible, how it would work and roughly how long it might take is a time consuming task that can result in a moderate to high amount of information for voters to review. As the number of ideas increase the information complexity will also keep increasing. This amount of information makes it more difficult for voters to have sufficient time to understand all of the ideas being presented to them.
* **Decision complexity** - Assessing ideas that are addressing ecosystem priorities requires a sufficient level of understanding of the implications involved in the idea and whether it is truly feasible or impactful. Voters then need to compare the diversity of ideas presented to them to then make a decision on which ones are the most promising. There are many variables that will influence whether an idea will become impactful or not such as market timing, current technical limitations and any existing user behaviours. All of these areas contribute towards increasing the overall decision complexity of selecting promising ideas.
* **Game theory complexity** - Bad actors that are looking to direct more effort and resources to bad ideas or ones that are not beneficial to the ecosystem could create ideas with this bad intent. Those same bad actors could also try to discredit other ideas to better benefit the chances of their own.
* **Participation complexity** - Understanding, comparing and voting on the most promising ideas would be very time consuming. This complexity could limit the willingness and capability of community members to participate in the process. Voters may want or need to delegate some of this responsibility to others to make it more manageable and feasible to participate.
**Complexities**
* **Information complexity** - The amount of information that gets included about each contributor would add to the overall information complexity that voters would need to be able to handle. Voters need to be able to determine the correctness of the information being presented to them such as whether the education and professional background is correct and relevant to their area of focus. Historical participation in different ecosystems along with any contributions they have made would be other areas that voters will also need to spend time on to be well informed.
* **Decision complexity** - Voters are challenged with looking at the potential contributors willing to help the ecosystem and comparing those contributors with each other to make informed decisions when selecting suitable contributors. Voters need to take into account the current priorities and ideas within the ecosystem and whether any of the potential contributors are well suited.
* **Game theory complexity** - There is an incentive for people to lie about their educational and professional background to gain an advantage in being selected in the process so they can receive compensation for working in the ecosystem. Bad actors may look to discredit other contributors with false accusations or misleading statements.
* **Participation complexity** - Voters will need to spend a sufficient amount of time to compare and consider the implications of selecting different people to contribute towards the ecosystem. Contributors would be committing large amounts of time to actually execute some of the ideas being suggested in the community. Ongoing effort might be needed to verify the claims of contributors to ensure the voting process is not too time consuming for voters. For contributors the incentives involved will need to be reviewed and adjusted to ensure that competent and quality contributors actively want to participate in the ecosystem.
## Approaches for reducing complexity
**Improving system and process design**
The most obvious way that complexity can be reduced for the funding processes is by constantly improving and iterating each of the processes and systems involved. Improving these processes will mean thinking about what data must or could be included, how people will interact with each other during these processes, what decisions are required and what area of governance can be removed, how information can be easily presented to voters and how incentives could be better aligned with creating impactful outcomes. All these areas amongst others will need ongoing reflection and improvement to help make an effective treasury funding process.
**Expert insight & analysis contributions**
Inviting and incentivising experts to contribute towards the different funding processes within an ecosystem can make it easier for other community members to learn about the most important factors and nuances that help them make more well informed decisions. Expert analysis could include reports covering the different problems or opportunities that exist for an ecosystem, reports on what is happening across the industry, or analysis that provides insights and data points around what is actually happening on-chain across different ecosystems. These are just some examples of how experts could effectively apply and analyse the available information in an ecosystem to make useful insights that help make voters more informed when making different decisions.
**Process delegation**
Delegating the responsibility of decision making for some of the funding process is another way that complexity could be reduced. This could be achieved in a few ways. Some people may delegate one or multiple of the priority, idea or contribution selection process steps to another person. Others may delegate all of the process steps to another person, but only do this for a certain focus area such as gaming or finance. These might be areas they don’t fully understand or that they don’t have time to spend on. Delegation could also be a blend between these two different approaches depending on how a community member wants to participate in any of the funding processes.
# Funding process differences
Exploring some of the key differences between existing funding processes and Web3 ecosystems
There are a number of similarities and differences between corporation and nation state funding processes with Web3 ecosystem funding processes. Some of the key differences that have an impact on the whole process is that Web3 funding processes will often have a higher number of voting participants, a lower amount of incentives to reward voters and a lower amount of voter responsibility.
Many Web3 ecosystems still have the founding entities, often in the form of a foundation, that help with managing an ecosystem's treasury. These foundations are often able to make unilateral decisions about what should be prioritised in the ecosystem when deciding how to disburse treasury assets. This has the obvious issue that it is more centralised in decision making and not necessarily representative of what the communities preferences currently are. Although this structure may have been an easier and quicker starting point for many Web3 ecosystems to start with, it is often not a preferred long term solution. Much of the appeal of the cryptocurrency movement is the idea that centralised actors with too much influence and power can be removed through the adoption of blockchain and distributed ledger technology. To fully remove middlemen and centralised actors it will be important for Web3 ecosystems to develop treasury systems and processes that help with migrating the voting power and influence over treasury funding towards the entire community.
**Number of participants**
Decisions in nation states and corporations can often be influenced and limited by leadership roles that exist in the organisation. This could be founders or the board of directors in corporations or elected officials and employees in leadership roles in nation states. Some organisations may decide to include a larger number of employees for some or all of their decision making. The amount of governance participation can often be lower in corporations and nation states than some of the emerging Web3 ecosystems due to the fact most Web3 ecosystems are actively looking to increase community participation across the funding decisions over the long term. Increasing the number of people involved in funding decisions can help with making a more inclusive and representative process however this comes at the cost of the total time it takes for an ecosystem to become well informed when making funding decisions. Increasing the number of participants for making decisions also means that a sufficient amount of time will need to be provided to these voters so they have enough time to vote on any decisions. In contrast when the number of voting participants is small these decisions could occur more quickly such as in face to face meetings.
**Voter responsibility**
For nation states and corporations the decision makers involved often have a high level of responsibility to make optimal decisions for their organisations - these stakeholders are usually fully compensated to do so. These decision makers are responsible to the shareholders in corporations and to the public in nation states. In Web3 ecosystems voters often do not have any contractual or even social agreement with the network that they have any responsibility to vote in a way that is in the best interests of the wider community. Voters will usually represent their own interests and preferences when making their own decisions, and would not be personally held accountable for any negative outcomes that arise due to their voting choices. Trying to increase the amount of voter responsibility in Web3 ecosystems could be a potentially effective way for encouraging voters to put more time and consideration into ensuring they are making optimal and well informed decisions.
**Voter incentives**
The leadership involved in making decisions across nation state and corporation treasuries will do so often in a fully compensated position and work full time for the organisation. This helps give them more capacity to make well informed decisions and better aligns the incentives with making optimal decisions. Some Web3 ecosystems might offer an incentive for voters to participate in the funding decisions, however it is rare for this compensation to equate to anything that representative or even near a full time salary equivalent. This difference in incentive is important as it can influence how much time people are willing to use for participating in complex and time consuming governance decisions. This difference in incentives emphasises the importance of developing simple and efficient governance processes that help to make it easier for people to participate in important ecosystem decisions.
## Considerations for Web3 funding processes
The number of community members involved in Web3 ecosystems could eventually represent numbers that match and exceed existing nation state populations. This factor poses a growing problem for Web3 ecosystems in determining how its treasury funding processes will be able to handle this growing scale of voter participation. The complexity involved in handling this scale is increased due to lower incentives and the low responsibility that voters have to make well informed decisions. Taking these factors into account some considerations can be made about what potential factors will be most important for creating effective Web3 funding processes that can effectively scale and generate consistent impact.
**Simple governance decisions**
For Web3 treasury funding to scale and handle a growing number of voting participants it will need to be extremely selective on what governance decisions it requests the community to have responsibility over. It will be difficult to expect a large population of voters to spend a meaningful amount of their spare time on becoming well informed about many complex governance decisions if they are not properly compensated for that effort. Treasury funding processes will need to determine exactly what decisions and areas are essential for voters to allocate their time towards and what decisions and areas are less important. The less important decisions and areas will be the suitable candidates to become delegated responsibilities that other people in those ecosystems could handle. Streamlining and simplifying treasury funding governance will be an area of paramount importance if Web3 ecosystems want to scale their treasury systems to handle millions of users.
**Automated systems & processes**
A number of systems and processes will be needed to operate a Web3 treasury at scale. These systems and processes could see an increasing amount of information complexity and participation that they need to handle. Contribution efforts will be needed to automate these systems wherever possible to reduce the time it takes to participate in funding and to reduce the complexity so that a larger number of community members can feasibly participate. One area that will likely grow in relevance is the application of AI to support ecosystems in their decision making ability and handling large volumes of information.
**Delegated responsibilities**
Large communities will often need to accept the fact that every community member does not have to or need to participate in every possible voting decision there is within the community. Web3 ecosystems will want to determine how a voter is able to delegate responsibility and voting power to other individuals or groups of individuals when they feel this is appropriate. An important outcome that Web3 ecosystems may want to achieve is that community members are given the ability to express their exact preferences and opinions in any of the funding decisions and that they can easily participate in the exact areas that interest them or that they have expertise in.
**Increasing voter commitment**
An emerging issue for Web3 ecosystems is how easily it is for community members to financially leave one ecosystem and join another by simply selling and buying two different assets. This is a risk for treasury funding as voters could be deciding where large sums of incentives are being directed. Voters that are able to vote on these outcomes but then can immediately sell their assets creates an attack vector that the ecosystem will need to consider. Web3 ecosystems will need to consider solutions such as lock-up periods or other mechanisms that help to minimise or prevent the risks around malicious actors with low commitment to the ecosystem trying to waste or misuse an ecosystem's treasury assets that get released through funding.
**Reducing attack vectors**
Web3 treasuries could eventually be disbursing vast amounts of incentives to help with improving and operating the network at scale. Bad actors will look for ways to exploit the incentives that are being offered. For Web3 ecosystems that want to grow and handle a large scale of participants and incentives. Treasury systems will need to be self correcting where possible to prevent bad actors from repeatedly exploiting the funding process. Incentives will need to be highly aligned so that it makes more sense for actors to act in a rational and positive way rather than to try and game the system. Technology such as self sovereign identity (SSI) and reputation systems will become an increasing part of the solution for identifying and preventing bad actors from abusing the funding process.
# Token funding vs network funding
Comparing the differences between token funding and network funding
Ecosystem contributors need a sustainable way to fund the contribution efforts involved in executing impactful ideas. Two approaches that are worth comparing is token based funding, where projects raise investment from minting a project token and network funding, where a networks treasury can fund contributors directly to work on different ecosystem initiatives.
Token based funding has been a popular way for projects to raise funding to pay for execution efforts across different Web3 ecosystems. In comparison, network funding exists in many ecosystems, however it commonly does not fund contributors directly. The suggested approach of funding contributors directly has emerged after analysing the different ways a networks treasury could operate a funding process. Open source contributor funding emerged as the most promising approach for compensating people that execute different initiatives in a Web3 network. This analysis will assume that the network funding process is adopting a contributor funding approach.
**Circular economies**
Both of these approaches can represent a circular economy. Network treasuries can generate income from network transaction fees or taxes and this can then help to fund initiatives that increase the amount of use cases and adoption. Tokens issued by projects can also introduce token based fees that users would pay when using their protocols and applications. These circular based economies can be an important part of making a sustainable model for generating income over the long term and this can help with maintaining and improving the network itself and any protocols and applications. To better understand why token funding might not always be very suitable as a funding approach it will be worth thinking about some of the ideas that can be implemented in Web3 ecosystems and whether they are suitable ideas that could be implemented as a circular economy:
{% content-ref url="/pages/xWD7rrV4eucmB5YabLnL" %}
[Circular economy ideas](/approaches/token-funding-vs-network-funding/circular-economy-ideas)
{% endcontent-ref %}
**Existing protocols and software library examples**
Web3 ecosystems can benefit from considering different open source libraries that already exist in Web2 environments such as internet protocols, utility libraries and front end and back end frameworks. These considerations help with thinking about the importance of funding open source initiatives in Web3 ecosystems. These initiatives aren’t intended to generate a financial return on investment. Instead they are focused on generating impact for the ecosystem. Some Web2 protocols and software libraries examples to consider:
{% content-ref url="/pages/HQfONzC7Ic20f4Hg2yjf" %}
[Web2 protocols & software library examples](/approaches/token-funding-vs-network-funding/web2-protocols-and-software-library-examples)
{% endcontent-ref %}
## **Approaches for funding ecosystem initiatives**
The two main funding approaches we're going to compare include:
* [**Token funding**](/approaches/token-funding-vs-network-funding/token-funding) - Projects raise funding by minting a token that is then sold to investors
* [**Network funding**](/approaches/token-funding-vs-network-funding/network-funding) - Projects raise funding through the networks treasury and funding pays for contributors directly. Contributors could work on one or multiple ideas at a time.
To compare these ecosystem funding approaches a number of [factors have been considered](/approaches/token-funding-vs-network-funding/ecosystem-funding-factors-for-consideration) and then applied to each approach to try and determine any strengths and weaknesses of each one.
To compare these ecosystem funding approaches a number of [factors have been considered](broken://pages/eWEZh1WjayPJdEAvb5og) and then applied to each approach to try and determine any strengths and weaknesses of each one.
**Funding the network, protocol and application layers**
These funding approaches can also be considered within the context of the different layers of a Web3 ecosystem. The network and infrastructure represents the base layer of the ecosystem. The network enables the development of a number of protocols that can be deployed on top of the network, this is the protocol layer. Applications can then integrate and use any of the functionality or protocols that are available on the network to create end user experiences, this is the application layer. Read more:
{% content-ref url="/pages/WIlKeppii8LqDywI3IUH" %}
[Funding the network, protocol and application layers](/approaches/token-funding-vs-network-funding/funding-the-network-protocol-and-application-layers)
{% endcontent-ref %}
**Key takeaways**
* **Greatly reduced complexities when using network funding** - Token based funding introduces a number of complexities for contributors that commit to minting a token for their project. Network funding gives contributors a large amount of flexibility to execute one or multiple ideas and it also removes the complexity of committing to any long term utility for a token that could result in a more complicated solution for the end user.
* **Many ideas do not need a token -** Many of the software and non software ideas that were previously identified do not need to create a token and attempt to create their own a circular economy. Adding a token that does not have a sufficient justification can increase the amount of governance and economic complexities involved in executing the idea. It also adds a personal burden for the contributors, as they need to maintain this token over time and even in situations where it might not be an impactful initiative to work on anymore. Tokens can make contributors more responsible and attached to a single idea they are working on even though there might be more impactful ideas they could work on that could more effectively benefit the ecosystem.
* **Network funding helps to produce more fully aligned incentives -** Funding that is disbursed from the network's own treasury helps to produce more fully aligned incentives for fully supporting initiatives that could generate impact for the ecosystem. The wider community can support initiatives that best support the network and produce the biggest chance of growing and improving the ecosystem. Network funding incentives help to remove the misaligned and partially aligned incentive problems due to the removal of project tokens. Project token holders are incentivised to defend their own interests at the expense of what might be best for the wider ecosystem.
* **Network funding is more important for funding maintenance and improvement of the network itself** - As highlighted in the analysis above around funding the network, protocol and application layers, the closer the software is to the network and infrastructure the more important it becomes that the code is open source and verifiable by the community. It also becomes more important that the network can sustain these initiatives itself over the long term. Achieving this helps to ensure the network will remain competitive over the long term. Network funding is highly suitable for supporting network and protocol efforts over the long term.
**Ecosystem funding approaches analysis**
{% content-ref url="/pages/jp2doFiZrf8uLWDsSLJ5" %}
[Ecosystem funding factors for consideration](/approaches/token-funding-vs-network-funding/ecosystem-funding-factors-for-consideration)
{% endcontent-ref %}
{% content-ref url="/pages/U4wJhbLS2zl2ui9P68nJ" %}
[Token funding](/approaches/token-funding-vs-network-funding/token-funding)
{% endcontent-ref %}
{% content-ref url="/pages/8KYj1Fd34FOsGHYHtbMC" %}
[Network funding](/approaches/token-funding-vs-network-funding/network-funding)
{% endcontent-ref %}
# Circular economy ideas
Listing out Web3 ecosystem ideas that could be considered when issuing a token to create circular economies
There are a number of software projects that could benefit from trying to create a circular economy through the usage of a token. However most of these ideas could also be implemented by using the networks treasury funding to sustain long term development. This means a token based funding approach would not be necessary.
**Software ideas**
The following ideas could create a circular economy with their own token, they could also charge fees to become self sufficient using the network coin and finally they could also be funded by the networks own funding process.
* Stablecoin's - e.g. USD token
* Security tokens - e.g. Bonds, stocks
* Real world asset tokens - e.g. Tokens that represent commodities or a house, car etc.
* Soulbound tokens - Tokens that are issued and designated to a single individual or entity and are not transferable.
* Privacy tokens - A token could wrap an existing coin from a public chain and then make the transactions private.
* DeFi protocols - DEX, borrowing & lending, synthetics, derivatives, CDPs
* DAO, governance & identity tooling
* Utility software libraries - For building smart contracts, transaction builders etc
* Network infrastructure tools & libraries
* Security reviews & code audits
* Scalability solutions
* Indexers, explorers & data oracles
* Wallets
**Other non software ideas**
There are a number of non software ideas that could benefit from the networks treasury funding. These are commonly less suitable for being funded with the creation of a new token.
* Research & analysis
* Demos & onboarding
* Articles & blog posts
* Hackathons
* Contributor mentorship
* Community hubs
* Workshops & courses
* Ecosystem educational resources
* Translation support
* Standardisation efforts
**Reasons a token might be useful or necessary**
* **Token utility** - Ideas might need a token for unique use cases and functionality that they can't achieve with the networks own coin.
* **Customisation of token** - Tokens can be customised for different use cases such as how the supply changes over time, what parts of the token are immutable or mutable or how that token can be used in different applications and environments.
* **Token autonomy** - Having a separate token means the project team and surrounding community that use that token would have full autonomy to update and replace the token as needed for their projects specific use cases.
# Web2 protocols & software library examples
Listing out example Web2 protocols and software libraries to consider when thinking about future Web3 ecosystem protocols and software libraries
Web3 ecosystems could develop a number of new protocols and software libraries that don’t require a token. These projects could be gradually improved and maintained over time. Listing some example Web2 protocols and software libraries can helps to provide some evidence that utility and governance based tokens might not be necessary for a large number of projects in Web3 ecosystems.
**Network protocol examples**
* [HTTP](https://en.wikipedia.org/wiki/HTTP)
* [TCP/IP](https://en.wikipedia.org/wiki/Internet_protocol_suite)
* [FTP](https://www.notion.so/TODO-8dd367f2ad0a4ccca555e781fef1215c?pvs=21)
* [SMTP](https://en.wikipedia.org/wiki/Simple_Mail_Transfer_Protocol)
**Software library examples**
* [Lodash](https://lodash.com/) - Utility library
* [Express](https://expressjs.com/) - Backend web framework
* [React](https://react.dev/) - Frontend web framework
**Advantages**
* **Faster integration** - Users of these protocols and software libraries can adopt them immediately and integrate them into their own solutions helping to speed up their own development efforts.
* **Modifiable** - Projects using these protocols and software libraries can take and modify the code to help with addressing any of their own specific use cases.
* **Self determined upgrades** - Users will self determine when they want to upgrade from one version to another. If they disagree with a certain change or don’t want to allocate the effort to making an upgrade they could remain on the same version.
* **Predictable** - Each version of these protocols and software libraries will usually come with a change log of what has changed since the last version. Documentation is also often available that outlines how the software works and how it can be used.
* **No required governance participation** - Anyone using these protocols and software does not need to be involved with how they are developed or be worried about some governance decision suddenly affecting their own usage of the software. Users can let the contributors involved in improving those protocols and libraries handle what changes should be made based on community feedback. Contributors using this software would decide when to adopt any new releases. Teams looking to maximise their execution efficiency will commonly prefer to not be engaged in the oversight and governance of every open source project they use and instead let that responsibility be delegated to other contributors.
* **No need to purchase a token** - Anyone using these protocols or software can express their preferences and opinions in the forums, code repositories and other available communication channels about what could be improved or what opportunities might exist. No token needs to be purchased for them to participate in providing feedback and having some form of influence over the direction of these protocols and software libraries. They are free to fork the code and make their own version if they need to!
**Drawbacks**
* **Fundraising to pay for contribution efforts** - These protocols and software libraries can be highly complex and require highly specialised professionals to help with maintaining and improving them over time. Funding can often be problematic for some projects due to the fact that the protocols and software libraries themselves are open source and free to use meaning they are not a revenue generating business. Many of these projects are reliant on large sponsors, often from corporations but also from governments and individuals.
* **Excessive sponsorship influence** - The largest sponsors to these protocols and software libraries could easily have a larger amount of influence on the development direction of these solutions due to their financial involvement. Projects can benefit from having higher amounts of sponsorship diversity to better protect and represent the interests of the entire user base of these protocols and software libraries.
**Key takeaways**
* **Tokens are often not necessary** - Tokens could introduce more complexities for people that just want to use and integrate these existing open source protocols and software projects. If every protocol and software project added their own token the users of these solutions would then need to be concerned about the price of those tokens and how it impacts how they can use the solutions available and also be concerned with how token governance could impact their ongoing usage of these solutions. Utility tokens in some projects could end up introducing malicious actor complexities due to the risks that a small group of actors manages to get hold of a large amount of tokens to maliciously impact the usage or direction of a protocol, application or software library.
* **Opportunity for addressing funding issues** - A big opportunity for Web3 ecosystems is that they have the ability to create circular economies that can provide ongoing financial support for building and sustaining open source protocols and software libraries. These emerging Web3 ecosystems massively benefit from having a robust and thriving open source ecosystem. Their entire user base can benefit from these initiatives in their own projects. Increasing the usage of network treasury funding could help with achieving this outcome of sustainable funding for open source development.
# Ecosystem funding factors for consideration
Factors for consideration for different ecosystem funding approaches
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Funding complexity**
* **Description** - Network improvements, protocols and applications will all need a sufficient amount of access to funding to pay for the contribution efforts involved with developing high quality software. How an ecosystems funding flows through the network will influence the incentives that exist and how easy it is for contributors to sustainably receive funding.
* **Maximum score** - 5, Very important. Access to funding is a vital part of making a sustainable ecosystem over the long term and paying contributors to improve and maintain the network whilst also developing new protocols, applications and software libraries.
* **Scoring questions**
* **Public goods funding** - How does the approach influence how contributors receive funding and does this approach increase or decrease the ease and complexity of funding publics goods? Does the approach help to increase a communities access to open source software?
* **Upfront commitment complexity** - Does the approach increase the amount of upfront commitment and complexity for the contributors due to how funding is made available?
* **Investment complexity** - How would funding be allocated to the ideas being suggested? Who would need to be involved in that decision and who’s capital is being used? What are the implications for projects that are not as suitable for creating high returns on investment? Do the ideas that are competing with established players have more or less access to funding?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Contribution flexibility**
* **Description** - Contributors can work on many different ideas to generate impact in an ecosystem. An ecosystem can benefit from the top performers being able to easily align themselves with the execution of initiatives that can generate the most impact for the ecosystem.
* **Maximum score** - 5, Very important. Contributors being able to direct their efforts to the most impactful initiatives could be of paramount importance to the stability and development of a network. Critical problems or sudden opportunities can be more quickly identified and addressed if contributors are able to allocate their time towards the most important initiatives.
* **Scoring questions**
* **Contributor commitment complexity** - Does the approach increase the amount of commitment a contributor needs to make when executing an idea? What contribution problems could this approach cause?
* **Scoring** - Higher flexibility is good (Score - 5). Lower flexibility is bad (Score - 1).
**Collaboration complexity**
* **Description** - How funding flows through an ecosystem can have a large influence on the amount of collaboration that occurs due to the structures and processes that have been put in place and the incentives that this produces.
* **Maximum score** - 5, Very important. An ecosystem that is more collaborative and aligned in executing similar ideas could be more performant at generating impact across the ecosystem. If funding encourages more competition over collaboration there is a risk that contribution efforts are increasingly wasted due to duplicated outcomes.
* **Scoring questions**
* **Collaboration incentives alignment** - Are other individuals and teams incentivised to collaborate with other projects? Are the incentives more aligned for collaboration or competition?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Varied outcomes complexity**
* **Description** - Using a token or network for funding different initiatives can have a number of positive or negative implications on the different potential outcomes that can occur when executing an idea.
* **Maximum score** - 5, Very important. Executed ideas can create very different outcomes and the skill and competencies of each contributor could be relevant to a wide range of ideas. The most adopted funding approaches will impact how effective a Web3 ecosystem is at responding to these different potential scenarios.
* **Scoring questions**
* **Contributor stops working on project** - What happens if a contributor decides to stop working on a project? Does the contributor continue to receive income? What further impact would likely be generated by this project?
* **Contributor works on another project** - What issues exist when a contributor wants to work on another project? What complexities and incentives exist that might prevent a contributor from doing this?
* **Limited ongoing contribution effort is needed** - What happens if there is a limited amount of ongoing contribution effort needed for an idea? How does the income get used? How could the contributor use their time to make impact for the ecosystem? What complexities does this situation create?
* **Small to moderate idea success** - If a project only receives a small to moderate amount of success how can the contributor respond to this outcome? Does this response represent the most impactful thing that the contributor could do for the ecosystem?
* **Project fails to get adoption** - What happens when a project fails to gain enough adoption? When it becomes more clear that the project would not be successful how would the contributor likely respond due to their commitment and incentives? How does this failure impact the contributor and their reputation?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Governance complexity**
* **Description** - How funding flows through an ecosystem can have an impact on what governance complexities can emerge based on each persons incentives, commitment and involvement with a project.
* **Maximum score** - 5, Very important. The most adopted funding approaches in a Web3 ecosystem can result in different governance structures and behaviours. Decisions and behaviours that emerge from governance may or may not be positive for generating impact for an ecosystem over the long term.
* **Scoring questions**
* **Ownership complexity** - Who owns the project and how could this ownership change over time based on how the project is being funded? What risks and complexities does this ownership have?
* **Leadership complexity** - What complexities exist when identifying and selecting leadership that is suitable for leading and executing an idea? How could this leadership change based on how the project is structured and funded?
* **Governance complexity** - How is the project governed and is there any added governance complexities in operating the project due to the involvement of a token for governance or parameter changes?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Token utility complexity**
* **Description** - Introducing a token has a number of considerations and complexities to consider. The long term value of a token can be highly influenced by the use cases it has and its purpose.
* **Maximum score** - 5, Very important. Projects need to consider the longevity and importance of the use cases for their token before minting a new token that they issue to investors. It is difficult to abandon a token once it has been created. Committing to a token increases the importance that the contributors involved have a high conviction that the token is absolutely necessary for the project over the long term.
* **Scoring questions**
* **Long term use case complexity** - What utilities will the token be used for? Could the base network coin be used instead of the token? If the token is used for governance why does this make sense for the project? Could the project end up with centralised actors who control the project and is this a good outcome for the project?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Community usage complexity**
* **Description** - Adding a token to a project can have a number of implications for the community members using the project due to how the token could influence how the project is used and governed.
* **Maximum score** - 5, Very important. Projects that introduce tokens into their project need to consider what complexities that token could introduce for the end user of the idea. Community members might need to be concerned with how they use the protocol or application due to the tokens utility or they might need to be more aware or even involved with governance due to how it impacts their own usage.
* **Scoring questions**
* **Usage complexity** - How could the project be influenced by the usage of a token? What could community members be concerned with due to how the project is funded and governed? What complexities are introduced for the end user and are those complexities justified?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
# Token funding
Web3 ecosystem projects could issue a token and try to create their own circular economy. An example could be a DEX where the fees are charged in the project's token and then used to help pay for ongoing development efforts. Ideas that issue a token are able to raise funds from community members or anyone outside that ecosystem that are interested in investing in that project or they just want to support what they’re working on.
**High funding complexity (Score - 2)**
* **Public goods funding** - Ecosystems that lean towards more idea token based funding instead of using network funding could result in a lack of support for public goods initiatives that often don't produce a large financial return for the investor. Relying on project token fundraising means that open source projects without a token could end up relying on donations. This could limit the amount of funding they receive, especially over the long term. Open source software in existing systems already face similar problems of it being difficult to receive a sustainable amount of funding. Some of these projects could create a token to raise funds to pay for the contribution efforts however this might be unnecessary for the project. If new projects start relying on the funding that is available in existing established projects there is a higher complexity around how these projects share the cost of supporting public goods initiatives. These projects would have their own investors and their own incentives to ensure their own project succeeds. If one project is more giving than others this could have a negative impact on their own treasury and expenses. The problem of public goods funding coordination becomes even more complex when there are multiple competitors in an ecosystem as now one project giving away more capital than others could create a financial competitive advantage for the other projects that don’t donate as much of their own funds. This behaviour could be to the detriment of the ecosystem. The shared coordination and funding complexities help to highlight the importance of network funding as it creates more fully aligned incentives for everyone to support open source public goods initiatives that can benefit the entire ecosystem. The incentives are only partially aligned for projects with their own tokens to support other public goods efforts in the ecosystem.
* **Upfront commitment complexity** - A project that issues a token to fundraise is making a moderately large upfront commitment about what the project is focused on, how it is going to function and how it will be sustainable and grow over the long term. This is because any investors in that token need to know what they are investing in and are often looking for investments that have a meaningful return on investment. The token would need to have sufficient long term utility to generate that return on investment. It could be difficult to state with much certainty that the token being suggested will actually be necessary and useful over the long term. It is difficult to remove a token once it has been minted and distributed to investors meaning there is a moderate to high complexity for contributors when committing to using a token in a project to raise funds.
* **Investment complexity** - Without any network funding a project would be more reliant on investors or donations to support the execution of their ideas. Investors are incentivised to identify the projects that have the most potential to make a return on investment. This makes it more problematic for high impact projects such as open source protocols and utility libraries as they generate little to no return on investment. It will be difficult for them to receive as much attention from these investors that understandably decide to allocate their capital elsewhere in more lucrative opportunities.
**Low contribution flexibility (Score - 2)**
* **Contributor commitment complexity -** Issuing a project token is a large commitment for the contributors who are responsible for that project. These contributors would then be responsible for making this token is successful and responding to the investors who have helped to fund the project. Receiving investment for a project that has a specific execution plan can limit the ability of contributors to pivot their contribution efforts to other ideas and areas that do not align with improving the project and its token. The usage of a token could limit how contributors generate impact for the ecosystem as now they have to try and make a return for their investors and token holders which could take precedent over allocating their time to other impactful initiatives that don’t increase the value of the project. Another problem is that contributors could become overly committed to creating a sustainable circular economy in a project that wasn’t well suited to this outcome to begin with. Abandoning a project and its token to work on a more impactful initiative could have negative repercussions from investors and community members due to them abandoning a token that people invested in. Community members may decide to not support this group of contributors again even though they might have acted in the best interests of the ecosystem. The contributors commitment to the token they initially issued could hinder their ability to pivot their contribution efforts towards other efforts.
**High collaboration complexity (Score - 2)**
* **Collaboration incentives alignment -** Projects with their own token based economies have only partially aligned incentives to fund open source initiatives that could generate impact for the wider ecosystem. The complexity of open source initiatives that benefit the wider ecosystem is determining who should help with supporting those initiatives and how much should they donate. Token holders from these projects would each determine the projects they want to support which can add an amount of governance overhead complexity as each project might need to make this same decision on what other initiatives its willing to support. The owners of these projects would need to consider how each open source initiative is beneficial to the project itself and how else it could use that funding. Projects that have limited capital and resources that are under more competition with other projects could be less likely to allocate much of their time and capital towards ecosystem public goods initiatives. Being frugal with their own time and capital could be important for preventing the failure of a project. Project tokens create more of an incentive to compete with other projects rather than collaborate. This is due to the risks around a limited return on investment for the project itself, the risk of failure due to wasting project assets on supporting other initiatives and the risk of giving competitors a financial competitive advantage if they give away assets and others don't. Projects with their own tokens could understandably choose to only focus on their own efforts that help to improve their own project as this will often be the most direct way to increase the value of their token.
**High varied outcomes complexity (Score - 2)**
* **Contributor stops working on project** - Projects in the earlier stages that have not decentralised the project could likely have a larger influence over what happens with any income that is generated by the project. There is a risk that limited impact is generated for that project unless a funding process and incentives are available that can bring in other contributors to work on the project now that the existing contributor is leaving. Projects which are more established could be more likely to have a larger amount of funding available to attract other contributors into the project.
* **Contributor works on another project** - If a project has issued a token it becomes much more difficult for a contributor to work on other projects that aren’t relevant to the projects own token. The larger the number of investors and capital invested the more scrutiny the contributor could face from these investors for not focusing on the project token that they are now responsible for. Contributors could be risking their own reputation and ability to fundraise in the future if they do not solely focus on making their own projects token successful. This can be a bad outcome for the ecosystem in situations where the project token didn’t make sense to begin with and the other projects that a contributor could work on could be far more impactful than what they are currently working on.
* **Limited ongoing contribution effort is needed** - Some projects do not need consistent contribution effort and might instead benefit from periods of little to no contribution effort to allow more time for feedback and usage patterns to emerge. In these situations there is some complexity around how the income that is generated for that project is used. If token income is being used to fund different initiatives that are impactful to the ecosystem, but that are not relevant to the project itself, there is a risk that token holders are conflicted with ongoing support for these efforts. Supporting these other initiatives could come at the cost of reducing the growth and value of the projects own token.
* **Small to moderate idea success** - A project with its own token that has a limited amount of adoption and success has the ongoing incentive for the contributor to continue to try and grow and scale that project. This could be problematic for some projects where there is a limit in how much adoption they might expect over the long term. In these situations the contributors may be able to generate more impact by working on other initiatives, however this could cause conflicts with the exiting token holders.
* **Project fails to get adoption** - Projects that have already issued a token and are showing sign of failure are incentivised to try and improve the project and fix any issues that could make the project succeed. If the contributor gives up too early this could cause conflict with the investors who could even see this as potential theft of their investment capital. If the contributor closes the project down too late then the contributor could have wasted a large amount of time trying to save a project that they already knew was not going to be successful after they learnt more about the market and most likely outcome.
**High governance complexity (Score - 2)**
* **Ownership complexity** - In the earlier stages of the project the original creators of the project would likely have a larger amount of ownership of the projects tokens. This early stage of ownership could be problematic in situations when contributors with a meaningful amount of tokens stop working on the project. Over the long term, if the ownership is distributed between a larger amount of community members there is still a risk around how decentralised this ownership is and what influence these owners could have on the other users of the project.
* **Leadership complexity** - In the earlier stages of the project it would be more difficult for a project with its own token to have a leadership change due to the fact that the original founders would likely have a larger majority of the tokens to vote on who is running the project. This leadership could more easily change over the longer term if the project token can be distributed across more users over time.
* **Governance complexity** - In the short term the main complexities for the project around governance would be if the contributors were looking to stop working on the project or work on other impactful initiatives. They might have a majority share and influence over the project however they could still have a difficult time convincing other people to work on the project and when trying to convince existing token holders that their suggestion makes sense. The longer term governance complexities are that even if the project token is well distributed across many community members there could be an increased complexity with deciding how income is used within that project. The token holders are incentivised to focus on initiatives that improve the tokens own use cases and value however there could be many other initiatives that could be impactful to the wider ecosystem. Community members might need to handle this governance complexity across multiple projects that each have their own token.
**Very high token utility complexity (Score - 1)**
* **Long term use case complexity** - It can be difficult to predict exactly how a project and its token will be used by its intended audience and also how the environment surrounding the project will change over time. A fast moving environment can increase the complexities around finding token utility use cases that will be relevant and useful over the long term. If these tokens become redundant in the future there is a risk of financial loss to the investors. Token based governance is another area of complexity that might not make sense for many projects. Token based governance could result in a small number of community members having a large influence over the direction of a protocol or application that is used by the wider community. This could also be problematic if these token holders could change any parameters such as the fees or how people access features within the protocol or application.
**High community usage complexity (Score - 2)**
* **Usage complexity** - Projects that have introduced a token with different use cases and for governance reasons could create a larger amount of complexity for the end user that they now need to regularly consider. When someone uses the application or protocol they might need to consider how the existing token holders could influence their own usage of that protocol or application. The governance process might be able to influence the amount of fees that these users pay or what features they have access to. This could be a concern for end users who could be unaware of these potentially sudden changes. Users might need to constantly monitor multiple applications and protocols and how these sudden governance changes could occur. Another usage complexity is around how any project income is used as now the users of these projects would be paying for those fees. Community members without any of the projects token might lose the ability to influence how their fees are used to generate further impact and maintain the project.
**Total score = 13 / 35**
# Network funding
Network funding is when the base network uses the genesis allocation, transaction fees or taxes to generate income for the ecosystems treasury that can then be used to fund impactful initiatives. Ecosystems are able to pay for contributors directly from the treasury. Either the foundation behind the network or the coin holders in the ecosystem will be commonly responsible for determining how treasury assets are allocated.
**Very low funding complexity (Score - 5)**
* **Public goods funding** - Funding that comes from the network itself has very high incentive alignment with supporting open source initiatives that help to maintain and improve the ecosystem. Network funding could greatly increase the amount of funding that is available for supporting open source software over the long term.
* **Upfront commitment complexity** - The funding that is made available from the network can be generated by transaction fees or taxes. The community can benefit from supporting open source initiatives that benefit the wider network and ecosystem. Contributors do not need to make any upfront commitments about what will be developed and can instead change their focus at anytime if the funding process is flexible. This means these contributors do not need to make any upfront commitment like they would be if they issued a token. Contributors could sustain themselves over the long term from network funding and create multiple open source libraries that don’t require a separate token.
* **Investment complexity** - Network income would come from transaction fees or other taxes. This means that the entire community that use the network would be the ones who decide which initiatives they want to support using the fees they’ve paid to the network. If the wider community has the ability to influence how this funding is used then can align the incentives for the community to support any promising contributors and ideas that could generate impact for the ecosystem. This could mean funding initiatives that compete with established projects. Community members benefit from supporting the most promising ideas that could generate the most impact for the ecosystem.
**Very high contribution flexibility (Score - 5)**
* **Contributor commitment complexity** - Contributor network funding can make it highly flexible for contributors to work on many different ideas that can generate impact for the ecosystem. Contributor funding can help to achieve a very high level of contribution flexibility. Contributors funded by network funding would be responsible for generating impact for the ecosystem, contributors would have the flexibility to identify the most impactful ideas to work on themselves. If contributors kept moving between too many ideas they might struggle to make a large enough amount of impact for the ecosystem. Contributors that don’t make enough impact for the ecosystem would be less likely to be selected in future funding decisions. Due to the need for contributors to generate impact they would still be incentivised to focus on one idea, or a handful of ideas, as this will better enable them to focus on the most promising ideas that could generate the most impact.
**Very low collaboration complexity (Score - 5)**
* **Collaboration incentives alignment** - Network funding helps to create fully aligned incentives for collaborating across multiple projects. If contributors are funded by the network itself they would be incentivised to identify any shared problems that other contributors are facing and develop solutions that help to address those problems. This could be a great way for a contributor to generate impact. The more impact a contributor makes the more likely it becomes they get selected in future funding decisions.
**Low varied outcomes complexity (Score - 4)**
* **Contributor stops working on project** - If contributors are funded directly by the network they would be able to stop working on a project whenever they believed it made sense to do so. If they wanted to stop contribution entirely then they should be able to stop receiving funding from the network at anytime. Existing or new contributors could continue to help with the execution of any open source project. Open source initiatives that don’t have a token would have less concerns around the original ownership and who has control over what amount of tokens. Open source initiatives are mutually beneficial for anyone to work on.
* **Contributor works on another project** - Contributors that are funded directly from the network itself could move between projects and also work on multiple projects at a time. Nothing prevents a contributor from directing their efforts towards more impactful initiatives. It is the responsibility of the contributor to determine which ideas are the most important to work on at a given point in time.
* **Limited ongoing contribution effort is needed** - Contributors could direct their efforts to multiple ideas at a time so this potential situation wouldn’t result in any conflicting problems or misaligned incentives. The incentives for the contributor are that they work on initiatives that can generate impact for the ecosystem. It wouldn’t matter if an idea didn’t need much ongoing effort to maintain and improve it over time as contributors could work across many ideas as long as they focus on generating impact.
* **Small to moderate idea success** - Contributors being paid directly by the network should be able to decide themselves whether it makes sense to continue to allocate more time towards growing a given protocol or application or whether other ideas would be more impactful to work on.
* **Project fails to get adoption** - Contributors could direct their efforts towards another idea whenever they believed the current idea was not going to be likely to succeed or be impactful enough for the ecosystem. The contributor would be assessed based on their ability to generate impact and not solely on whether any of the executed ideas failed or not. No investors would get financially hurt from this decision as no tokens have been issued. A contributor who had numerous failed ideas but then made a lot of impact with another idea could still be one of the most impactful contributors in the ecosystem.
**Moderate governance complexity (Score - 3)**
* **Ownership complexity** - Open source projects that are funded by the network don’t need to have fixed ownership. Numerous contributors in the ecosystem could be interested in supporting these initiatives. Other projects that are owned by a group of people could also still be supported by network funding. Protocols are commonly well suited to being publicly owned where any contributors can be selected to help with working on improvements and new versions.
* **Leadership complexity** - Network funding could support open source initiatives on an ongoing basis. The main complexities for this approach is that talented leadership might be needed to effectively execute an idea. In these situations a project could benefit from electing or enabling someone to lead these projects to better ensure they are executed as intended. Although this adds some selection based complexity the benefit of a contributor funding approach is that leadership can change over time as the needs of a project changes. Contributors aren’t tied to a single idea and could help with leading multiple projects if this was sensible and beneficial to the ecosystem.
* **Governance complexity** - Projects that have no token and that can receive ongoing funding from the networks funding process could benefit from removing the complexities of using token based governance. Many protocols could be versioned and deployed as new immutable smart contracts after each version update. This could be useful for some protocols as it would remove the governance complexity of directly updating a released protocol and instead the efforts are focused on creating a new version whenever this is needed. People can then migrate to newer versions over time. Some of the governance complexities that can exist with contributor network funding are around determining who should be involved with executing different ideas, how software versions get agreed and committed and how elected leadership is decided for ideas that benefit from more stable and competent leadership.
**Very low token utility complexity (Score - 5)**
* **Long term use case complexity** - Projects that are funded by the network do not need to introduce a token to raise funding. Instead the contributors involved in executing any idea can wait until it is very clear that a token is absolutely necessary. Until that point the contributors can execute the idea using the networks funding process. This removes the complexities around identifying and committing to a token with long term utility as the contributors are now able to learn whether the idea actually gets used and whether a token is even necessary for the project to function.
**Very low community usage complexity (Score - 5)**
* **Usage complexity** - Community members that are using projects that do not have a token could benefit from not needing to be concerned with token based governance decisions impacting their usage of the protocol or application. If contributors deploy immutable open source contracts then the community does not need to be concerned with sudden changes to how the code functions. Removing token based governance can also help with reducing the risks around a suddenly emerging group of malicious actors from capturing a large amount of tokens and voting in a way that could be detrimental to the existing users of the protocol or application.
**Total score = 32 / 35**
# Funding the network, protocol and application layers
Exploring the differences that can be considered when funding different layers of a Web3 ecosystem
## **Network layer**
The network layer includes any blockchain or distributed ledger ecosystem. Bitcoin, Ethereum, Solana, Cardano and Polkadot are all networks. Protocols and applications can commonly be built on top of these networks.
**Complexities**
* **Project tokens only have partially aligned incentives** - Protocols or applications that are building on top of a network don’t have fully aligned incentives to maintain the network itself. Instead the incentives are only partially aligned as although they do benefit from improvements to the network they also have an opportunity cost in situations where they can simply migrate to another network. A project building on top of the network has no obligation to pay for any contribution efforts that maintain and improve the network, instead it could be considered as a form of donation.
* **Importance of self sustainability** - A network that relies on donations from community members or from projects building on top of the network is at a higher risk of stagnation if it fails to generate enough income to pay for necessary contribution efforts to maintain and improve the network.
**Token funding vs network funding**
Blockchain and distributed ledger networks already have their own coin that is used to pay for node operation through fees or taxes. This same coin can be used for generating income for the network. Similar to protocols and applications the network layer could generate income to maintain and improve itself using these fees and taxes. Transactions fees or taxes could represent a long term approach for generating income for the network that can then be used for funding different initiatives. Projects building on top of the network don’t have fully aligned incentives to pay for network maintenance and improvements. Donations are more of a good will gesture rather than an obligation. A network that can generate income to fund its own development is the more appropriate approach to sustainably maintain and improve the network.
## **Protocol layer**
The protocol layer includes any smart contract based protocols that are developed for the wider ecosystem to use. Protocols often implement a specification to solve a specific problem. Protocols could focus on token exchange, borrowing & lending, derivatives, social messaging, game engines or on many other areas.
**Complexities**
* **Long term token use cases** - Protocols that use their own token have a risk that when the protocol matures there might be less ongoing contribution effort needed. If the protocol rarely needs to be updated and maintained there is an opportunity to remove the fees and token attached to that project and make a new deployment that has no fee to reduce the costs for the end user of that protocol. Everyone in the ecosystem can benefit from having protocols that are free to use.
* **Fast changing environment** - It can be difficult to predict exactly how a protocol is going to be used and how it might need to evolve over time. A changing environment could introduce new use cases that change what is required or preferred.
* **Importance of open source** - If protocols are intended as a public good for the ecosystem it is beneficial for the developers who are integrating that protocol into their own solutions to be able to verify and review the code themselves and ensure it meets their requirements and also to verify it’s secure and trustworthy.
* **Ownership is often not desirable** - Similar to internet protocols like TCP/IP, HTTP, SMTP and many others, it is often not desirable for these protocols to be owned by a single company or small group of people that are seeking to generate profit from the users of that protocol. A large part of the value of these protocols is they have been created and provided as a public good for the benefit of society. Anyone is able to use these protocols however they wish to do so. Contributors who are funded as stewards for these protocols can help to maintain and improve them over time. These contributors are often sponsored by stakeholders that are interested in the maintenance and progression of these protocols. Sometimes existing companies contribute the time of their own employees to support these protocols. Web3 ecosystems could highly benefit from this same approach of making protocols that are for the benefit of the community. Protocols do not need to be privately owned or controlled by a small number of people or subset of the community. Web3 ecosystems have the opportunity to fund contributors on an ongoing basis to help with the maintenance and improvement of these emerging protocols.
* **Preventing misuse and theft** - If a token is issued for a protocol there is a concern about what those token holders are able to do with any controlling ownership amount. Concerns could emerge around the use of kill switches, parameter changes or if the owners can stop or alter the usage of the protocol in anyway.
**Token funding vs network funding**
Some of the issues with introducing a token for a protocol are how the environment could change over time and how the long term use cases of the token may not be sufficient to justify the token. A token can also introduce a situation where the is a small number of actors or a subset of the community who has control and influence over a protocol that was intended to be a benefit to the wider ecosystem. If these owners are able to misuse or abuse their influence over the protocol this could be adding an unnecessary risk that is not beneficial to the ecosystem's stability. Issuing a token for a protocol could end up increasing the amount of competition between different projects due to the need for them to maintain and grow the value of their own token so they can sustain themselves. This could come at the cost of reduced collaboration across the ecosystem if projects are not effectively identifying shared problems and collaborating on potential solutions. Protocol token funding could be effective in some use cases however it is preferable to avoid the usage of a token if the protocol development can be funded in another way sustainably. Network funding should be highly effective for funding protocol development if the network is able to generate enough income over the long term to pay for these efforts.
## **Application layer**
The application layer focuses on end user solutions, such as web or mobile applications. Applications can integrate network and protocol functionality or any libraries that are available to make solutions that can be used directly by community members. Example applications could be social or finance applications or online games.
**Complexities**
* **Long term token use cases** - Adding a separate token to fundraise for an application might be problematic unless there is long term utility in the token. Some examples of where a token could make sense could be for loyalty or reward points in an e-commerce platform or in-game currencies in an online game. In other situations the application may benefit from simply charging a fee with the network coin itself rather than making another token. Application development could be funded by community investment using the network's own coin or be funded by the network itself.
* **Open source vs closed source** - Applications could go down a closed source route where they charge some form of fee to use their application and then want to protect their code from being copied and deployed for free. Another approach could be that application development is supported by network funding and the code is open source from the start and the community can freely deploy and edit this application as they want to. Both open source applications and closed source applications could be sustainable over the long term however closed source would have increased competition in this environment as the open source solutions would be free and openly available to use. Closed source applications would need to provide a better or more tailored experience for end users to justify any one-off or ongoing cost to use that application.
* **Preventing misuse and theft** - An ongoing risk for end users with applications is if those applications mislead the user into performing an action that results in a loss of funds. If the application is closed source then there is an increased reliance that the wallets and transaction signing interfaces that people are using can help with identifying applications that are attempting to do something malicious. These problems can be more easily checked and verified if the codebase was open source.
**Token funding vs network funding**
Some applications could benefit from the usage of a token over the long term. Other applications may be more suitable for generating income through fees to use the application. Network funding could be another approach that is effective for developing many open source applications that can then be modified and used by anyone freely. There are many different ways that an application developer could combine and compose the available protocols and network functionality together into a new user experience. This variety of ways that an application could be built for both general or niche use cases can increase the opportunity that a multitude of sustainable funding approaches could exist in parallel over the long term. Open source applications are still a highly desirable outcome so that the code can be checked and verified.
## **Open source software libraries**
Open source software libraries could be beneficial for any of the network, protocol or application layers. Libraries could help with math, cryptography, data processing and formatting, compression, data storage, transaction building, scalability or many other areas. Some of these libraries could be used across one or all of the network, protocol and application layers.
Software libraries such as these do not necessarily need to have a business model to be sustainably funded. Network funding could play an important role in ensuring these types of initiatives are supported over the long term.
**Token funding vs network funding**
Ecosystems without much network funding available could become more reliant on projects building on top of the ecosystem to lead and support the development of open source libraries. The main issue with this approach is that the projects would only have partially aligned incentives to support these open source initiatives. If they support these initiatives more than other projects in the ecosystem they could be putting themselves into a weaker financial position than the competition. Projects are incentivised to succeed, this incentive can conflict with using their capital to support initiatives that aren’t fully aligned with increasing their own chances of success. Network funding does not face this partially aligned incentive problem as any funding that comes from the network can be directed towards any high impact open source initiative that improves the ecosystem. Network funding creates fully aligned incentives to repeatedly identify and support the most impactful open source initiatives.
## **Key takeaways**
* **Network funding is at its highest importance for maintaining and improving the network itself** - The most reliable way to sustainably fund the contribution efforts needed to maintain and improve the network will likely be from network fees and taxes. It is of the highest importance that any code developed to maintain and improve the network itself is open source so it can be verified and audited by the wider community.
* **Network funding is highly preferable for protocol development** - Similar to Web2 protocols there is a massive benefit for the community when protocols are developed as a public good that is for the benefit of the ecosystem. Some protocols may require a token to function more effectively however when in doubt it is more beneficial for the protocol to remain open source and be owned by the community. Protocols that are responsible for a growing amount of ecosystem assets can benefit from having a similar amount of verification and auditing checks that any network changes would have.
* **Network funding could be the most effective for application development** - Applications could create revenue models in a number of ways and some applications may benefit from the usage of a token over the long term. However Network funding is still a highly promising approach that could prove to be one of the most effective due to the fact it creates more fully aligned incentives to develop what is best for the wider ecosystem. Network funding helps to fund projects that can be open source from the start. More experimentation will be needed to find out which funding approaches are the most effective for different types of applications.
# Contribution approaches
Comparing the different contribution approaches that could be used for making submissions for knowledge, priorities, ideas and contributor information
Contribution towards the funding process concerns any suggestions contributors can make towards what knowledge, priorities, ideas and contributors could be promising or important for the community to consider. How information is submitted, stored and connected across the funding process can have a significant impact on how the funding process functions and scales.
1. **Submit Knowledge** - Contributors could share informational resources that could be useful for the ecosystem to consider. Some contributors may also submit their own research and analysis to help better inform the community on what is happening both inside and outside the ecosystem.
2. **Submit Priorities** - Contributors can contribute to ecosystem prioritisation by suggesting what the most important problems or opportunities are in the ecosystem that might be worth considering.
3. **Submit Ideas** - Contributors could suggest ideas which detail how a certain initiative could be executed and the potential value that initiative could generate for the ecosystem.
4. **Submit Contributor Information** - Contributors might want to help with the execution of ideas and start building a reputation in the ecosystem by submitting their personal and professional information and any contribution history for the community to then consider.
## Approaches for handling knowledge, priority, idea and contributor information submissions
The following are some example approaches that cover how submissions could be handled to enable contributors to make suggestions within a funding process:
* [**Fully combined submissions**](/approaches/contribution-approaches/fully-combined-submission) - Suggestions cover information about any relevant knowledge, priorities, idea and contributors in a single submission.
* [**Idea & contributor combined submissions**](/approaches/contribution-approaches/idea-and-contributor-combined-submissions) - Suggestions separate knowledge and priorities and then ideas and contributors into two separate submission processes.
* [**Independent submissions**](/approaches/contribution-approaches/independent-submissions) - Suggestions for knowledge, priorities, ideas and contributors each have their own separate submission process.
To compare these decision approaches a number of [factors have been considered](/approaches/contribution-approaches/contribution-factors-for-consideration) and then applied to each approach to try and determine any strengths and weaknesses of each one.
There are further ways you could group together the submission of knowledge, priority, idea and contributor information. However the above comparison helps to highlight that the most expressive, lowest complexity and lowest time required approach to participate in funding is best achieved by keeping the submission for these processes independent from one another.
**Contribution approaches analysis**
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[Contribution factors for consideration](/approaches/contribution-approaches/contribution-factors-for-consideration)
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{% content-ref url="/pages/IB9l7e6qPplzS1mz3QEb" %}
[Fully combined submission](/approaches/contribution-approaches/fully-combined-submission)
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[Idea & contributor combined submissions](/approaches/contribution-approaches/idea-and-contributor-combined-submissions)
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[Independent submissions](/approaches/contribution-approaches/independent-submissions)
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## Further advantages for an independent submissions approach
There are a number of further advantages for handling funding submissions separately that can be highlighted.
**Better data structure for increasing usability, composability, reusability & maintainability**
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[Funding process data handling](/approaches/contribution-approaches/disbursement-process-data-handling)
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**High flexibility to experiment with funding decision approaches**
Keeping these submission processes separate means the funding process can compose this information into proposals for decisions in any way the community prefers. When information is initially submitted into the funding process it does not require a community decision. The composition of information to create a decision can happen at any point with a combination of the information that has been previously submitted. The benefits of being able to compose these decisions out of independent submissions is the community is able to change their mind on what decision approach they want to adopt. Alternatively they could also adopt multiple approaches to experiment with different approaches for different use cases.
**Opportunity to increase collaboration & feedback**
Allowing people to submit suggestions for any of the relevant funding areas independently and separately from decision making allows a community to have the maximum opportunity to engage and respond to the information that is submitted. Establishing community sentiment, feedback and team forming could all occur due to the submission of new information such as new ideas or contributors who are interested in getting involved in the ecosystem. The faster an ecosystem is able to view and respond to this information the faster that any collaboration and feedback can occur. Higher collaboration can lead to discovery of new approaches to solving important problems, better knowledge curation and a higher depth of information being shared which could help improve future funding decisions.
**Enabling contributor specialisation**
By giving contributors the full ability to submit suggestions in a way that they might want to, there is increased ability for contributors to specialise on the areas that they are most experienced or interested in. For instance by having an independent submission process for priorities a contributor who wants to specialise in understanding the knowledge available in an ecosystem and then translating that into important priorities could do so. Alternatively another contributor could just be a skilled software developer that wants to contribute to the ecosystem. That contributor might not have any ideas that they want to suggest to the ecosystem at the moment but they do want to join the existing efforts. This contributor could achieve that by submitting their contributor information with the indication that they are interested in working in the ecosystem. By keeping that process independent the community now can easily and more quickly respond and invite that person to collaborate with them on existing ideas if it made sense to do so. Keeping the funding process submissions independent helps to enable contributors to participate in the exact way they want to.
**Opportunity to increase information flow & response speed**
Keeping the submission of suggestions for knowledge, priorities, ideas and contributors separate allows contributors to submit this information more immediately than having to gather and collect multiple pieces of information about other processes if they were combined. This potential increase in the speed of information flow can help make the ecosystem more responsive to important and useful information. For knowledge submissions, this could mean some new insight or piece of data becomes available that completely changes the understanding of the current environment and what is and isn’t important for the ecosystem. For priorities this could mean the identification of a sudden critical issue that might have just emerged and it’s vital that this information propagates across the ecosystem and is resolved as fast as possible. For ideas this could mean getting feedback and starting team formation on promising ideas as soon as they are conceived as an idea rather than having to wait for a decision process or having to be more fully formed at the point of submission. For contributors this can mean being able to immediately indicate their willingness and capability to contribute to the ecosystem so that other community members can immediately see this and respond to that contributor.
**Opportunity for contributors to immediately start building reputation**
Contributors would be able to participate with more specific submissions that they believe add value to the ecosystem, this can help them with building a reputation in the ecosystem. If contributors were able to submit their personal information as a potential contributor they could also be enabled to submit contribution logs to showcase how they’ve been participating and working in the ecosystem. This allows them to build up evidence of why they are useful and impactful for the ecosystem. The community benefits from this as they can then consider that contributor as a potential candidate to receive compensation from the treasury in future funding decisions if they have evidence of their ongoing impact.
# Contribution factors for consideration
Listing the different contribution factors that will be considered for each funding contribution approach
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Contributor participation time required**
* **Description** - How long does it take for a contributor to make suggestions and participate in the funding process when suggesting knowledge, priorities, ideas or themselves as a contributor.
* **Maximum score** - 5, Very important. The longer it takes for someone to try and participate in the funding process and contribute to an ecosystem the less likely it is for someone to participate. This becomes even more likely if that initial contribution effort is not compensated.
* **Scoring questions** - How long does it take for a contributor to make contributions to the priority, idea or contributor processes involved in funding? Do they need to spend extra time on other less relevant areas for them to participate?
* **Scoring** - Low time required is good (Score - 5. High time required is bad (Score - 1).
**Contribution complexity**
* **Description** - A funding process wants to avoid being too complex for someone to make useful contributions. Contributions could be creating or helping with emerging priorities or ideas or instead helping with the execution of ideas.
* **Maximum score** - 5, Very important. The higher the complexity is for people to contribute to a funding process the harder it becomes for people to make potentially impactful contributions.
* **Scoring questions** - How easy is it for someone to suggest priorities, ideas or execution approaches? What amount of information and context is required for someone to contribute to any of the funding areas?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Contribution expressiveness**
* **Description** - Contribution expressiveness means people should be able to contribute the full range of potential suggestions that correspond to the type of value and involvement they want to provide. Contributors could express themselves and create impact in an ecosystem in many ways, the funding process can either help to enable or prevent some or all of these different types of contribution.
* **Maximum score** - 5, Very important. Every contributor can have a different set of preferences and capabilities in how they would like to help support an ecosystem. Adopting an expressive approach to contribution will allow them to contribute in the exact way they want to. This maximises the chance that contributors will get involved as they aren’t being forced to make contributions to areas they aren’t interested in doing.
* **Scoring questions** - How do contributors suggest priorities, ideas or execution approaches? What flexibility does the approach give people for contributing in multiple ways that could be beneficial to an ecosystem?
* **Scoring** - Higher expressiveness is good (Score - 5). Lower expressiveness is bad (Score - 1).
# Fully combined submission
Fully combined submission for suggesting knowledge, priorities, ideas and contributors
**Overview**
A fully combined submission means that a contributor suggestion for the funding process will include any relevant knowledge, priority, idea and contributor information in the same submission.
**Very high contributor participation time required (Score - 1)**
For contributors to participate they have to spend the largest possible amount of time to create a suggestion. They will need to gather and submit relevant information that covers knowledge, priorities, idea information and contributors that could execute the idea in a single suggestion. The contributor would need to spend time doing all of the background research and analysis to understand the potential priorities that exist, suggest the most important priorities in their submission, think and decide on a suitable idea, and then finally find a team of other suitable contributors to work on this initiative. The time this would take would be very high, making it very difficult for many contributors to practically participate if this approach was adopted.
**Very high contribution complexity (Score - 1)**
Each funding process requires a mixture of different knowledge and skills. Combining these funding processes into a single submissions results in the contributor having to have a lot of knowledge about what is happening in the ecosystem and what problems and opportunities exist, they need to then have the skill to effectively to compare and understand which potential priorities might be the most important, then turn that priority into a suggested idea and finally articulate how it would be executed along with identifying any other community members that would be suitable and keen to support the execution of that idea. The approach could easily require research, analytical, marketing and recruitment skills in the same submission as well as some relevant domain expertise in the idea actually being suggested. Due to this combination of different factors this contribution approach is highly complex.
**Very low contribution expressiveness (Score - 1)**
If a contributor just wanted to suggest a piece of knowledge as relevant to an ecosystem or suggest that a new priority might be more important than the existing ones they would not be able to do so using a combined submission approach. Instead they would need to submit an entire proposal that covers every part of the process. This is the least expressive the system could be for enabling these different forms of contribution.
**Total score = 3 / 15**
# Idea & contributor combined submissions
Idea & contributor combined submission for suggesting ideas and contributors along with a combined submission for knowledge and priorities
**Overview**
The idea and contributor combined submission approach separates the funding processes into a knowledge and priority submission and an idea and contributor submission. The submissions should be able to reference the submission data from other processes, for instance an idea and contributor combined submission should optionally be able to reference an existing knowledge and priority combined submission.
**Moderate contributor participation time required (Score - 3)**
Contributors are able to select which area of funding they want to contribute towards with more flexibility using a separated approach. Now contributors would only need to spend time submitting knowledge and priorities to make a submission or alternatively could look at suggesting ideas along with the contributors that could help with executing those ideas.
**Moderate contribution complexity (Score - 3)**
Not every piece of knowledge needs to be submitted with a priority and vice versa just like an idea doesn’t need to have contributors ready to execute it for it to start receiving feedback. Requiring this combined information in both these two submissions approaches increases the complexity for contributors to bring together the required information for them to participate instead of letting them contribute with only the relevant information that they wanted to provide.
**Moderate contribution expressiveness (Score - 3)**
Contributors can more easily suggest multiple different ideas to address the numerous priorities that could exist, however they are still limited in that they would need to define the contributors that would be working on those ideas.
**Total score = 9 / 15**
# Independent submissions
Independent submissions for suggesting knowledge, priorities, ideas and contributors
**Overview**
Independent submissions means that submitting suggestions for knowledge, priorities, ideas and contributor information are handled as independent submission processes. Submissions can happen independently and would not rely on other funding process submissions. The submissions should also be able to reference the submission data from other processes, for instance ideas should optionally be able to reference any existing priorities that have been submitted.
**Very low contributor participation time required (Score - 5)**
Contributors could create submissions in one or all of the funding processes whether that’s suggesting priorities or ideas or suggesting that they could be a potential contributor to help with execution. If a contributor only wanted to submit their own contributor information then they would be able to do so which reduces the time required to participate as they wouldn’t have to spend time on other processes in funding if they didn’t have anything valuable to suggest at that stage.
**Very low contribution complexity (Score - 5)**
The contributor who is submitting any suggestions for knowledge, priorities, ideas or their own contributor information only needs to understand the data and format required for that specific submission they are making. This reduces complexity to the minimum as contributions only need to understand and bring together the information required for that submission rather than multiple processes in a single submission.
**Very high contribution expressiveness (Score - 5)**
Contributors can make submissions in the exact processes they want to and do not need to spend time on areas they have less expertise in or that they aren’t interested in. One contributor could decide to spend all their time applying knowledge to create and improve priorities and then spend no time on suggesting ideas or finding contributors to execute those ideas. Contributors would be able to highly express their preferences on how they want to participate in supporting the funding process.
**Total score = 15 / 15**
# Funding process data handling
Considerations about the data structures used for handling funding process data
Knowledge, priorities, ideas and execution cover the four key processes involved in funding. Contributors handle the step of execution. There is a many to many relationship between knowledge and priorities, priorities and ideas and ideas and contributors:
* Knowledge & priorities - Many pieces of knowledge can be relevant to the importance of many different priorities.
* Priorities & ideas - Many different priorities can have many different ideas that could help with addressing each of those priorities.
* Ideas & contributors - Many different ideas can have many different contributors that are helping to execute those ideas.
Many to many relationships between knowledge, priorities, ideas and contributors
In relational databases, data normalisation is a process in database design that helps with organising data to minimise redundancy and dependency. The principles behind data normalisation are relevant for how a funding process can handle and process its data due to the amount of duplicated data that can emerge because of the numerous many to many relationships. A funding process could need to handle an ever increasing amount of data being stored and used across the different systems and processes involved in funding.
### Importance of separate but interlinked data structures
Storing the funding processes data separately whilst also allowing this data to reference data from the other processes is one way that a funding system can increase its usability, scalability, maintainability and composability.
**Usability**
If data from each process is handled separately but can be interlinked with each other it will make it easier for voters in the funding process to review one piece of data such as an idea and then see all of the related and linked priorities that this idea could help with and also what contributors are involved in executing that idea. A key outcome that the end user benefits is being able to more easily see and traverse through the data to more easily understand what other ideas are tackling those same priorities and what other ideas those same contributors might be working on. All of this information is highly beneficial for the voter when making more informed decisions during funding. If this data was all bundled into the same data structure the issue of duplication could make it far more difficult for a user to find all of the related information about a priority, idea or contributor. Another benefit of having the data for these processes stored and verified separately is that contributors would be able to more easily submit information about any of the processes immediately. For instance a contributor might submit information about themselves so everyone else in the ecosystem can immediately see what skills and background they have and how they’re interested in supporting the ecosystem. This can help speed up the matchmaking between new contributors and emerging project teams. Another contributor could submit a priority the moment they believe it could be of high importance. This separation of concerns in the data structure allows the contributors to more easily submit the relevant information for each funding process. The community can then more immediately consider and respond to this information.
**Scalability**
Ensuring that data can be referenced and used in other processes can help with reducing the amount of duplicated data being stored. Achieving this can help decrease the storage cost of maintaining the funding process as it scales. If the data is not interlinked in any way it could also become more difficult to find the relevant surrounding data, such as which ideas share the same priority. If priorities were stored as copies and not written or maintained in the same way then identifying where there is overlap becomes increasingly difficult. If the principles of data normalisation are considered and integrated into a funding processes data structure another concern that could emerge is whether the read performance of that data is scalable. If faster read performance is required then the data layer could be treated as a source of truth and solutions could be built on top of that data layer to cache this data and potentially denormalise it for those specific use cases that require a faster read performance.
**Maintainability**
If data is not consistent across the funding process there is a higher risk that the system becomes harder to maintain as it tries to scale. For instance if priority and idea data was stored in a single structure the amount of duplicated priorities could easily increase over time. If there was new information relevant to that priority that meant updating the existing information then that could require updating every idea that has some form of variation of that priority. If this priority is normalised and managed in one place then this information could have been shared across many ideas and updated by itself. Due to the variation in how people document and update their own priority and idea submissions it could be difficult to even try and automate this process. Even if the process was automated in some capacity it would still be far more costly than maintaining a single priority separately that each idea can then reference. The faster and easier it is for the funding process to maintain and update important information the quicker a community can become at responding to that information.
**Composability**
How data is stored and linked with other data influences how easily it can be used. If data is stored independently it can still be combined to create a new data set such as a decision proposal. A proposal could combine information about priorities, ideas and contributors and then be put to the voters for a decision if this was required. Alternatively that same data could also be used in completely separate proposals. Maintaining this data in independent structures whilst allowing each process to easily reference data from other processes can help with making it easier for proposals to be created that bring together any of this relevant information from different sources. For example, there could be a range of different priorities and contributors that already exist in the ecosystem. A new idea being submitted could then reference the relevant priorities and contributors that are relevant to this new idea. Only the new idea information is needed and can be stored in the funding system independently from the other priorities and contributors. Those same priorities and contributors being referenced in one idea can then also be referenced in any other future idea that gets submitted in the future.
# Decision approaches
Comparing the different decision approaches that could be used for selecting priorities, ideas and contributors
A high level overview of the key decisions that are made during funding are that voters are tasked with digesting any self selecting any relevant knowledge about an ecosystem before they then move onto selecting the most important priorities, ideas and contributors that could help with generating impactful outcomes for the ecosystem.
1. **Knowledge Selection** - Available knowledge within an ecosystem will play an important part in all of the selection processes involved in funding. Both automated systems and one off pieces of research or analysis can help with creating useful sources of information for voters. Voters having more access to quality knowledge sources will help ensure that they are more well informed when making any funding decisions.
2. **Priority Selection** - Priorities help to highlight the most important problems and opportunities that exist in an ecosystem. Voters will apply their own understanding of the ecosystem and available knowledge to determine which priorities are the most important for the ecosystem at that moment in time. The selection of priorities can often influence which ideas and contributors get selected as the most promising and suitable for addressing those priorities.
3. **Idea Selection** - Ideas help to articulate a solution which could be executed that would help with addressing one or multiple priorities. Voters could participate in selecting the most promising ideas that can help with addressing the existing priorities in an ecosystem.
4. **Contributor Selection** - Contributors offer their time and skills to help with the execution of ideas. Voters could help with selecting the contributors that should be compensated and responsible for the execution of the most promising ideas.
How different decisions are handled and composed together will greatly influence the flexibility, scalability and complexity of funding process decision making.
## Approaches for handling priority, idea and contributor decisions
The selection of knowledge is often a personal choice where the voter will self determine what pieces of information they believe are most important, this is naturally influenced by their expertise and background. An open and community wide decision process could be used to select knowledge, this is something worth considering in the future. For this initial decision comparison we will just focus on the selection of priorities, ideas and contributors.
A number of decision approaches could be used to select which priorities, ideas and contributors are the most important or promising. A selection of these approaches include:
* [**Fully combined decision**](/approaches/decision-approaches/fully-combined-decision) - The selection of priorities, ideas and contributors all happens in the same selection process.
* [**Idea & contributor combined decision**](/approaches/decision-approaches/idea-and-contributor-combined-decision) - The selection of priorities happens independently and then the selection of ideas and contributors happens in the same process.
* [**Independent decisions**](/approaches/decision-approaches/independent-decisions) - The selection of priorities, ideas and contributors happen all in separate processes. Voters are encouraged to participate in all of the decisions.
* [**Passive idea selection**](/approaches/decision-approaches/passive-idea-selection) - The selection of priorities, ideas and contributors happen as separate decisions. Voters are encouraged to participate in idea selection in the areas they are interested in participating.
* [**Delegated idea selection**](/approaches/decision-approaches/delegated-idea-selection) - The selection of priorities, ideas and contributors happen as separate decisions. Voters are encouraged to participate in sharing their preferences of which ideas are most promising in a community vote, however the responsibility of actually selecting which ideas will be executed is delegated to the contributors that the voters have selected.
To compare these decision approaches a number of [factors have been considered](/approaches/decision-approaches/factors-for-consideration) and then applied to each approach to try and determine any strengths and weaknesses of each one.
The most expressive, flexible and least complex of the decision approaches outlined above were those that adopted independent processes for decision making to select the most important priorities, ideas and contributors.
The differences between passive idea selection and delegated idea selection have been explored in more detail here:
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[Contributor vs voter idea selection](/approaches/decision-approaches/contributor-vs-voter-idea-selection)
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**Decision approaches analysis**
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[Decision factors for consideration](/approaches/decision-approaches/factors-for-consideration)
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[Fully combined decision](/approaches/decision-approaches/fully-combined-decision)
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[Idea & contributor combined decision](/approaches/decision-approaches/idea-and-contributor-combined-decision)
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[Independent decisions](/approaches/decision-approaches/independent-decisions)
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[Passive idea selection](/approaches/decision-approaches/passive-idea-selection)
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[Delegated idea selection](/approaches/decision-approaches/delegated-idea-selection)
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## Considerations for handling knowledge
At the point of making any funding decision the voters involved will have some pre-existing knowledge based on their own experiences and skill sets as well as having access to any publicly available knowledge about the ecosystem, other ecosystems and relevant topic areas.
Voters will decide how much time they want to spend on identifying new knowledge that could help them with making more informed funding decisions. Voters may decide not to digest new information for a number of reasons. One could be because they don't trust the source of the new information. Another reason could be that they believe they already have enough knowledge to make informed decisions. Another reason could be they simply don't have enough time available to go through the knowledge sources.
A funding process will benefit from making it easy to access knowledge that is relevant and accurate so that voters are able to make more well informed funding decisions. Some example areas that could help voters are if they could easily find out what has been funded historically, what priorities or ideas have been completed and which ideas or contributors have been historically the most effective at generating impact for the ecosystem.
For more complex funding processes there could be value in exploring how a knowledge selection process could be introduced before voters select priorities, ideas and contributors. Voters may benefit from being able to share and vote on the relevance and accuracy of different sources of knowledge to help with the process of making the community more well informed for upcoming decisions. The most important pieces of knowledge could then become more well known across an ecosystem due to this collective effort to identify quality information sources.
## Prioritising certain funding outcomes
A key question to ask when adopting any of these different funding decision approaches is what types of outcomes are most important? What outcomes should the treasury funding process be optimising for? There could be many different outcomes that are important to each ecosystem, each of which those ecosystems may then want to quantify and optimise over time. The following are simply examples, and not even necessarily good ones! Many other potential outcomes can exist that could be optimised for.
**Maximising decision involvement**
One potentially desirable outcome for an ecosystem could be that a treasury system maximises the involvement of voters in every funding decision. Achieving this outcome would mean the entire community will need to be able to vote on any part of the funding process and the systems and processes should help with actively encouraging voters to get involved in all available decisions. The independent processes approach could be one suitable way to achieve this type of outcome as voters would be encouraged to vote on everything and voters would also be able to vote on exactly what they want in each process without any compromise on their preferences. The reasons this property might not be desirable are that it might not be practical to try and expect or encourage voters to participate in every decision in the funding process. The larger the ecosystem is the harder this would be to achieve. This higher complexity at scale is a reason why approaches such as passive or delegated idea selection can be considered as alternatives.
**Maximising participation scalability**
Maximising the amount of participation in the funding process would mean making it easier and faster for voters to participate in the funding process. The easier and quicker it is for voters to participate in the funding process the more easy it will be for the funding process to scale the amount of participation to a larger audience. Optimising for this outcome will mean reducing the total time required and overall decision complexity as much as possible to achieve a higher amount of participation across a larger community. If this was the primary concern for a treasury system then considering the delegated idea selection approach could potentially be a suitable option. This reduces some of the required involvement from the voter and leans towards increasing the simplicity and speed of the funding decisions.
**Maximising both participation scalability and decision involvement**
Trying to get all community members to decide on every decision can be a difficult outcome when trying to scale the amount of participation to a larger audience. Time consuming funding decisions can easily lead to voter apathy and disengagement, a problem that can increase as an ecosystem tries to scale. One way an ecosystem could achieve a balance in achieving both these outcomes could be by adopting a passive idea selection process. Under this approach all voters could still participate in the different funding decisions however at a system and process level it is the priorities and contributor selection that are encouraged as the main decisions that should be made by the community. This then leaves the idea selection as optional, helping to reduce the complexity and time taken to participate which helps with increasing participation scalability whilst also allowing for full decision involvement.
# Decision factors for consideration
Listing the different decision factors that will be considered for each funding decision approach
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Voter participation time required**
* **Description** - Voter participation time required concerns how much time the voter must spend to participate in the voting process.
* **Maximum score** - 5, Very important. It will be vital for funding processes to minimise the required time it takes for voters to participate so that the maximum number of voters can feasibly participate that are willing and capable of doing so. The higher the amount of time that is required to participate in voting the higher the likelihood of increasing voter apathy and disengagement.
* **Scoring questions** - How much context and information is required for someone to be well informed in the process? How much time would need to be committed to participate? How long might it take to make a decision? Can the voter participate in only the decisions they’re interested in or capable of helping with or must they be involved in every part of the process covering priorities, ideas and contributors?
* **Scoring** - Lower required time is good (Score - 5). Higher required time is bad (Score - 1).
**Voter decision complexity**
* **Description** - Determining how complex it is for a voter to make decisions when selecting their preferred priorities, ideas and contributors.
* **Maximum score** - 5, Very important. The more complex the decision process is the easier it becomes for voters to make suboptimal decisions. It also becomes more likely that voters disengage with the process or simply delegate the decision to someone else.
* **Scoring questions** - How complex is it for a voter to make an informed decision when they want to properly participate in one of the funding process votes? How fast can voters make an informed decision?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Voter expressiveness**
* **Description** - An expressive voting system means that voters are able to express their opinions and preferences through their voting decisions.
* **Importance score** - 5, Very important. To properly understand what the current sentiment and preferences are of a community it is important that voters are able to express what their exact preferences are when voting and sharing their opinions.
* **Scoring questions** - Can a voter specify exactly what their preferences are given a set of different decisions or are they limited in only being able to respond to what has been presented to them instead of their actual preferences? How much potential information is lost with the approach being taken?
* **Scoring** - Higher expressiveness is good (Score - 5). Lower expressiveness is bad (Score - 1).]
**Funding outcome influence**
* **Description** - Decisions made by voters are at their highest influence when it creates a fixed and exact outcome, one example could be a system parameter change. Alternatively voting outcomes might not produce fixed and exact outcomes and instead create influenced outcomes. For instance voters could prefer and vote on a high level idea but not have influence on how that idea is exactly executed and what is involved during execution.
* **Maximum score** - 4, Fairly important. In many cases such as where the majority of incentives get allocated the voters will want to have a higher and more exact influence on where assets are disbursed. In other situations such as exactly what idea gets executed or how an idea is approached the importance of that influence might not be as important if there are more effective, scalable and efficient ways to handle those outcomes to generate the right outcomes.
* **Scoring questions** - What influence does the voter have for each of the decisions in the suggested funding approach? Is any reduction in voter influence justified due to a potential approach?
* **Scoring** - Higher influence is good (Score - 5). Lower influence is bad (Score - 1).
**Voter decision change complexity**
* **Description -** Voters sometimes change their mind on what is most important or promising based on new information or a changing environment. What complexities might emerge for an ecosystem that wants to change the priorities, ideas and contributors involved in the future due to the decision approach being taken?
* **Maximum score** - 5, Very important. The more complex it is for an ecosystem to make changes to the existing priorities, ideas and contributors involved the slower that the funding process can become in adapting to important changes in its environment. This slower ability to manoeuvre and change can then lead to stagnation and slower adaptability.
* **Scoring questions** - How easily can an ecosystem change their decisions in the future as new knowledge emerges which can influence which priorities, ideas and contributors are the most promising and suitable at that moment in time? How easily can contributors change their execution approach to react to a fast changing environment?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
# Fully combined decision
Fully combined decision for selecting priorities, ideas and contributors
**Overview**
A fully combined decision is where voters will select the priorities, ideas and contributors in a single process. This means proposals in this type of process will contain one or multiple priorities, ideas and contributors that voters will then decide between.
**Very high voter participation time required (Score - 1)**
For voters to participate they need to read, understand and compare all of the proposals with the priorities, ideas and contributors that are suggested. Voters must participate in the entire funding process with the entire decision making in a single vote. Voters are unable to partially participate in some of the funding process separately.
**High voter decision complexity (Score - 2)**
The voter must digest and understand the priorities, ideas and contributors being suggested to them before making any decision. Voters must analyse the tradeoffs between each combination of priorities, ideas and contributors. This greatly increases the decision complexity as a voter may want to endorse certain priorities or ideas but not the contributors who are attached to that proposal and vice versa where they fully support the contributors involved but not the ideas or priorities they are suggesting.
**Very low voter expressiveness (Score - 1)**
If a voter wanted to select any specific priorities, ideas or contributors they would be unable to do so at the voting stage unless the exact combination of priorities, ideas and contributors was already submitted as a voting option. The voter can only choose between what the contributors submit as their own preferred combination.
**Very high funding outcome influence (Score - 5, Multiply by importance of 4/5 or 0.8, Final Score - 4)**
The voters decision will influence exactly how contribution efforts are being directed through the selected proposals that define the priorities, ideas and contributors involved.
**Very high voter decision change complexity (Score - 1)**
To make future changes to previous decisions an entire new proposal would be needed to suggest any changes to the priorities, ideas or contributors in a similar proposal based on the exact change that were needed. Alternatively the ecosystem would need to introduce a separate change process to make changes to these different areas. The obvious issue with this however is it then adds in even more processes and complexity to the funding process. If the processes were independent then voters would be able to reuse the same systems they used for the initial vote to make changes
**Total score = 9 / 24**
# Idea & contributor combined decision
Idea & contributor combined decision for selecting ideas and contributors
**Overview**
An idea and contributor combined decision means that selection of ideas and contributors are combined into the same decision. Contributors would submit an idea along with who is contributing to that idea at the same time, voters would then decide between these ideas. The priority selection process would happen separately.
**High voter participation time required (Score - 2)**
Voters are able to participate in the priority selection decision and ideas and contribution selection decision separately. This means they could decide to participate in just one of those votes instead of both. This reduces the amount of context and information required to participate in the funding process as they can decide where and how they participate. Some voters may only want to participate in voting on the priority setting process which would mean they don’t need to review all of the ideas and contributor combined proposals.
**High voter decision complexity (Score - 2)**
The number of potential ideas can often have the largest variety of options for voters to choose from. When combining this with the contributor selection the voter complexity is increased as voters now must both understand and compare the tradeoffs with each combination of ideas and contributors with all of the others. This is instead of the more simple separate decision of which ideas are the most promising and then separately which contributors are the most suited.
**Moderate voter expressiveness (Score - 3)**
Voters would be able to select the exact priorities that they believe are the most important for the ecosystem. Voters would need to pick from the idea and contributor combinations presented to them meaning they would not be able to easily influence which ideas and contributors are selected individually. As the number of ideas and contributors would represent the larger part of the decision complexity this can limit the flexibility and options available to voters. Community members who wanted to contribute ideas but not execute them, and contributors who wanted to execute ideas but didn’t have an existing idea, would both currently have a higher difficulty in participating with this approach. This complexity could then result in further limiting the voters choices as some of these potential ideas and contributors might not get submitted for consideration.
**Very high funding outcome influence (Score - 5, Multiply by importance of 4/5 or 0.8, Final Score - 4)**
The voter's decision will influence exactly what priorities are preferred and exactly how contribution efforts are being directed through the selection of proposals that define the idea and contributors involved.
**Moderate voter decision change complexity (Score - 3)**
Voters can reuse the same system and process to vote on any of the priorities set and then vote again in the future to change those priorities using the same process. For updating which are the most promising ideas or contributors an ecosystem could reuse the same process and just update the idea or contributors as needed but this then adds bloat to the process due to the repeated information. Alternatively the ecosystem could introduce independent processes for updating the ideas or contributors however this then adds in more complexity by increasing the total amount of processes being used in the ecosystem to manage potential future changes.
**Total score = 14 / 24**
# Independent decisions
Independent decisions for selecting priorities, ideas and contributors
**Overview**
Independent decisions means that the selection of priorities, ideas and contributors all happen in separate processes. These independent decisions could happen periodically one after another or they could all be ongoing continuous processes.
**Moderate voter participation time required (Score - 3)**
Voters could participate in one or all of the funding decisions around selecting priorities, ideas and contributors. This approach gives the voter the full freedom to participate in whichever decisions they want to for the funding process. The reason this approach still has moderate complexity is due to the amount of time it would take for voters to understand and compare decisions across all of these processes. The idea selection process can easily be the most demanding in terms of time required to understand and analyse the ideas submitted. This high time requirement to compare ideas provides sufficient rationale why voters may potentially decide to disengage from the process as it scales in size due to the time it would take to cover and understand such a wider range of focus areas.
**Moderate voter decision complexity (Score - 3)**
Each voter can decide between the priorities, ideas and contributors individually. Voters only need to compare a limited amount of information for each separate decision rather than having to take into account all of these factors at once in different combinations. This approach helps remove the complexities that emerge from combining different processes together. The main complexity that remains is that voters will still need to actively look to understand and compare potentially complex ideas to properly participate in idea selection under this approach. This process can be time consuming and highly complex for people who may not have a matching skill set to fully understand the potential impact and feasibility of each of the ideas submitted.
**Very high voter expressiveness (Score - 5)**
Voters are able to select the exact priorities, ideas and contributors they prefer individually. Voters do not have to make any compromises when making decisions that match their opinions and preferences.
**Very high funding outcome influence (Score - 5, Multiply by importance of 4/5 or 0.8, Final Score - 4)**
The voters decision will influence exactly what priorities, ideas and contributors are preferred which will directly influence how contribution efforts are being directed through the selection of proposals in each process.
**Very low voter decision change complexity (Score - 5)**
Voters would be able to use the same decision processes with minimal modification for future decisions about making changes to which priorities, ideas or contributors are most important for the ecosystem. Contributors could make new suggestions for new priorities, ideas or contributors to help with executing those ideas at any point by operating these processes separately.
**Total score = 20 / 24**
# Passive idea selection
Independent decisions for selecting priorities, ideas and contributors, ideas are passively selected
**Overview**
This decision approach includes the same ability for voters to select priorities, ideas and contributors that the independent decision approach does. The main difference is that under this approach these is an acceptance that there is not a goal of continuously trying to increase voter participation in the idea selection process. Instead only priority and contributor selection is highly encouraged. Community members who have relevant skills or a particular interest in certain idea focus areas are left to participate in the idea process. The voters decision on which ideas are selected and executed is still authoritative with this approach, the voters decide on which ideas are executed.
**Low voter participation time required (Score - 4)**
Voters could participate in one or all of the different decisions involved with selecting priorities, ideas and contributors. This voter has the full freedom to participate in whichever decisions they want to for the funding process. The main areas that the ecosystem encourages is participation in priority selection and contributor selection which results in reducing the total average time required for voters to participate.
**Low voter decision complexity (Score - 4)**
Each voter can decide between the priorities, ideas and contributors individually. Voters are mainly just encouraged to try and vote on the priority and contributors being selected. This helps to reduce the overall decision complexity as if voters don’t feel the need to understand and compare every idea that gets suggested in the ecosystem they are more likely to just participate in areas they feel are either necessary to support or areas they are interested in or have expertise in that are relevant.
**Very high voter expressiveness (Score - 5)**
Voters are able to select the exact priorities, ideas and contributors they prefer individually. Voters do not have to make any compromises when making decisions that match their opinions and preferences.
**Very high funding outcome influence (Score - 5, Multiply by importance of 4/5 or 0.8, Final Score - 4)**
The voters decision will influence exactly what priorities, ideas and contributors are preferred which will directly influence how contribution efforts are being directed through the selection of proposals in each process. The only key difference in this approach is that voters are not actively encouraged or expected to vote on every idea, however as mentioned the outcome of any decision from voters is still authoritative on what ideas will actually be executed. This means this approach has a very high influence on the outcomes of funding.
**Very low voter decision change complexity (Score - 5)**
Voters would be able to use the same decision processes with minimal modification for future decisions about making changes to which priorities, ideas or contributors are most important for the ecosystem. Contributors could make new suggestions for new priorities, ideas or contributors to help with executing those ideas at any point by operating these processes separately.
**Total score = 22 / 24**
# Delegated idea selection
Independent decisions for selecting priorities, ideas and contributors, idea selection is delegated to contributors
**Overview**
Delegated idea selection is where the actual voting power for selecting the ideas that get executed is given to the contributors who are selected by the voters. This means that community members would not directly have authority over which ideas must be executed. Instead they would have authority on which contributors they think will be most effective at addressing ecosystem priorities and selecting and working on the most promising ideas. The idea selection process itself can still be fully open, transparent and invite participation and voting from all of the community members. Community votes on the most promising ideas would provide invaluable information to the selected contributors on which ones they might decide to spend more time on. However the actual decision on which ideas get executed is left with the contributors. The contributors have a direct incentive to pick the most promising and impactful ideas as this will increase the chance that they are selected again in the future to contribute to the ecosystem. The main difference with this approach to a passive idea selection process is the contributors are responsible for selecting the ideas that get executed instead of the voters.
**Very low voter participation time required (Score - 5)**
Voters could participate in either priority or contributor selection. The voters are only responsible for determining what priorities and contributors are preferred and selected. Voters may optionally participate in the idea selection process however they would not have any voting power and would just be expressing their opinions and preferences that the contributors working in the ecosystem can then respond to and consider.
**Very low voter decision complexity (Score - 5)**
Each voter decision on priorities and contributors can be done so individually meaning voters only need to compare a limited amount of things when making each decision. This complexity is even further reduced with this approach as the idea selection process is delegated to the contributors who are selected. The voters could optionally participate in the idea generation and selection process though this wouldn’t be required.
**Very high voter expressiveness (Score - 5)**
Voters are able to share their exact preferences on the priorities, ideas and contributors they prefer by voting on them individually. Voters do not have to make any compromises when deciding what proposals and suggestions match their opinions and preferences. This approach still has a very high expressiveness as idea selection can still be fully open to the community so they can indicate their preferences through a vote. The key difference is those preferences don’t result in the voter having full control over the outcomes of the funding process.
**High funding outcome influence (Score - 4, Multiply by importance of 4/5 or 0.8, Final Score - 3.2)**
The voters decision will influence exactly what priorities and contributors are preferred which highly influence how contribution efforts are being directed as contributors would be responsible for executing ideas that help with addressing those priorities. Voters would still also be able to vote on what their preferred ideas are for addressing those priorities, however the outcome of which ideas actually get executed will be left to the selected contributors to decide. If contributors ignore these suggestions completely without good reason they are likely to not be elected again in future rounds. This incentive structure results in voters still having a high influence in the funding outcome.
**Very low voter decision change complexity (Score - 5)**
Voters would be able to use the exact same decision processes for any future changes about which priorities and contributors are most important and suitable for the ecosystem. Voters indirectly have influence over the idea selection through the fact that if they change priorities the future ideas being selected should be targeted at addressing those priorities. Voters could also still indicate their changing preferences in the most promising ideas through a community voting process. Although that change in community preference can easily be recorded, the contributors are still who determine whether they will move their current contribution efforts to a new and emerging idea that is deemed more promising.
**Total score = 23.2 / 24**
# Contributor vs voter idea selection
Comparing the voter (passive idea selection) and contributor (delegated idea selection) decision approaches
The key difference between independent decisions and passive idea selection is that with passive idea selection it is accepted that all voters do not need to try and vote on all ideas. Instead voters are only encouraged to vote in areas they are more interested in or have expertise in. This more relaxed stance and expectation on voters expected involvement in idea selection becomes far more scalable for handling a growing number of voters by helping to more drastically reduce the time required and the expected complexity to compare and vote on ideas. This is because voters would only spend time on the ideas they want to spend time on due to their own interests or expertise rather than all of the available ideas.
The delegated idea selection approach focuses on the contributor being the group of individuals who are responsible for selecting which ideas they actually execute. The following comparison will look at comparing the more scalable voter selection approach (passive idea selection) with the contributor idea selection approach (delegated idea selection).
The analysis below helps to highlight the wide range of issues that exist when trying to scale voter idea selection. If good decision outcomes can be achieved with either approach the delegated idea selection approach is still highly preferred as it would be far more effective for reducing the total time required and amount of complexity for voters to participate. Pushing the responsibility of idea selection towards the voters needs to be fully justified due to the large cost of trying to scale the number of voters with a decision process that is highly time intensive and complex. This complexity is only increased when the voters don’t necessarily work full time in the area or have sufficient context to understand all of the nuances of each idea that is worth considering. Scaling an ecosystem to handle millions of voters is a significant ongoing challenge for Web3 ecosystems. Considerations are needed on how the time and complexity can be further reduced so that voters can more feasibly and willingly want to participate.
## Voter idea selection
**Advantages**
* **Exact outcome influence** - The voter has a direct influence over which ideas get executed meaning they can apply their experience and expertise in supporting the decision about which ideas are the most promising to get executed.
**Drawbacks**
* **Participation scalability limitations** - The larger and more complex an ecosystem becomes the harder it also becomes for voters to be well informed about the trade offs of different ideas across the many different focus areas and markets in the ecosystem. Even if the voter wants to participate in many different idea related decisions this might not be possible once the ecosystem reaches a certain size due to the complexity and diversity of the range of ideas involved.
* **Lack of experience & expertise** - If voters are responsible for selecting which ideas to execute there is a risk that the people who do vote don’t have the sufficient expertise and experience to fully understand the nuances and tradeoffs involved of executing one idea over another. There is a risk of making non optimal decisions if the vote is determined increasingly by voters with less expertise and experience due to these voters outnumbering the more informed contributors who are actually executing those ideas in the ecosystem.
* **Lack of accountability** - The voters selecting the ideas to execute won’t be responsible for executing the ideas themselves or the outcomes that idea generates if they are not publicly sharing that voting choice. Contributors are more accountable than voters for their selection of ideas to execute as if they don’t create any impact over the course of one or multiple ideas they might not get selected again in a future funding decision.
* **Slower responsiveness** - If ideas need to have a community wide level of support through community voting before they can be executed there is a higher risk that the responsiveness of the ecosystem reduces. This can mean slower responses to new promising ideas or suddenly changing priorities. If a new idea could be executed that helps to address a changing priority it would need to be approved by community voters.
* **Higher risks around support for novel research & innovation** - If the ideas being executed are decided by the majority there is a risk that novel ideas that are not as supported in the beginning fail to be executed. Novel areas of science or research that are less obvious or well known could lead to fundamental changes in the ecosystems understanding of certain areas or could help with identifying new discoveries or approaches to solve certain problems. The dynamic nature of exploring potentially impactful ideas could be more easily stifled if a large population is responsible for having to select which ideas will be executed or not.
**Factors that increase the practicality of voter idea selection**
* **Smaller ecosystem** - A smaller ecosystem will make it easier for voters to remain well informed on certain areas when making selection decisions.
* **Lower complexity ideas** - If the ideas being suggested are of lower complexity it will be easier for voters who don’t have the same expertise and experience in those areas to more effectively understand, compare and select the most promising ideas.
* **Voters having more accountability** - If votes were public or there was some form of reputation attached to voters choices this might help with increasing the amount of accountability for voters to spend enough time on becoming sufficiently well informed decisions when making a decision.
* **Compensating voters** - If the vote is compensated sufficiently there would be more incentive for voters to spend a larger amount of time to truly understand the nuances of the ideas and participate. This does mean that voters could choose to just game this approach so that they just receive the voting rewards so this isn’t an effective solution.
**Example scenario highlighting the issues with voter idea selection**
There aren’t any easy to find case studies of larger corporations using an approach where the employees across the company vote on the ideas that get executed across the company. There are numerous reasons this wouldn’t make sense, even within corporations where people are working full time at that same company. If an engineering team was working on a set of new potential features and the decision on which ideas will be executed was left to the whole company to decide the amount of governance complexity this introduces is profound. Now teams who work in completely different areas of the business such as in marketing, recruitment or legal could now vote on which ideas are executed. The engineering team would have a lot more context on what might make sense as they have all the engineering background and context of what is and isn’t feasible and practical, they also have deeper knowledge about any analytical history that they introduced and monitored and also have general experience from working with end users and across that particular area for a number of months or years. If everyone in the company was able to vote on this selection of ideas it would create the situation where other employees could have a greater influence on the ideas that get selected over the team itself whom has the most expertise and experience. This problem is then duplicated across the whole company where the engineering team would also be able to vote on the ideas selected for other areas of the business. The time costs of trying to become well informed in numerous areas becomes unattainable very quickly on top of any existing full time job responsibilities. In situations where the wrong idea gets selected by the employees of the wider company who is accountable for that decision? Do those other employees now get fired or receive a warning? If the decision is spread across many people and those employees don’t have accountability for being fully informed or don’t need to help in executing those ideas it is also hard to put much responsibility onto the team who are executing as they weren’t given the responsibility and influence over the outcome. If the engineering team is given a higher amount of influence over their own execution efforts it becomes far easier to apply a higher expectation around the accountability of that team selecting the right ideas to execute as they have the full experience and expertise required to make those decisions. The key decision that the wider group of employees does need to make when forming these teams is which people should be hired into the organisation to work on these different areas. For Web3 ecosystems these problems around the number of potential participants, complexity and accountability are far worse than this example of a large corporation! It is far more challenging than this example as the voters in Web3 ecosystems aren’t often working full time in the ecosystem, meaning they will often have even less experience and expertise on what is possible and pragmatic compared to the full time contributors who have months or years of experience. Although it might not be scalable and practical to push the responsibility of idea selection towards large groups of individuals, it is important that individuals can share their preferences and opinions about what ideas are most promising in both corporations and Web3 ecosystems.
## Contributor idea selection
**Advantages**
* **Aligned incentives** - Contributors are elected by the community to help with executing ideas and generating impact for the ecosystem. If the contributors do not align their contribution efforts with generating impact such as by addressing existing priorities or other potentially impactful initiatives they are less likely to be selected in future decisions. It is in their best interests to work on the most impactful ideas.
* **Expertise & experience** - A contributor who is spending their full time on executing ideas across different areas of an ecosystem will have a growing amount of expertise and experience about what works and what doesn’t, why ideas might be approached in one way or another and have all of the context that they’ve learned through working in the ecosystem. This expertise and experience can help with making more informed decisions about what is most promising and practical when suggesting and selecting ideas that they can contribute towards.
* **Accountability** - Voters will want to continue selecting and supporting the contributors who are producing the most impact for the ecosystem. When a contributor is compensated through funding they are accountable for aligning their contribution efforts with generating impact. This same accountability to generate impact will mean contributors will be incentivised to select the most promising ideas.
* **Scalable** - Using contributors to select the ideas they execute is far more scalable than pushing this responsibility towards the voters. With a contributor selection approach only the contributors who are relevant and interested in an area of work will need to participate in the idea selection process. This maximises the chance that the contributors involved are more informed on this focus area and reduces the need for contributors to spread themselves too thin across every possible focus area in the ecosystem. This approach means that voters are only responsible for electing the contributors that are the most competent and effective at generating impact. This approach is much easier and will take far less time than expecting voters to compare and select promising ideas.
**Drawbacks**
* **Lower voter outcome influence** - The voter will need to have higher levels of trust in the contributors ability to personally select the most promising ideas to work on to help with addressing the community selected priorities. The voters should still be able to express their preferences and opinions about any of the ideas that are being submitted and considered in the ecosystem. Voters can still have a high level of influence over how ideas get refined and executed if they are able to express those preferences and opinions to the contributors who are executing them. The key difference is the contributor is who is accountable and responsible for selecting which ideas they work on to create impactful outcomes.
# Incentive approaches
Comparing the different incentive approaches that could be used for compensating contribution efforts
Incentives could be attached to any of the funding processes during priority, idea or contributor selection. How these incentives get distributed across any of these processes can also be different. How incentives are handled in funding will have a direct impact on determining the budgeting, decision and governance complexities that emerge and each of these approaches will need to consider the game theory risks that could occur.
## Incentive approach criteria
The criteria for any approach in this comparison is that the incentive approach must be able to handle the bulk of the incentives being disbursed from an ecosystem's treasury. This means that the approach should be suitable and capable of handling 50% to 100% of the incentives that will be disbursed.
The execution incentive approaches that were not suitable for handling the majority of the incentives being disbursed have been identified with the applicable rationale:
{% content-ref url="/pages/gqMAQuVhEMCZPMH7awrU" %}
[Unsuitable incentive approaches](/approaches/incentive-approaches/unsuitable-incentive-approaches)
{% endcontent-ref %}
Any of these incentive approaches can benefit from introducing other supplemental incentive approaches to enhance the effectiveness of that specific incentive approach. This comparison is only concerned with approaches that could handle a majority portion of the incentives for a growing ecosystem.
## Approaches for handling incentives in a funding process
The incentive approaches for comparison include:
* [**Priority milestone incentives**](/approaches/incentive-approaches/priority-milestone-incentives) - Incentives are distributed to directly address priorities, how the priority will be addressed is broken down into milestones.
* [**Priority time incentives**](/approaches/incentive-approaches/priority-time-incentives) - Incentives are distributed to directly address priorities, an amount of compensation is requested to pay for the time the contributors will allocate towards addressing that priority.
* [**Idea milestone incentives**](/approaches/incentive-approaches/idea-milestone-incentives) - Incentives are distributed to execute ideas, how the idea gets executed is broken down into milestones.
* [**Idea time incentives**](/approaches/incentive-approaches/idea-time-incentives) - Incentives are distributed to execute ideas, an amount of compensation is requested to pay for the time the contributors will spend on executing that idea.
* [**Contributor time incentives** ](/approaches/incentive-approaches/contributor-time-incentives)- Incentives are distributed to pay for the time that contributors allocate to executing different ideas.
To compare these funding process incentive approaches a number of [factors have been considered](/approaches/incentive-approaches/incentive-factors-for-consideration) and then applied to each approach to try and determine the strengths and weaknesses of each one.
**Key takeaways**
* **Milestones increase budgeting complexity** - Contributors need to spend a far larger amount of time planning out the execution of an idea or the efforts involved to address a priority if the incentive has to be attached to milestones being completed. This incentive attachment to tasks increases the complexity of contributors needing to be accurate with their estimations. This is exceptionally difficult when those contributors might be working on novel ideas and research and the environment they are working in is constantly changing as well as external factors. Any mistake in the milestones can easily lead to under compensation or large delays in future payments which increases compensation tensions and can also lead to exploitation through unpaid contribution efforts.
* **Milestones increase voter complexity** - If the incentives are attached to priorities being addressed or ideas being executed there is an increased complexity for voters in determining whether those compensation requests are fair and reasonable. The reason for this is that each proposal can be focussing on different priorities and ideas and be executed very differently than other proposals. The result of this is that each milestone is unique and different from all others. This means that voters cannot easily compare and judge what is fair and reasonable based off one of their previous efforts to fully understand a proposal. Each time a voter wants to review a proposal they will need to understand the proposal more broadly and then specifically look at the milestones and scope in sufficient detail to make a judgement on each milestone. This is in contrast to time based incentives where the voters can instead learn the market data about what is fair and reasonable for different skills and roles and then apply this knowledge to compare every contributor that is requesting compensation.
* **Milestones increase game theory risks** - The more ability a funding process gives the contributor to self determine the tasks and budget the more the opportunity they give them to exaggerate and lie about what will be executed and how long it will take. As the scope of work increases the opportunity and ease of getting away with this only increases further due to the high complexity for the voter to accurately determine what is fair and reasonable. This means that the further away you move the incentives away from the contributors and towards high level priorities the riskier the incentives become for enabling bad actors. It is far more difficult to be malicious with contributor based compensation as the salary ranges and experience levels are not unique to each proposal and that information helps to keep any voters informed on whether someone is under or over requesting compensation.
* **Majority of incentives will go to contributors** - When you consider how the incentive is actually used within any of these incentive approaches a key thing to point out is that the majority of incentives will end up being used to pay for contributors and their execution efforts. This means that adding wrappers around how those incentives are distributed by attaching them to ideas or priorities simply means that the funding process is creating an intermediary step between how funding moves from the treasury to the contributors who will get paid for execution efforts.
**Additional approaches for consideration**
* **High level budgets** - An ecosystem could allocate budgets across different high level areas that are important to the ecosystem. Each of those budgeted areas could have the same or separate funding systems and processes which adopt any of the incentive approaches mentioned above. The important areas for an ecosystem could be broken down in a number of ways. One approach could be skill & responsibility based such as marketing or software development, another approach could be market based such as DeFi or AI.
**Incentive approaches analysis**
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[Incentive factors for consideration](/approaches/incentive-approaches/incentive-factors-for-consideration)
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[Priority milestone incentives](/approaches/incentive-approaches/priority-milestone-incentives)
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[Priority time incentives](/approaches/incentive-approaches/priority-time-incentives)
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[Idea milestone incentives](/approaches/incentive-approaches/idea-milestone-incentives)
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[Idea time incentives](/approaches/incentive-approaches/idea-time-incentives)
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[Contributor time incentives](/approaches/incentive-approaches/contributor-time-incentives)
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## Idea cost approaches
The majority of funding for executing ideas is often used for compensating the contribution efforts that are made by the individuals involved in the execution of those ideas. Ideas can also require different assets, products or services to help with generating the intended outcome. These costs for the different assets, products or services will need to be handled by the funding process. There are a few approaches for how idea costs could be handled:
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[Idea cost approaches](/approaches/incentive-approaches/idea-cost-approaches)
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## Considerations for incentivising the submission and maintenance of information
The majority of incentives will be used to help compensate for the contribution efforts made to execute different ideas. Incentives could also be useful for encouraging the submission of information such as proposals or they could also be used for compensating contributors to maintain information that is important to the ecosystem. Considerations for submission incentives and the maintenance of information can be found here:
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[Proposal submission incentives](/approaches/incentive-approaches/proposal-submission-incentives)
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[Maintenance of information incentives](/approaches/incentive-approaches/maintenance-of-information-incentives)
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# Unsuitable incentive approaches
Listing the execution incentive approaches which are not suitable for handling the majority of incentives
The incentive approach comparison aims to compare the different incentive approaches that could be used to compensate the majority of contribution efforts in a medium to large ecosystem. The scale and complexity of the contribution efforts involved in these ecosystems require suitable incentive approaches. Highly skilled contributors need to be effectively incentivised to participate in supporting and growing an ecosystem.
There are a number of the [execution incentive approaches](/incentives/contribution-incentive-approaches) that would not be very suitable for handling the majority of the incentives made available by larger ecosystems.
## No incentives
Providing no incentives for skilled contributors to help with developing and supporting an ecosystem is not sustainable over the long term. This problem applies regardless of whether this incentive approach was attached to priorities, ideas or contributors.
Even if skilled contributors were willing to give large amounts of time up for free and not be compensated for those efforts there would be the issue that their contribution efforts lead to making these ecosystems more valuable. This means they are working for existing owners of that ecosystem for their benefit and proportionally making them wealthier at their own expense. The incentives are not aligned with this approach.
## Task incentives
Task incentives are a great way for creating an incentive for contribution that needs to be scaled to a large number of people. A good example could be creating an incentive for people to answer a survey or another could be for rewarding voters for participating in decision making. This approach is not suitable for handling the majority of the funding being disbursed by a larger ecosystem due to the governance overhead in trying to create tasks for every possible different problem and opportunity. Much of what contributors will be working on is unique or more narrow in focus and completed by multiple separate teams working on their own specific areas. Novel research and innovation is also not something that can easily be turned into a repeatable task based incentive that can be planned out ahead of time.
## Impact incentives
Impact incentives focus on rewarding contributors based on the impact they generate for the ecosystem due to their contribution efforts. The immediate flaw with this approach is that impact is not known ahead of time meaning that contributors would be required to work for a period of time before impact can be defined and measured meaning there could easily be a large delay before they would be compensated. This lack of stability and uncertainty would make it much more problematic for contributors to participate in an ecosystem as they would have little certainty that they will be paid for their efforts. Measuring impact is also very difficult as there are many different outcomes that could create impact that aren’t necessarily quantifiable. Some areas of work, such as complex protocol design, could take much longer periods of time before any impact is generated. These situations could easily lead to higher amounts of tension and conflict if governance decisions misallocated the incentives available due to not taking enough of these factors into account when measuring impact. Impact incentives are not very suitable as a main incentive approach to handle the majority of funding. Impact incentives can be highly effective as an supplementary approach to enhance another incentive approach that was adopted. If an ecosystem did want to increase their allocation of funding to use impact incentives over time, the key outcome the ecosystem will want to achieve is that they become increasingly effective at accurately understanding and measuring impact so that the incentives made available are not poorly allocated.
## Performance incentives
Performance incentives focus on rewarding contributors based on their performance when executing and supporting the ecosystem. Performance incentives are a great way to ensure contributors who put larger amounts of effort in get the recognition deserved and rewarded for their contribution efforts. A similar flaw with this approach is that the performance of a contributor is not known ahead of time. This means that contributors would need to make a certain amount of contribution effort first before their performance can be assessed and compensated. Measuring performance also has some similar complexities to measuring impact where some contributors could create impact for an ecosystem in a multitude of different ways. Some contributors could be software developers who are responsible for creating code but are also excellent mentors to other contributors in the space. They might produce less code each month due to this but they also might have increased the productivity of other developers by a large margin. How should any reviewers of that process fairly determine who has performed better? There can be a reasonable answer to this question however it increases the complexity of using this approach for the majority of the incentive being made available. Due to this complexity this incentive works well as an supplementary incentive approach for improving the compensation of people who have made more effort in an ecosystem than others. If the majority of the incentives being made available are handled with performance incentives then the accuracy of the performance reviewing process needs to be very high as it would have a large influence on exactly what contributors get paid. This could easily lead to situations where contributors who were performant and impactful in others ways are not correctly recognised and compensated which could lead to conflicts and disengagement from the ecosystem. If an ecosystem wants to increase the amount of incentive that gets distributed through a performance incentive they will need to make sure their ability to identify, measure and compare the performance of each contributor is highly accurate.
# Incentive factors for consideration
Listing the different factors that will be considered for each funding incentive approach
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Budgeting complexity**
* **Description** - Contributors need to plan out the budget required for their submission so that their contribution efforts can be fairly compensated. The proposal submission will detail how the compensation would be used. Where the incentive is attached in funding will impact the complexity of budget planning.
* **Maximum score** - 5, Very important. Budget setting is something that will deeply impact the submission information and level of detail that is required. Higher complexity can lead to incorrect incentive outcomes or disengagement from the process due to the time it takes just to participate in making a submission and the issues that can occur when those budgets are not fully accurate.
* **Scoring questions** - What budget planning is required to make a submission? What benefits does that budget planning approach provide? How difficult is it for those estimations to be accurate? How often could the budget be under or over estimated and how does that complicate the distribution of incentives over time and impact the initial budget planning?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Voter decision complexity**
* **Description** - Budgets attached to submissions will need to be understood and compared by voters so they are informed when selecting which submissions are fair and reasonable and also which submissions could be the most effective at generating impact for the ecosystem.
* **Maximum score** - 5, Very important. Where and how the incentive is attached to submissions will directly influence the amount of complexity there is for voters to understand and compare the differences in submissions and their proposed budgets.
* **Scoring questions** - How much does the budgeting approach increase the complexity for voters? Does it take just more time to compare the submissions or is the comparison now also far more complex to understand? Can the voter reuse information when making comparisons?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Governance complexity**
* **Description** - Governance of the incentives will concern what checks and balances are necessary for the incentive approach to function effectively and who has control over the assets as they flow from the treasury towards the contributors involved in different initiatives. The incentive approach can influence how funds are managed and disbursed.
* **Maximum score** - 5, Very important. Governance over how the incentives are managed and distributed could either increase or decrease the chances of misuse and the amount of shared complexity between the contributors involved. The larger the incentives become the more important it is to think about how the incentives flow from the treasury to the contributors.
* **Scoring questions** - Who has influence and control over how the budget requested will be used? Are there increased risks of corruption or tension between contributors due to the approach? What checks and balances might be needed to ensure the incentives are used correctly? How can voters intervene when an issue emerges?
* **Scoring** - Lower complexity is good (Score - 5). Higher complexity is bad (Score - 1).
**Game theory risks**
* **Description** - Incentives will play a large role in influencing certain outcomes based on how voters and proposers could most benefit themselves in different ways by interacting with each incentive approach.
* **Maximum score** - 5, Very important. Contributors and voters will respond to the incentives that are placed in front of them. How those incentives are structured and distributed will lead to certain responses based on the game theory that those approaches create.
* **Scoring questions** - How could voters or contributors act to increase their chances of receiving the available incentives and what impact could that have on the effectiveness of the funding process? What emergent behaviours could occur due to how the incentives are structured? Does the incentive approach make it more or less likely that novel initiatives get funding that could generate large amounts of impact for the ecosystem?
* **Scoring** - Lower risk is good (Score - 5). Higher risk is bad (Score - 1).
**Contribution flexibility**
* **Description** - Ideas and priorities can change as new information emerges or when preferences or the environment changes. Contributors can benefit from being able to respond to these changes by reallocating their contribution efforts towards initiatives that can generate the most impact for the ecosystem. How incentives get attached to the funding process can influence the amount of complexity there is for contributors to change how they allocate their efforts.
* **Maximum score** - 5, Very important. If an ecosystems contributors are not able to be responsive to important changes that happen in the ecosystem there is an increased risk that incentives are wasted due to contribution efforts being allocated to non impactful areas. If an emergency happens in the ecosystem the available contributors will need to be flexible and able to respond to these emergencies as fast as possible.
* **Scoring questions** - What influence does the incentive have when it is attached to different parts of the process? If contributors suddenly change what they are working on does this compromise the original intent of the incentives? What complexities can emerge when peoples contribution efforts get redirected to other areas?
* **Scoring** - High flexibility is good (Score - 5). Low flexibility is bad (Score - 1).
**Income stability**
* **Description** - Where the incentives get attached to the funding process will influence the income stability for contributors. This will be based on how likely it is they get under or over compensated for their contribution efforts and also how consistently they are able to get selected for receiving future compensation.
* **Maximum score** - 5, Very important. Contributors who have to handle unstable income will need to spend more of their time planning and accounting for these problems. Some contributors might decide to simply not participate in the environments where income is not stable as they cannot afford to not be paid for their contribution efforts. Higher income stability means that contributors can spend more of their time focusing on their contribution efforts and generating impactful outcomes for an ecosystem.
* **Scoring questions** - What is the likelihood of a contributor receiving future compensation based on how it is being attached to the funding process? How often could contributors be under or over compensated for their contribution efforts?
* **Scoring** - High stability is good (Score - 5). Low stability is bad (Score - 1).
# Priority milestone incentives
Incentive approach for addressing priorities using budgeted milestones
**Overview**
Priority milestone incentives mean that a proposal would detail out the different tasks and steps involved in addressing a priority by executing different milestones. Each of those milestones would have to specify the amount of compensation that is required to execute each one. An amount of time could be specified against each of the execution tasks to achieve this total required compensation. Funds are released as each milestone gets executed where evidence will need to be submitted to prove that a milestone is complete. The milestones are strict in terms of the expected execution output that will occur for the compensation to be distributed. Any changes to the milestones would need to go through some form of approval process.
**Very high budgeting complexity (Score - 1)**
The budgeting complexity would inherit the same complexities as the idea milestone incentives approach. On top of this there is even increased complexity due to the following:
* **Budget planning complexity** - The larger the scope and budget is for addressing a priority the higher the complexity there is in budget planning due to the range of ideas that might be involved and the range and depth of the tasks that might need to be executed for those ideas. Large scope also increases the likelihood that something could happen during execution that changes the priority or the ideas being executed. This further increases the difficulty of creating accurately budgeted milestones.
* **Execution scope risks** - Having proposals that could fund multiple ideas increases the potential scope and scale of the compensation being requested. The larger the scope of the idea the more risk there is that the execution efforts could take longer or shorter than expected due to a range of emerging factors during execution.
**Very high voter decision complexity (Score - 1)**
The voter decision complexity would inherit the same complexities as the idea milestone incentives approach. On top of this there is even increased complexity due to the following:
* **Ease of understanding** - Proposals that have multiple ideas would increase the complexity for the voter to fully understand whether those ideas can be executed within the stated milestone budgets. The larger the amount of scope the higher the complexity is for voters to fully understand whether the compensation duration and amount is fair and reasonable.
* **Ease of comparison** - Milestones across each proposal could be vastly different in scope and compensation for addressing different priorities. This makes it very difficult for voters to easily compare and determine if each of these proposals is fair and reasonable in their budgets without a sufficient level of understanding of each proposal individually.
**High governance complexity (Score - 2)**
The governance complexity would inherit the same complexities as the idea milestone incentives approach. On top of this there is even increased complexity due to the following:
* **Incentive distribution risks** - Larger proposal compensation requests increase the risks of the incentive being stolen or misused by the individual or multisig of contributors who are responsible for handling it.
* **Size of compensation risk** - Risks increase around how funds are used in any situation where larger amounts of compensation are handled by an individual or multiple people using a multi-sig. There would be a higher incentive to steal or misuse the funds for personal gain.
* **Community moderation complexity** - A larger scope and budget for addressing priorities means that contributor set priorities have more of a risk of being exaggerated or containing lies about how long a piece of work would actually take due to the amount of incentives involved. A larger amount of scope increases the moderation complexity to effectively determine if these suggested budgets are fair and reasonable.
**Very high game theory risks (Score - 1)**
The game theory risks would inherit the same risks as the idea milestone incentives approach. On top of this there is even increased risks due to the following:
* **Proposal details** - Addressing a priority can take a larger amount of execution effort which could result in requests for a larger amount of compensation in each proposal. The larger the scope and budget there is for a proposal the more risk there is that the estimated time it takes to execute something is exaggerated or purposefully incorrect. As milestones for each proposal are unique this becomes even harder to determine if the contributors are trying to game the system as they are able to self define the milestones.
* **Malicious voters** - The larger that the available incentive is the more reasons there are for malicious voters to try and influence the outcome of the funding decisions.
**Low contribution flexibility (Score - 2)**
* **Changing an existing idea** - A contributor would only partially be able to change how they execute an idea as the outcomes would still need to still match the milestones that have been budgeted and set. If the contributor wanted to change the milestones they would need to seek approval from the community to make changes to those existing milestones. If contributors were able to change these milestones without any form of approval then it would remove the reason for using milestones incentives in the first place as instead they could have simply just adopted time based incentives so that the contributors can change their execution approach at any point. This approach is not inherently very flexible for enabling contributors to change how they execute already planned ideas that address a funded priority.
* **Contributing to a different idea** - For ideas in the same priority a contributor might need to come to some form of agreement with other contributors if the incentives are already allocated using milestones. For ideas focussed on other priorities a contributor would similarly need to come to some agreement about how they will be compensated under the other priorities planned budgets. This approach has a relatively small amount of flexibility for enabling contributors to work on different ideas.
* **Contributing to a different priority** - The contributor would need to get funding for a different priority or come to some agreement with another team who already has funding for addressing that different priority. This approach is not very flexible for enabling contributors to work on different priorities.
* **Incentive complexities** - A contributor looking to contribute towards a different priority would need to determine how much compensation is needed for them to contribute to that priority and then also come to some form of agreement with the other contributors who were funded for that priority. This is more complex to handle as the milestone budgets would have already been set which can increase the chance that they need to be adjusted. It could also be difficult to budget for the future work correctly due to many changing factors that could influence how long they actually spend contributing to these other priorities. Contributors would also face incentive complexity when they want to change any existing milestones and budgets that they have already planned for with their own funded priority. Incentive complexities exist for any type of contribution change.
* **Moderation complexity** - Some form of approval process is likely needed for when an ideas milestones need to be changed.
**Low income stability (Score - 2)**
* **Likelihood of future income** - Being selected for one priority will not result in any high certainty that the contributor will have their future priorities selected. The contributor will need to identify the most promising priorities that might get selected and then request to join those proposals if they want to increase the chances that they receive future compensation.
* **Compensation accuracy** - Predicting the time it takes for every execution milestone is challenging. Ideas that need to be executed may change due to factors outside of the contributors control during execution. These changing ideas, factors and environments can lead to situations where the contributor is under or over compensated for their contribution efforts.
**Total score = 9 / 30**
# Priority time incentives
Incentive approach for addressing priorities using time based compensation
**Overview**
Priority time incentives mean the proposals will detail out how a priority is going to be addressed and what time they will need to make progress on addressing that priority. This incentive approach could work without the ideas and tasks involved being planned out. However for this example we will assume that proposals always have a plan of what will be executed. The only guarantee this proposal is making is that a certain amount of time will be directed to addressing this priority and that it will be achieved through different peoples contribution efforts. The contributors involved are not being mandated to spend an exact amount of time on a specific idea or task within an idea that they have planned out. Instead they are required to provide proof of their contribution efforts to showcase what has been achieved over a period of time. Proposers would submit another proposal to request future funding for addressing the same priority once the allocated time from the previous proposal has been used up.
**Moderate budgeting complexity (Score - 3)**
The budgeting complexity would inherit the same complexities as the idea time incentives approach. On top of this there is even increased complexity due to the following:
* **Budget planning complexity** - Proposals that have multiple ideas for helping to address a priority would have increased complexity in trying to add estimations about how long it could take to address a priority. Priorities do not necessarily need to have an exact quantifiable outcome on whether they have been addressed or not which only further adds to this complexity of trying to estimate how long it might take. One easier approach could be to plan out a shorter period at a time and to then review how much more effort is needed to address a priority after each period of execution.
* **Execution scope risks** - There should still not be a high risk of having unstable distribution of incentives if they are distributed based on contribution time however there is an increased risk that the scope of execution could increase or decrease due to an increasing amount of surrounding factors as well as changing factors for each ideas execution. There also might be situations where the priority being addressed becomes less important and other situations where other priorities become far more important.
**Moderate voter decision complexity (Score - 3)**
The voter decision complexity would inherit the same complexities as the idea time incentives approach. On top of this there is even increased complexity due to the following:
* **Ease of understanding** - Proposals with multiple ideas in them for addressing a priority would increase the complexity for the voter to understand whether these ideas can be executed in any estimated time period. The larger the amount of scope the higher the complexity is for fully understanding whether the compensation duration and amount is fair and reasonable.
* **Ease of comparison** - Attaching the incentive to priorities can increase the scope of the proposals which can increase the total differences and overall complexity. This will make it even more difficult to compare proposals with potentially vastly different budgets and scopes.
**Moderate governance complexity (Score - 3)**
The governance complexity would inherit the same complexities as the idea time incentives approach. On top of this there is even increased complexity due to the following:
* **Size of compensation risk** - Proposals looking to address a priority could be of a larger size if they are intending to execute multiple ideas. If excess funding is requested beyond the initial contributors involved in the proposal there is a higher risk that these funds could be misused. The larger the amount of funds being requested the more that there is a need for transparent and verifiable usage of funds.
* **Community moderation complexity** - If there are multiple ideas being executed to help with addressing a single priority there is a higher amount of complexity for the community to moderate this incentive approach as it could be more complex to share disapproval towards some of the execution efforts and approve other efforts if it’s all combined together into single decisions.
**High game theory risks (Score - 2)**
The game theory risks would inherit the same risks as the idea time incentives approach. On top of this there is even increased complexity due to the following:
* **Proposal details** - Addressing a priority can take a larger amount of execution effort which could result in allocating a larger amount of compensation in a given proposal. The larger the scope of a proposal the more risk there is that the estimated times it takes to execute something are exaggerated or purposefully estimated incorrectly. This should mostly be picked up using a verification approach of individual contribution logs however the risk of potential abuse happening would still be higher if there is a large enough incentive involved.
* **Malicious voters** - The larger that the available incentive is the more reasons there are for malicious voters to try and influence the outcome of the funding decisions.
**Moderate contribution flexibility (Score - 3)**
* **Changing an existing idea** - A contributor could change how they execute any existing idea that is focussed on the same priority as much as they need to. There is no added complexity for changing how an existing idea gets executed.
* **Contributing to a different idea** - For other ideas that are funded by the same priority incentive there would be no added complexity for a contributor to reallocate their efforts to that idea. For ideas that are addressing different priorities a contributor would need to come to some agreement with those other contributors about how they will be compensated and how they will work under their allocated incentives. This approach is somewhat flexible for enabling contributors to work on different ideas.
* **Contributing to a different priority** - The contributor would need to get funding for the different priority or come to some agreement with another team who already has funding for that different priority. This approach is not very flexible for enabling contributors to work on different priorities.
* **Incentive complexities** - A contributor looking to contribute towards a different priority would need to determine how much compensation is needed for them to contribute to those initiatives and then also come to some form of agreement with the other contributors who were funded for addressing that priority. Budgeting for this correctly could be difficult to get right due to many changing factors that could influence how long they actually spend contributing to addressing that priority. Contributors would have no added incentive complexity when changing an idea that they are already working on when it's still related to addressing the priority that they already have funding for.
* **Moderation complexity** - No approval process would be needed for contributors to change how they are executing an existing idea or when they want to allocate their contribution efforts to other ideas that address the same priority. For situations where contributors want to help with another funded priority this is up to the other contributors that they need to come to an agreement with. This means a community approval process wouldn't be needed.
**Moderate income stability (Score - 3)**
* **Likelihood of future income** - Being selected for one priority will not result in any high certainty that the contributor will have their future priorities selected. The contributor will need to identify the most promising priorities that might get selected and then request to join those proposals if they want to increase the chances that they receive future compensation.
* **Compensation accuracy** - Contributors would be paid for their time spent executing ideas that help to address the funded priority. The compensation can be set and agreed ahead of time in the priority proposal meaning there should be a high stability around the actual income they receive whilst they are working on that funded priority.
**Total score = 17 / 30**
# Idea milestone incentives
Incentive approach for executing ideas using budgeted milestones
**Overview**
Idea milestone incentives mean that a proposal would detail out the different tasks and steps involved in executing an idea across different milestones. Each of those milestones would have to specify the amount of compensation that is required to execute each one. An amount of time could be specified against each of the execution tasks to achieve this total required compensation. Funds are released as each milestone gets executed and evidence is provided to prove that a milestone is complete. The milestones are strict in terms of the expected execution output that must occur for the current milestone to be fully compensated. Any changes to the milestones would need to go through some form of approval process.
**High budgeting complexity (Score - 2)**
* **Budget planning complexity** - Proposals would need to break down the idea into milestones with the tasks that will be executed in each one. The amount of compensation required for that milestone then needs to be attached. The time taken for each of those tasks could also optionally be included to demonstrate the exact calculations. This creates a high amount of complexity for the proposer as they need to be accurate on the exact time that will be spent on each milestone. This can be difficult to achieve as there are often many changing surrounding factors that can influence the time it takes to execute an idea as well as changes in the scope of the idea as more is learnt over time. Contributors will need to respond to this changing information and environment as it occurs.
* **Execution scope risks** - The larger the scope of the idea the more risk there is that the execution efforts could take longer or shorter than expected due to a range of emerging and changing factors during execution. This could result in contributors being under or over compensated for different pieces of work due to the requirement of using milestone based budgets. Differences in actual compensation with the expected compensation could easily increase tension between contributors when they are underpaid for their efforts. Alternatively there is also a risk that contributors could try to exploit the process and repeatedly get overcompensated. Changes of scope that result in different budgeting outcomes is a high risk for proposers. Smaller scoped proposals also do not remove the budgeting complexity as now proposers need to repeatedly make many smaller proposals with accurate budget planning which still adds large amounts of administrative overhead as well uncertainty in being selected and funded for each of those ideas.
**High voter decision complexity (Score - 2)**
* **Ease of understanding** - Voters need to roughly understand the feasibility of the budget that has been allocated to each of the suggested milestones to determine if the compensation is fair and reasonable. Voters would be able to see how much time and effort is going to be spent on each milestone. Voters would either accept or decline that suggestion based on their own expertise and understanding. There is a high complexity for voters due to the fact they need to have enough understanding of the idea and required skills to effectively judge what is fair and reasonable. When the incentive is more closely attached to the tasks itself the voter needs to have the right background and expertise to truly understand the skills and time it might take to execute certain areas of work. This is in contrast to time incentives where the voter only needs to understand what the market rates are for different roles and the experience level of the contributors involved in the idea.
* **Ease of comparison** - Each idea would have completely different milestones and scoping of those milestones. This factor makes it harder to standardise the milestone structure and content which then makes it harder for voters to make easy comparisons between the different proposals that are requesting compensation. In comparison, it is far easier for voters to compare time based incentives as the voter is able to look at the requested salary against existing market data to be sufficiently informed on whether that request is fair and reasonable.
**Moderate governance complexity (Score - 3)**
* **Incentive distribution risks** - The proposal budget could be handled by an individual or a group of people using a multi-sig. If it is managed by one person they have influence over how and when this incentive is distributed which could cause tensions if they misuse or restrict how this incentive is distributed. Similarly a multi-sig also introduces issues where conflicts could occur during execution that slow down or prevent funds from being distributed.
* **Size of compensation risk** - Idea funded proposals could request funding beyond what is needed for compensating the initial contributors involved. For instance funding could be requested to help fund future contributors. The risk of misusing these funds increases with the amount of funds that can be requested. The larger the available incentive is the higher the likelihood that people could be willing to try and abuse the funding process for self gain. Sufficient checks and balances will be needed to ensure transparent or verifiable usage of funds.
* **Community moderation complexity** - Community governance would help with identifying which ideas are not being executed well so that more competent contributors can be selected in future decisions. If there are only idea milestone submissions as contribution logs there is a higher governance complexity for the community as it could become more difficult to determine if there are highly performant contributors in that group of people executing the idea as they won’t have the individual contribution logs to compare with other people who were compensated. The community would require more accurate contribution information using individual time based logs rather than a milestone task approach if they wanted to more easily understand and compare the performance of contributors across the ecosystem.
**High game theory risks (Score - 2)**
* **Proposal submissions** - There is an incentive for contributors to submit multiple ideas to increase their chance of receiving compensation. Ideas can come in many sizes so a funding process restricting contributors to only one idea submission could be limiting. In contrast if the process accepts multiple ideas from the same contributors this means that there is a higher complexity for voters to compare and select from these.
* **Proposal details** - There is an incentive to exaggerate the amount of work it will take to complete a milestone so that the contributors can receive more compensation than the work to be completed. This can increase the verification complexity as the moderators need the right skills and context to be able to properly understand whether a milestones budget is fair and reasonable. If milestones are based on grouped tasks this gives the contributors more ability to manipulate this number and for it to be hard to spot due to the fact that milestones will often be unique which makes them difficult to compare with other milestones in the ecosystem.
* **Execution verification** - Proposers would be required to submit evidence to prove they have completed a given milestone. The main way that the contributors could try to exploit this process for their benefit is by claiming they did the work of someone else in a milestone and using that as evidence.
* **Malicious voters** - Malicious groups of voters that are trying to benefit themselves would have a larger incentive and ability to get access to more funding compared to just contributor incentives. This is because the cost of an idea could be budgeted to exceed the costs of the contributors salaries that are suggesting the proposal.
* **Voting outcomes** - Voters have the personal incentive of voting on things that will benefit them. The risk of this occurring at a wider scale is that novel research and innovation that does not immediately benefit the voter does not get actively supported. This could just be because the potential impact of this work is not easily understood due to its complexity or novelty. It could be difficult to get the community to widely agree on every idea that should be supported that could have the potential to generate large amounts of impact.
**Very low contribution flexibility (Score - 1)**
* **Changing an existing idea** - A contributor would only partially be able to change how they execute an idea as the outcomes would still need to still match the milestones that have been budgeted and set. If the contributor wanted to change the milestones they would need to seek approval from the community to make changes to those existing milestones. If contributors were able to change these milestones without any form of approval then it would remove the reason for using milestones incentives in the first place as instead they could have simply just adopted time based incentives so that the contributors could change their execution approach at any point. This approach is not inherently very flexible for enabling contributors to change how they execute their already funded idea.
* **Contributing to a different idea** - For other funded ideas a contributor would need to come to some form of agreement with those other contributors about how they will be compensated and how they could contribute under their available budget. This approach is not very flexible for enabling contributors to work on different ideas.
* **Contributing to a different priority** - The contributor would need to get funding for an idea that addresses the other priority or come to some form of agreement with another team who already has funding for an idea that is addressing the different priority. This approach is not very flexible for enabling contributors to work on different priorities.
* **Incentive complexities** - A contributor looking to contribute towards a different idea would need to determine how much compensation is needed for them to contribute to those initiatives and then also come to some form of agreement with the other contributors who were funded for that initiative. This is more complex to handle as the milestone budgets would have already been set which increases the chance that they need to be adjusted due to contributors moving around their contribution efforts. It could also be difficult to budget for the future work correctly due to many changing factors that could influence how long they actually spend contributing to these other ideas. Contributors would also face incentive complexity when they want to change any existing milestones and budgets that they have already planned for their own ideas. Incentive complexities would likely occur for any type of contribution change.
* **Moderation complexity** - Some form of approval process is likely needed when milestones need to be changed for an already funded idea.
**Low income stability (Score - 2)**
* **Likelihood of future income** - Being selected for one idea will not result in any high certainty that the contributor will have their future ideas get selected. The contributor will need to identify the most promising ideas that might get selected and then request to join those proposals if they want to increase the chances that they receive future compensation.
* **Compensation accuracy** - Predicting the time it takes for every execution milestone is challenging. Ideas that need to be executed may change due to factors outside of the contributors control during execution. Changes in the idea being executed and surrounding factors and environments can lead to situations where the contributor is under or over compensated for their contribution efforts.
**Total score = 12 / 30**
# Idea time incentives
Incentive approach for executing ideas using time based compensation
**Overview**
Idea time incentives mean the proposals will detail out how an idea is going to be executed and what time they are looking to be compensated for to make progress on executing that idea. The proposal may not intend to fully execute the idea and could just be funded for a certain time period of execution efforts. This incentive approach could work without the tasks and steps involved in idea execution being fully planned out. However for this example we will assume that proposals always have a plan of what will be executed. The only guarantee this proposal is making is that a certain amount of time will be directed towards executing an idea with the time based contributions efforts made from any people working on that idea. The contributors involved are not being mandated to achieve a certain outcome over that time period. The contributors will receive compensation for their contribution time and not the exact outputs. Instead they are required to provide logs of their contribution efforts to showcase what has been achieved over each period of time. Proposers would submit another proposal to request future funding to continue executing the same idea once the allocated time from the previous proposal has been used up.
**Low budgeting complexity (Score - 4)**
* **Budget planning complexity** - Proposals would only need to specify the total amount of time that they will be spending on executing an idea. This total time could equate to what is needed to execute the idea fully or it could just help with executing a certain amount of an idea such as with 3 or 6 month time periods. If the proposal is stating a total completion time there is complexity in getting this value right as many factors could change that increase or decrease the time it takes to execute an idea. Planning is simple for a time based approach as contributors are paid for the time they allocate to executing the idea. The contributors may state what they believe will be the total time it will take to execute that idea however if this is wrong compensation would still be distributed based on the total time they have contributed. The main complexity for budget planning with this approach would be for situations where the contributor tries to estimate the total time they believe it will take to execute the different parts of the idea.
* **Execution scope risks** - If the contributors complete the work faster than what was stated then they are incentivised to continue making efforts towards future work to receive the next round of compensation. This can help with aligning the incentive for contributors to improve or extend the work they have started in situations where it didn’t take as long as expected. Another benefit of this approach for budgeting is that if the contributors were funded for a few ideas and one of these was completed in a shorter time than anticipated then the incentive for those ideas could then be immediately used to support the other ideas execution efforts. The main execution scope risks are that an idea might not get completed in the time that the contributors have been funded for.
**Low voter decision complexity (Score - 4)**
* **Ease of understanding** - Ideas can still be planned out with the tasks and steps involved with executing an idea. The exact time taken and budget being allocated to each step is what isn’t required using contributor time based incentives. It would not be very difficult to understand the budgets of each idea if the salary or hourly rate is provided. Voters would be able to use existing industry data about salary ranges against different roles and experience levels to determine whether the requested values are fair and reasonable. Voters could also reflect on the tasks involved in the ideas execution to determine if the complexity of the idea matches the skill and compensation being requested.
* **Ease of comparison** - It will be far easier to compare proposals when time incentives are used as the voters will be able to see the compensation requested for each individual involved in the idea based on the time and amount of compensation being requested. This makes it easy for voters to compare ideas and see which ones are fair and reasonable for the complexity of the idea that they would be working on.
**Low governance complexity (Score - 4)**
* **Incentive distribution risks** - With time based incentives the funding process could be set up to compensate the individuals directly from the treasury based on the idea proposal requests. Distribution of compensation going straight to individuals helps to remove the risks around a central actor controlling funds and reduce the risk around disputes occurring when a multisig approach is used.
* **Size of compensation risk** - Idea funded proposals could request funding beyond what is needed for compensating the initial contributors involved. For instance funding could be requested to help fund future contributors. The risk of misusing these funds increases with the amount of funds that contributors are able to request. The larger the available incentive is the higher the likelihood that people might be willing to try and abuse the funding process for self gain. Sufficient checks and balances will be needed to ensure transparent and verifiable usage of funds.
* **Community moderation complexity** - Community governance would help with identifying which ideas are not being executed well so that more competent contributors can be selected in future decisions. Having individual monthly contribution logs will keep everyone in each team accountable for executing work that they stated they will and also make it far easier for the community to compare the performance of different contributors across the ecosystem.
**Moderate game theory risks (Score - 3)**
* **Proposal submissions** - There is an incentive for contributors to submit multiple ideas to increase their chance of receiving compensation. Ideas can come in many sizes so a funding process restricting contributors to only one idea submission could be limiting. In contrast if the process accepts multiple ideas from the same contributors this means that there is a higher complexity for voters to compare and select from these.
* **Proposal details** - There is an incentive to exaggerate the amount of time it would take to execute the tasks involved in an idea to receive more compensation than the actual effort required. As contribution logs would be submitted monthly it will be easier to compare submissions and identify which contributors are not performing as well as others by comparing their execution outputs with other contributors. However the risk that contributors still try to do this would still be an ongoing concern and consideration.
* **Execution verification** - Proposers would be required to submit evidence to prove they have completed a month's worth of execution efforts. The main way that the contributors could try to exploit this process for their benefit is by claiming they did the work of someone else in a milestone and using that as evidence or by claiming that the work they did complete took a month when in fact it took less than a month.
* **Malicious voters** - Malicious groups of voters that are trying to benefit themselves would have a larger incentive and ability to get access to more funding compared to just contributor incentives as the compensation for an idea could be budgeted to exceed the costs of the contributors salaries that are suggesting the proposal. The excess in costs could be misused to benefit the proposers.
* **Voting outcomes** - Voters have the personal incentive of voting on things that will benefit them. The risk of this occurring at a wider scale is that novel research and innovation that does not immediately benefit the voter does not get actively supported. This could just be because the potential impact of this work is not easily understood due to its complexity or novelty. It could be difficult to get the community to widely agree on every idea that should be supported that could have the potential to generate large amounts of impact.
**Low contribution flexibility (Score - 2)**
* **Changing an existing idea** - A contributor could change how they execute an idea as much as they need to as they have not committed to any specific execution milestones and instead must allocate a period of time towards executing the idea. There is no added complexity for contributors to change how an existing idea gets executed.
* **Contributing to a different idea** - For other funded ideas a contributor would need to come to some agreement with those other contributors about how they will be compensated and how they will work under their allocated incentives. This approach is not very flexible for enabling contributors to work on different ideas.
* **Contributing to a different priority** - The contributor would need to get funding for an idea that addresses the other priority or come to some agreement with another team who already has funding for an idea that is addressing the different priority. This approach is not very flexible for enabling contributors to work on different priorities.
* **Incentive complexities** - A contributor looking to contribute towards a different idea would need to determine how much compensation is needed for them to contribute to those idea and then also come to some form of agreement with the other contributors who were funded for that idea. Budgeting for this correctly could be difficult to get right due to many changing factors that could influence how long they actually spend contributing to these other ideas.
* **Moderation complexity** - No approval process is needed for contributors to change how they are executing an existing idea. For situations where contributors want to help with another funded idea this is up to the other contributors that they need to come to an agreement with. This means a community approval process wouldn't be needed.
**Moderate income stability (Score - 3)**
* **Likelihood of future income** - Being selected for one idea will not result in any high certainty that the contributor will have their future ideas get selected. The contributor will need to identify the most promising ideas that might get selected and then request to join those proposals if they want to increase the chances that they receive future compensation.
* **Compensation accuracy** - Contributors would be paid for their time spent executing the funded idea. The compensation can be set and agreed ahead of time in the ideas proposal meaning there should be a high stability around the actual income they receive whilst they are working on that funded idea.
**Total score = 20 / 30**
# Contributor time incentives
Incentive approach for compensating contributors time spent on executing any idea
**Overview**
Contributors would provide their personal, professional, contribution history information and expected compensation and suggested duration of contribution when submitting their contributor proposal. If selected the contributor would be paid their compensation amount over the defined period of time such as monthly for six months. Contributors would need to submit a proof of contribution log to provide evidence of the work they’ve done over that period of time to be eligible to receive the next round of compensation. Contributors would be help with addressing priorities by executing ideas that have been suggested and maintained in a separate process. Contributor salary ranges could be suggested as guidance for contributors to consider when making a proposal. Salary lower and upper bound ranges could also potentially be mandated through system parameters. For this example no mandated salary ranges would be applied due to the inherited governance complexity and limitations it could cause in how contributors want to participate.
**Very low budgeting complexity (Score - 5)**
* **Budget planning complexity** - Contributors only need to state what their expected compensation will be for the period that they would be contributing for. The complexity for budget planning for salaries is reduced by the fact that there is already a lot of market data available about the different roles that exist and the salary ranges they get paid. It is ultimately up to the contributor to determine what they are happy with and the community to decide whether they accept or decline that budget. Contributors will also be able to provide evidence of previous roles and the attached compensation or provide contribution history to help with justifying their compensation request.
* **Execution scope risks** - The scope is time based and only focussed on one individual, meaning there are no risks of the proposal taking longer or shorter than expected. The contributor will simply be compensated for the contribution time that was requested and approved. If the contributor provides evidence that shows their month of contribution effort they will be eligible to receive the next round of compensation.
**Voter decision complexity (Score - 5)**
* **Ease of understanding** - Voters only need to understand who the contributors are along with any education, professional background and contribution history to make a judgement on how impactful each contributor could be for the ecosystem. Voters would be able to see existing market data about salaries and experience levels and then can compare this information with all of the different contributors. The voters can reuse the same market information to determine if the contributor matches up with the compensation requested and also can easily compare contributors to better inform their decisions.
* **Ease of comparison** - The information being requested by each contributor is similar and easy to structure for making it very easy to compare many contributors. This ease of comparison will make it much easier for voters to select the most promising candidates from a large list of options.
**Low governance complexity (Score - 4)**
* **Incentive distribution risks** - There aren't any risks around incentive distribution with a contributor time incentive approach as the entire incentive is allocated to a single individual. All of the compensation would be released to the individual after each month's worth of execution efforts are verified. This removes the governance complexity of managing any of the allocated assets as the incentive is not moving through an intermediary step and being distributed between many contributors.
* **Size of compensation risk** - The compensation would only cover an individual's salary meaning there would be less opportunity or incentive for corruption and misuse of funds as the incentive is targeted to one individual's compensation.
* **Community moderation complexity** - There is at least moderate complexity for a community to remove bad actors as the community will need to compare the individuals contribution logs and determine which of those is the worst and of those which do not meet the expected standard. One way to reduce the potential impact of bad actors being selected is to adopt some form of probation period to more easily prevent those contributors from receiving future funding without the need for any community intervention. A key benefit of attaching the incentive directly to the contributors is that if a contributor isn’t performing well on one idea they could redirect their efforts to another idea immediately. This increases the impact of community engagement and feedback with contributors as they could more easily identify any ongoing issues and provide constructive feedback that supports those contributors in generating impact in other areas.
**Low game theory risks (Score - 4)**
* **Proposal submissions** - It would be difficult to post multiple proposals as a contributor without lying about their background in the other proposals as otherwise all the proposals would be duplicates. If a contributor did try to make multiple submissions it would become more obvious once they start trying to receive funding due to any onboarding checks, video calls or contribution logs. Any attempt to receive funding from duplicate proposals would cause long lasting damage to their reputation.
* **Proposal details** - Contributors are incentivised to exaggerate or lie about their credentials and background to increase their chances of being selected. Some of these claims could be verified by checking with educational entities or previous employers. Over time if verifiable credentials are adopted more widely this will offer one potential solution to this problem around verification. If a contributor lies about their background there is at least a moderate chance that this becomes more obvious during any onboarding or initial contribution outputs.
* **Execution timeline** - Contributors would only be able to request an amount of funding that is based on the time they would be contributing. To receive compensation they would also need to provide contribution log evidence to prove that they had executed work over the previous month so they become eligible for future months. The only thing the contributor could easily do is lie about how much work they did in the month by potentially using other people's efforts masked as their own or exaggerating how long it took to complete their own work. Once caught the contributor would be unlikely to be selected in the funding process again and could also damage their prospects in other ecosystems across the industry.
* **Execution verification** - Contributors could lie about their contribution efforts to attempt to get compensated for work they didn’t do. If this work can be proven to be someone else’s efforts the contributor would have a high risk of causing long term reputation damage that they can’t remove.
* **Malicious voters** - If a handful of voters were trying to benefit themselves or other people they know through their voting behaviour they would struggle to get more funding than they are able to allocate to the individuals that they are trying to support. Those individuals would only be able to request compensation to pay for their salaries.
* **Voting outcomes** - There is a much lower risk of contribution efforts not being directed to novel research and innovation as contributors would not be prevented from identifying and working on any of these areas themself. Contributors are who would be responsible for selecting the most impactful opportunities to work on. Attaching the incentive to contributors helps to remove the need for the wider community to approve every idea that will get executed and gives more autonomy to the contributors who should be well informed enough to judge what areas are most worth spending their time on to try and generate impact for the ecosystem.
**Very high contribution flexibility (Score - 5)**
* **Changing an existing idea** - A contributor could change an idea as many times as they like as they are being paid for their contribution time. There is no added complexity for contributors to change how an existing idea gets executed.
* **Contributing to a different idea** - A contributor could redirect their efforts for any amount of time to other ideas in the ecosystem if they believe another idea will generate more impact than the current one they are working on. There is no added complexity for contributors to start contributing towards a different idea.
* **Contributing to a different priority** - Same as the above. There is no added complexity for contributors to start contributing towards a different priority.
* **Incentive complexities** - Contributors wouldn't need to come to agreement with any other initiative or spend time considering how much they should be compensated as they will already be allocated the amount the requested for helping with execution efforts.
* **Moderation complexity** - No approval process is needed for contributors to change an existing idea or when they allocate their contribution efforts towards a different idea or priority.
**High income stability (Score - 4)**
* **Likelihood of future income** - If contributors are selected based of their merits, such as their contribution history and professional background, the chances of being selected for future compensation could be quite high for well performing contributors. Providing contributors are able to provide evidence about their contributions made the chance that high performers get selected again should increase over time as the ecosystems ability to measure contributors performance and impact generated is improved.
* **Compensation accuracy** - Contributors would be paid for their time spent executing ideas that help to execute the funded idea. The compensation would be agreed ahead of time and the contributor could expect high stability over the income they receive whilst they are contributing to the ecosystem.
**Total score = 28 / 30**
# Idea cost approaches
Comparing the different idea cost approaches that could be used for approving and funding idea related costs
There are a number of idea related costs that can require funding from the funding process. These costs could be handled in a number of different ways.
Some example idea related costs include:
* Hardware
* Production costs
* Real estate
* Rent or lease payments
* Software subscriptions
* Backup & data storage
* Office supplies
* Insurance
* Security services
* Education & training
## Approaches for handling idea costs
The idea cost approaches for comparison include:
* [Costs attached to contributors](/approaches/incentive-approaches/idea-cost-approaches/costs-attached-to-contributors) - The idea related costs are attached to the contributor proposals which request compensation.
* [Costs attached to ideas](/approaches/incentive-approaches/idea-cost-approaches/costs-attached-to-ideas) - The idea related costs are attached to idea proposals where all costs are budgeted costs are covered in a single submission.
* [Independent idea costs process](/approaches/incentive-approaches/idea-cost-approaches/independent-idea-costs-process) - The idea related costs are handled in an independent approval process. This process could occur in parallel to idea and contributor decisions.
To compare these idea cost approaches a number of [factors have been considered](/approaches/incentive-approaches/idea-cost-approaches/idea-cost-factors-for-consideration) and then applied to each approach to try and determine the strengths and weaknesses of each one.
**Key takeaways**
* **Attaching costs to contributors is often unsuitable** - Many of the idea related costs could be integrated into the costs included in a contributor proposals budget such as for some hardware, rent or lease payments, software subscriptions, backup & data storage, office supplies, insurance, utilities, security services and education & training. However this approach could be more problematic when there are larger ideas with group related costs such as around production, real estate, certain software subscriptions and security services. These situations would likely need the costs to be handled and approved separately. To adopt an approach of attaching certain costs to contributor proposals a funding process could introduce a policy to prevent the other larger type of costs from being an option if these type of costs were not a need for the ecosystem.
* **Every incentive approach can benefit from an independent idea costs process** - An ecosystem can benefit from an independent idea costs process even when the incentives are attached at the point of idea selection. Using a separate process helps to reduce complexities around cost changes and budget planning whilst also giving the voters more expressiveness in how they can indicate their exact preferences. This is ideal for situations where a group of voters agree with the importance of an idea but disagree with one of the idea related costs that has been suggested. Using an independent process enables voters to quickly indicate their preferences and can help with speeding up the process of encouraging further information when it is needed to better justify certain idea costs that have been suggested.
**Idea cost approach analysis**
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[Idea cost factors for consideration](/approaches/incentive-approaches/idea-cost-approaches/idea-cost-factors-for-consideration)
{% endcontent-ref %}
{% content-ref url="/pages/CnUKHJrVr9GYh58AHMu0" %}
[Costs attached to contributors](/approaches/incentive-approaches/idea-cost-approaches/costs-attached-to-contributors)
{% endcontent-ref %}
{% content-ref url="/pages/jeZc8hyVa0UREuBCEZBb" %}
[Costs attached to ideas](/approaches/incentive-approaches/idea-cost-approaches/costs-attached-to-ideas)
{% endcontent-ref %}
{% content-ref url="/pages/BTsELLqiOEjpwNMF21KY" %}
[Independent idea costs process](/approaches/incentive-approaches/idea-cost-approaches/independent-idea-costs-process)
{% endcontent-ref %}
## Considerations for **adopting an independent idea costs process**
**Increasing speed of idea submissions and feedback**
A separate process for approving idea related costs can help with making it easier to submit and receive feedback for ideas in an ecosystem. An idea could still have its different costs planned out at the beginning but the difference is the actual request for that cost could be delayed. This is useful for situations where it is difficult to achieve an accurate cost at that time or when the idea cost does not need to be paid for in the short term. Removing this complexity can increase the rate in which feedback is given to new ideas as they can more easily be suggested and approved by a community without being fully formed.
**Handles changing costs**
Costs can increase or decrease during different points of an ideas execution. New costs can emerge that were not previously needed due to a change of execution outcome, other costs could potentially be removed due to a change in how the idea is actually being executed. An independent idea cost approval process would enable requests for funding these changes in idea costs at the point that the change occurs. Any evidence required to justify that change would be added to that request. Without a separate process the existing ideas would need to make another idea based proposal using the same process they used to get community support for their original idea to receive any future funding.
**Flexible request timing**
Idea related costs could still be requested immediately at the point of an ideas initial submission with a separate approval process. This can be preferred when contributors are accurately able to calculate and present the costs ahead of time. Alternatively if the idea requires some initial execution efforts before the contributors will know the accurate costs the contributors involved in the execution would benefit from being able to request those costs at that point in which they become more well informed. The contributors could still provide estimates about the costs upfront however the actual commitment to the request only happens at the point of the costs are more accurately known. This flexibility allows for ideas to be planned as much as they can be when they get suggested but then still enables them to evolve and be further planned over time as further experience and the right information becomes available during the execution of an idea.
## Other factors to consider
**Incentive approach considerations**
Attaching idea costs to a single idea suggestion doesn’t change the fact that the costs involved for an idea could change over time or have new costs that emerge. Due to this, any incentive approach can benefit from having an independent cost process so that proposers are able to update these requests and make new ones as their idea evolves over time. If there was no separate process for approving idea related costs the proposer would need to submit a new proposal with the similar information as before to then be considered before receiving funding. If the proposer was allowed to change an idea proposal and idea costs in any way that change the compensation being disbursed it would still require voter approval, if it didn’t then this ability to change what funding a proposer receives could easily be exploited. An ecosystem could prefer to take a rigid approach to cost planning and decide to not support any changing circumstances. However this could easily lead to more conflicts and friction due to under or over estimations of costs. Preventing any changes could mean that projects fail or stagnate during their execution due to a lack of ability to respond to changing factors and environments that were outside of their control.
**Budgeting approach considerations**
Treasuries have a finite amount of assets to disburse. When disbursing these assets an ecosystem may want to limit the amount of assets that get used for idea related costs against what gets used for contribution efforts. For instance, it could be detrimental to have many ideas get approved that have large idea related costs attached to them if that meant that there was little funding left to pay for contribution efforts that help with executing those ideas. If a funding process had a fixed release of funds per round or for a period of time they could decide to add a cap to the amount of available budget that is used for idea related costs. This would be easier to track with an independent idea costs process as all costs going through that process would be tagged as idea related costs and the other incentives would be tagged as contribution effort incentives. A percentage split approach between idea costs and contributor costs could be adopted. Budget caps could also work for preventing idea costs from exceeding specific values as a way to safeguard the funding process. Budget caps could be useful in earlier stages of development for treasuries whilst they are still testing and experimenting with numerous funding approaches. Percentage split or budget cap based approaches could be restrictive for some ideas so these approaches may not be suitable for some ecosystems.
**Contributor fraud and corruption considerations**
Risks around contributor fraud and corruption are important and require consideration regardless of how idea costs are handled. Contributors involved in the execution of ideas could become corrupted or malicious during execution. If those contributors start requesting for idea costs to execute their idea this could be done so in bad faith where their real intention is to take the funds for themselves. One approach that could be adopted to help prevent this, especially for larger payments, is to adopt an escrow contract that has a number of verification and moderation steps to help to slow down and check the funding of larger cost requests. These checks could help with identifying the received address and owner, verifying their ownership or control of the address, the value of any assets involved and exactly how any assets involved are being moved or changed in terms of ownership.
# Idea cost factors for consideration
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Idea cost budgeting complexity**
* **Description** - Contributors will need to plan and justify the costs that are involved with the execution of an idea that are outside of the contribution effort costs.
* **Importance score** - 5, Very important. When and how idea costs get selected and distributed can have a big influence on the budgeting complexity that contributors need to handle. The approach could also result in increasing administrative burden when submission efforts and governance decisions might need to be duplicated.
* **Scoring questions** - How much idea cost planning needs to be done upfront? How complex could it be for a contributor to determine accurate costings?
* **Scoring** - Low complexity is good (Score - 5). High complexity is bad (Score - 1).
**Idea cost change complexity**
* **Description** - Where and when idea related costs can be requested can influence how complex it is for adding new idea costs or making changes to existing costs.
* **Importance score** - 5, Very important. During the execution of ideas a number of new costs could emerge or changes to existing ones due to new information and changing factors and environments.
* **Scoring questions** - How can new costs be requested from the funding process? How can existing costs be amended or returned? What effort does a contributor need to make future requests?
* **Scoring** - Low complexity is good (Score - 5). High complexity is bad (Score - 1).
**Voter expressiveness**
* **Description** - Where idea costs get handled will determine how expressive the governance process is for enabling voters to share their exact preferences in their decisions.
* **Importance score** - 5, Fairly important. A voter may fully endorse an idea and support its execution but may disapprove of the idea related costs that have been budgeted for. Enabling voters to express this helps to ensure ideas costs can be reconsidered and improved when other options or approaches for handling a certain cost might be more suitable.
* **Scoring questions** - How easy is it for voters to express their exact preferences when it comes to supporting or rejecting the idea costs being requested? Can voters support an idea and not support the costs involved in that idea?
* **Scoring** - High expressiveness is good (Score - 5). Low expressiveness is bad (Score - 1).
# Costs attached to contributors
**Overview**
Attaching idea costs to contributor proposals means that contributors would need to account for any idea related costs when they are requesting their own compensation. This could be achieved by either just increasing their requested amount to include a buffer to handle these costs or it could be more exact by requesting the exact amount needed plus the compensation they are requesting.
**High idea cost budgeting complexity (Score - 2)**
The obvious problem with attaching idea costs to contributors is it is not suitable for the larger idea related costs such as real estate, production costs, office rent or lease payments or the larger software subscriptions or security service agreements. This approach would only truly work in situations where these types of larger shared costs are not accepted in the funding process and instead the ecosystem is focussed on compensating peoples contribution efforts. Some idea related costs could be suitable to attach to the contributors compensation requests when they are more relevant to the contributor such as smaller pieces of hardware or low cost insurance, software subscriptions, education & training and office supplies. Overall this approach can be fairly limiting in what types of idea costs it can easily handle.
**Very high idea cost change complexity (Score - 1)**
Without a separate process for handling idea costs the contributor wouldn’t be able to request further funds unless they could amend their original contributor compensation request. This would require approval and if they are only changing the idea related costs then this would start to look more like a separate idea costs process. Without this process a contributor would need to request for those funds in a future contributor funding process.
**Very low voter expressiveness (Score - 1)**
Voters would not easily be able to express their exact preferences about what idea costs should and shouldn’t be included unless this was handled separately.
**Total score = 4 / 15**
# Costs attached to ideas
**Overview**
Keeping idea costs attached to idea suggestions means that these costs would need to be requested in the idea proposal itself. Each of the idea costs would be accounted for and included in the same approval as the idea itself.
**Moderate idea cost budgeting complexity (Score - 3)**
Each of the idea related costs can be budgeted for in the idea proposal. This can be fine for some of the costs that an idea might have however some costs could change over time or be difficult to calculate ahead of time without further execution effort. This means it can be moderately difficult for contributors to accurately budget for these idea costs ahead of time.
**Moderate idea cost change complexity (Score - 3)**
To change the existing idea related costs or to add new ones a contributor either needs to estimate all of these costs upfront in the initial idea proposal or withhold those requests entirely until a future repeated idea proposal. Creating a future idea proposal for this purpose adds extra complexity for the voters who then need to approve multiple similar instances of the same idea and this also increases the effort for contributors to handle these repeated submissions.
**Low voter expressiveness (Score - 2)**
The grouped costs could be easily listed out when the costs are directly attached to the idea however there is still little ability for the voter to properly express their preference in a vote and can only do this by sharing their feedback and opinions on the idea itself. The voters either have to accept everything or nothing.
**Total score = 8 / 15**
# Independent idea costs process
**Overview**
An independent idea costs process means that idea related costs are handled separately from any voting that supports or rejects any suggested ideas. An already supported idea could submit further idea related costs for consideration to the community. A separate idea cost process could function in a multitude of ways depending on the requirements of the ecosystem. As one example some funding processes could decide to automatically include and approve idea related costs when the request value being requested is small. Those ecosystems could then adopt an independent approval process for situations where those costs exceed a certain value.
**Very low idea cost budgeting complexity (Score - 5)**
Idea costs don’t need to be fully planned upfront. An initial idea suggestion could focus on what they are able to plan and estimate at the time of submission. When other estimated costs can be more accurately determined those requests could be submitted at the point in which more accurate justifications and evidence can be provided. This approach helps to increase the timeliness and accuracy of any idea cost requests.
**Low idea cost change complexity (Score - 4)**
At any point the contributors involved in an idea could request a change to the costs required for any part of an idea. A separate idea cost process could handle these requests in any way that makes sense for the ecosystem. For instance the purpose, usage and beneficiary details could all be part of the idea cost request. The policies for how idea cost funding can be requested and updated could be very different across each ecosystem. The main concern with having an independent process is if this process is used often it could increase the overall complexity to handle idea cost changes by having too much flexibility. An ecosystem could obviously put limits on how often a proposer could request for changes if this flexibility in handling idea costs became a growing problem.
**Very high voter expressiveness (Score - 5)**
Voters would be able to indicate their exact preferences on any of the requested funds for idea related costs. The ecosystem could also decide that the community only needs to be involved in idea costs that go above a certain amount being requested. Anything below that could be automatically approved and determined by the selected contributors. The funding could come from a set budget that is made available for idea costs.
**Total score = 14 / 15**
# Proposal submission incentives
Considerations for how incentives could be used to encourage the submission of proposals that are beneficial to the funding process
The funding process requires information to be submitted by the community so decisions can be made regarding what priorities are the most important, which ideas look the most promising and which contributors should be selected to execute those ideas. Incentives could be used to encourage the submission of this information. Alternatively contribution incentives could be used to encourage the submission of different proposals and information. The submission approaches being considered can be found here:
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[Proposal submission incentive approaches](/incentives/proposal-submission-incentive-approaches)
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## Priority
Incentives could be used to help encourage people to submit priorities that help with identifying what opportunities or problems exist in an ecosystem. A submission incentive could also help with encouraging proposers to add other existing information that provides evidence towards why a priority is actually important. An incentive could also be used to reward voters for participating in the selection of important priorities for the ecosystem.
**Potential incentive approaches**
* **Selection incentive** - A selection incentive could be effective for encouraging a diversity of contribution by compensating the proposers who created priorities that were selected by the wider community. This could help increase the incentive for anyone in the community to submit priorities as they could be compensated for doing so if their priorities are selected by the community. This gives proposers more reason to allocate a sufficient amount of time in writing a more thorough submission about a priority with the relevant supporting evidence.
* **No incentive** - Community set priorities can have a large influence on how treasury assets are allocated and used to generate impact. Due to this there is a natural incentive for community members to express their opinions on what priorities they believe are most important due to the possibility that those suggestions get selected and lead to generating impactful changes that benefit them and the wider community. A no incentive approach might also work because the submission of priorities does not need to be a complex process. There might be a need for ongoing maintenance of the information attached to a priority but this incentive does not need to be handled at the submission stage. Another reason a no incentive approach may be suitable is because the complexity of the average priority could be relatively low for smaller ecosystems or ecosystems that have a more focussed and narrow set of longer term goals. The more complex that priorities become, the more important it will be for that community to consider how incentives could help compensate for the increasing amount of contribution effort required for people to participate.
## Ideas
Incentives could be used to help encourage people to submit ideas that if executed help to address some of the existing priorities in the ecosystem. An incentive for idea proposals will need to consider how it encourages people to add all of the relevant information for voters to be well informed on whether an idea is a promising potential solution or not. Incentives could be used to reward voters for reading and voting on the selection of the most promising ideas.
**Potential incentive approaches**
* **No incentive** - Incentives do not need to be attached to the submission process for ideas if there is already an incentive available for compensating the community selected contributors. Contributors who get selected and compensated to help with the execution of ideas would already have the incentive to generate impact by submitting promising ideas that they could work on and executing those ideas. Creating a good idea helps to demonstrate to voters that contributors are well informed about a given topic area and provide evidence that these contributors are suitable for being selected for future compensation. The main potential issue with using no incentives is it could result in a smaller amount of participation from the wider community as they wouldn’t be compensated for suggesting ideas unless they were also becoming a contributor that gets compensated to execute those ideas. Community members would have no incentive to help with the idea submission process beyond the non-financial incentives that exist such as wanting to suggest and see positive change in the ecosystem.
* **Selection incentive** - The selection of ideas could result in compensation for the authors that submitted that idea. This incentive could result in separating the responsibility of executing an idea with submitting an idea. Under this approach there could be a higher risk that an idea does not have the contributors required to execute an idea as intended if this has not been verified beforehand. However a benefit to providing some form of compensation for idea selection is it could help to encourage a wider diversity of ideas being submitted by the wider community and not just by those who are executing the ideas. If the contributors who are executing the ideas are already submitting high quality ideas this added selection incentive might not be necessary.
## Contributors
Contributor proposal submissions can be seen as something similar to the submission of a CV or job application. Selected contributors will usually be paid for their contribution efforts to help with the execution of different ideas. This creates a natural incentive for people to submit proposals with any information about themselves so that they have the opportunity to be selected and become a compensated contributor. Incentives could potentially be used to help support a referral process to further attract the submission of contributor proposals. Incentives could also be used to reward voters that participate in the selection process.
**Potential incentive approaches**
* **No incentive** - There is a natural incentive for contributors to submit their professional information and be considered as a potential candidate to help with the execution of ideas. Having no incentives for the submission process could be the simplest and most suitable option.
* **Selection incentive** - A selection incentive may be useful for situations where contributors are referred by other people to join the ecosystem as a potential contributor. There are risks that this process is gamed by people who are only looking to extract this compensation. This risk would be more problematic in situations where contributors are not identity checked as this referral incentive could then be more easily and repeatedly abused.
# Maintenance of information incentives
Considerations for how incentives could be help with maintaining important information across the funding process
Information that is submitted through a funding process will often need to be maintained and updated as new information emerges or changes occur. Incentives could be used to encourage contributors to maintain this information over time. Alternatively contribution incentives could be used to handle the maintenance of funding information. The contribution incentive approaches that could also be used for maintaining information are covered here:
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[Contribution incentive approaches](/incentives/contribution-incentive-approaches)
{% endcontent-ref %}
## Priorities
Priorities will often change over time as new information or changing factors and environments influence the current progress and importance of the existing priorities. Incentives can help with handling how priorities get maintained over time after they are submitted and selected through voting. Incentives could help with encouraging people to provide feedback and discussion around any of the existing priorities. Feedback could mean providing supporting or counter arguments to the points made in an existing priority. This feedback could also include further supporting evidence to better justify their feedback. Keeping priorities and any related information up to date will be an important part of keeping the voters informed on the progress and changing importance of existing priorities. The more accurate and reliable prioritisation is the more accurate an ecosystem can become in allocating treasury assets towards initiatives that address the most important priorities.
**Potential incentive approaches**
* **Time incentives** - Paying contributors to maintain and update priorities over time could be a simple and effective way to keep priority information up to date. Full time based compensation for this work could be an effective approach for this responsibility as the contributors involved in supporting the priority process would have the capacity to consider how any new information relates to any of the existing priorities. Contributors would have more capacity to moderate the information that gets attached to existing priorities which is important as otherwise priorities would become difficult to read and digest if too much information was added. This incentive approach could also help with ensuring priorities meet certain quality thresholds if this verification was deemed necessary.
* **Performance incentives** - If contributors were very actively involved in maintaining a priority process they would likely become much more informed of the different pieces of information that are emerging and flowing through the ecosystem. The better that these contributors are able to identify and understand this diversity of information the more effectively they should be able to highlight and apply that information to any of the existing priorities. Rewarding contributors who most effectively contribute towards achieving these outcomes could be an effective way to align the incentives for encouraging contributors to become increasingly well informed when contributing to the prioritisation process if this results in them increasing the likelihood they receive a larger amount of compensation.
* **Task incentives** - Contributors could be rewarded for every time they suggest additions or changes to the information that is attached to an existing priority. The benefit of this type of approach is it would add a simple incentive for contributors to keep a priority up to date with new information and could help to distribute that incentive amongst many different contributors. The main concern with this approach is that priorities can benefit from having the most highly relevant and concise information being added to inform the community on what is happening for each priority. Adding every piece of information that might be somewhat relevant could easily result in bloating the priority process. A task incentive could increase the risk that many contributors suggest many different pieces of information just to receive the compensation, rather than being very deliberate and considerate when adding this information.
* **No incentives** - If the priorities being submitted are less complex and don’t need updating over time with new information then adopting an approach that doesn’t add any incentives could be a suitable option for some ecosystems. No incentives is also a suitable approach if this incentive is already handled with other contribution incentives. If priorities do benefit from being updated with up to date information then there could be a risk that voters would become less well informed when making decisions if there is no incentive to increase the speed the priorities are kept up to date.
## Ideas
Selected ideas that get executed will create new information about the progress and importance of those ideas over time. This information could be made more readily available to the voters for improving future decision making. Further evidence from different knowledge sources could also become available over time which provide evidence showing why one certain solution approach might be more suitable than another. Proposers may also want to add new information to justify why an existing idea needs to be changed and improved so it can create more impact for the ecosystem. Considerations can be made towards how incentives could help keep idea information up to date. The incentives could be handled with contribution incentives if contributors who are selected to work on an idea become also responsible for keeping idea information up to date. Alternatively added incentives could be used to encourage anyone in a community to maintain and improve the information that is attached to ideas. Progress and completion reporting, community feedback and discussion and any justifications for changing an existing idea could be some of the most common types of information that is updated and maintained over time.
**Potential incentive approaches**
* **No incentives** - Incentives aren’t necessarily required for keeping an idea up to date with relevant information such as progress or completion reports, execution approach or outcome changes or providing feedback and discussion around the impact being generated. The incentive to keep an idea up to date with the right information could be handled with contribution incentives where contributors who are selected to be compensated to help with the execution of ideas could also be responsible for keeping those ideas up to date. This could be a simple and suitable option for keeping the incentive design simple.
* **Performance incentives** - Compensation could be rewarded to contributors that are highly effective at keeping an idea up to date with relevant information. This could be effective to help with quickly updating an ideas information so that the community is always well informed.
* **Task incentives** - An incentive could be made available for each time that information gets added to an idea. This could help with incentivising a wider range of community members to keep an idea up to date rather than just the contributors who are executing an idea. The risk with this approach is that the incentives could lead to irrelevant information being added that bloats the funding process.
* **Time incentives** - Incentives could be used to compensate contributors for their time to help with keeping the information up to date about an idea. This could be useful for ensuring contributors are being very deliberate about the amount of time a contributor should ideally take when keeping an idea up to date and the information that they decide to add. This time incentive could be handled with contribution incentives that help with handling the execution of ideas, creating a separate time based incentive just for updating idea information could be adding unnecessary complexity.
## Contributors
Selected contributors that start executing different ideas will generate new information about themselves that builds up over time such as their contribution history and profile information. Monthly contribution reports are one piece of information that could be attached to a contributor's profile to keep voters informed about the exact contributions they have made. There is a natural incentive for contributors to keep this information up to date as it can directly influence how successful they are in future votes where the community selects the most promising contributors.
**Potential incentive approaches**
* **No incentives** - Contributors have a natural incentive to keep their information up to date to maximise their chances of being selected and compensated for future execution efforts. There isn’t a large amount of information required to keep contributors profile up to date which helps to support an approach that doesn’t add any incentives for this part of the funding process.
* **Task incentives** - Task incentives could be suitable if it made sense to have a wider amount of the community being active in updating contributor information instead of just the contributors themselves. Contributors could also receive an incentive for updating this information but this might not make sense if they are already receiving compensation when they are selected for making contribution efforts. A task incentive could potentially be useful for moderating the information that is being added by contributors by the community.
* **Time incentives** - The accuracy and correctness of the information being added to a contributor's profile could be moderated and verified by people who are paid to moderate the information. This could be a necessary way to better identify when contributors have been lying or exaggerating about their background, education or contributions.
# Contribution verification approaches
Comparing the different contribution verification approaches that could be used for checking the execution outputs of different individuals and teams
Contribution verification is used to verify the contribution efforts of contributors. Contributors would submit evidence about their contribution efforts and the community could then check and verify those outputs. Funding can benefit from having a verification process to reduce the risk of bad actors trying to misuse or steal community funds. Verification can also help future decision making if a community is more easily able to determine if the execution outputs made by different individuals and teams is sufficient for the compensation they are receiving.
The importance of recording, measuring and verifying contributions has been covered in more detail separately:
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[Contribution verification](/contributions/contribution-verification)
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## Approaches for verifying contribution outputs
There are three main approaches that have been compared to consider how contributors could submit contribution logs to showcase their recent efforts:
* [**Task milestone based contribution logs**](/approaches/contribution-verification-approaches/task-milestone-based-contribution-logs) - A contribution log records the completion of the milestone tasks involved in a project.
* [**Project time based contribution logs**](/approaches/contribution-verification-approaches/project-time-based-contribution-logs) **-** A contribution log records a projects execution outputs after a set period of time.
* [**Individual time based contribution logs**](/approaches/contribution-verification-approaches/individual-time-based-contribution-logs) - A contribution log records an individuals execution outputs after a set period of time.
To compare these contribution verification approaches a number of [factors have been considered](/approaches/contribution-verification-approaches/contribution-verification-factors-for-consideration) and then applied to each approach to try and determine the strengths and weaknesses of each one.
**Key takeaways**
* **Automation of submission and verification** - The time it takes to submit contribution logs and verify the outputs should reduce over time due to new tools and processes that can be developed. This results in these two factors becoming increasingly less important over time due to the fact that much of the data could be added and verified automatically with the right systems in place. This means that some of the main important factors are around contribution measurability, accuracy of the information provided and reducing the ongoing game theory risks. All of the suggested approaches benefit from automating the submission and verification of different contribution outputs. Code commits or document submissions would be some examples areas that can be more easily recorded and verified. Improved toolings for recording contribution efforts will make it simpler for contributors to automatically log their contribution efforts and for the community to have more confidence in knowing who was responsible for different contributions.
* **Individual time based contribution logs approach is preferred** - Out of these three approaches the most effective approach for making it easy and scalable for community moderators to handle verification is the individual time based contribution logs approach. Individual contribution logs give much more accuracy and in depth information that can improve contributors ability to build their reputation, improve voter decision making and accuracy of performance measurement.
* **Individual time based contribution logs also produce project time based logs and task milestone based logs** - Contributors can indicate which ideas they are working on when making submissions in their contribution log. They could also indicate which phase or milestone of the idea their contributions are relevant to. If this information is also added the individual contribution logs are able to be used in aggregation to generate project time based contribution logs and task milestone based contribution logs. This makes individual contribution logs much more composable and useful than the other two verification approaches due to how they can be used.
**Contribution verification approaches analysis**
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[Contribution verification factors for consideration](/approaches/contribution-verification-approaches/contribution-verification-factors-for-consideration)
{% endcontent-ref %}
{% content-ref url="/pages/uS8UOpk3XXl5yHululF1" %}
[Task milestone based contribution logs](/approaches/contribution-verification-approaches/task-milestone-based-contribution-logs)
{% endcontent-ref %}
{% content-ref url="/pages/3PZzotiEWQGGLP05GTbK" %}
[Project time based contribution logs](/approaches/contribution-verification-approaches/project-time-based-contribution-logs)
{% endcontent-ref %}
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[Individual time based contribution logs](/approaches/contribution-verification-approaches/individual-time-based-contribution-logs)
{% endcontent-ref %}
# Contribution verification factors for consideration
Listing the different verification factors that will be considered for each contribution verification approach
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Contribution measurability**
* **Description** - Contribution measurability is concerned with how easy it is to quantify and compare the contributions outputs that get submitted.
* **Maximum score** - 5, Very important. Measurability is very important for making it easier to compare the contribution efforts of different contributors to more easily determine who the best and worst performers are, whether contribution outputs are improving or not over time and for making any comparisons with other ecosystems.
* **Scoring questions** - How measurable are the contribution logs created through each approach? Is the time period the same each time? Is the scope of work fairly consistent?
* **Scoring** - Higher measurability is good (Score - 5). Lower measurability is bad (Score - 1).
**Contribution log accuracy**
* **Description** - Accuracy in contribution logs means it should be clear who is responsible for each of the contributions made when executing any given idea.
* **Maximum score** - 5, Very important. This is highly valuable for a growing ecosystem where many moving parts could be being worked on at any point in time. Making it clear who was responsible for working on a given area to the rest of the community makes it easier for people to be aware of this and then also direct questions to the relevant people immediately without any intermediary steps.
* **Scoring questions** - How easily can a piece of contribution effort be tracked back to an individual who worked on that area? How accurate is a contribution log submission likely to be in covering this?
* **Scoring** - Higher contribution log accuracy is good (Score - 5). Lower contribution log accuracy is bad (Score - 1).
**Reputation building usability**
* **Description** - Contribution logs can help with building up an individual or team's reputation over time based on the quality of their contributions. Making it easier for people to build reputation in an ecosystem can help top performers with being identified and selected in future funding decisions.
* **Maximum score** - 5, Very important. Reputation building can be a powerful approach for identifying and rewarding top performers in an ecosystem. Ecosystems should benefit from being able to retain the best performing talent by enabling them to build up and showcase their reputation.
* **Scoring questions** - How can a team and individual build up a reputation using the contribution recording approach? What value do the contribution logs have for reputation building when contributors start to move around and execute different ideas with different teams?
* **Scoring** - Higher usability is good (Score - 5). Lower usability is bad (Score - 1).
**Performance measurement usability**
* **Description** - Measuring the performance of contributors can help with determining the full value of someone's contribution efforts. Performance measurement can help to align the incentives with the contributors who have made the most effort and been the most performant at executing different ideas.
* **Maximum score** - 5, Very important. Performance measurement will be an important part of making sure that each contributor's compensation is fair and reasonable given the facts about their performance. If the incentives aren’t well aligned with rewarding top performers these actors could look towards other ecosystems that are more effective at identifying and rewarding the value they bring to the ecosystem.
* **Scoring questions** - How can the performance of an individual contributor and team be better understood and measured using this contribution log approach? How could those contribution logs be used to accurately measure their performance?
* **Scoring** - Higher usability is good (Score - 5). Lower usability is bad (Score - 1).
**Future voting usability**
* **Description** - Contribution logs could become an increasingly useful source of information for voters to become more well informed on which contributors and teams have been the most performant and impactful in the ecosystem.
* **Maximum score** - 5, Very important. Ecosystems will benefit from being able to easily identify and retain the most performant and impactful talent. Informative contribution logs could represent an important information source for voters to identify and select this talent in future funding decisions.
* **Scoring questions** - How could voters use the contribution logs to make future voting decisions? Does the information source become more insightful and useful over time?
* **Scoring** - Higher usability is good (Score - 5). Lower usability is bad (Score - 1).
**Game theory risks**
* **Description** - How contribution outputs are recorded and verified by a community will influence how easy it is for bad actors to try and game that system.
* **Maximum score** - 5, Very important. Bad actors can try to abuse any system that makes it easier enough for them to extract a larger amount of incentive than they should be receiving.
* **Scoring questions** - How could contributors attempt to increase the amount of incentive they are receiving for doing less work? How could contributors lie or be deceitful about the amount of work they are actually doing?
* **Scoring** - Lower risk is good (Score - 5). Higher risk is bad (Score - 1).
**Verification time required**
* **Description** - Verification time is concerned with how long it would take for a community moderator to verify that contribution log submissions are correct.
* **Maximum score** - 3, Moderately important. Reducing the time it takes to verify a submission will help with reducing operational costs of moderating the funding process. The verification of contributions can be increasingly automated over time such as with code commits, designs created or documents written. The importance of verification time should reduce over time as more tools and processes are created and refined.
* **Scoring questions** - How long would it take on average for a moderator to verify the contribution logs submitted by contributors?
* **Scoring** - Lower verification time required is good (Score - 5). Higher verification time required is bad (Score - 1).
**Submission time required**
* **Description** - Contributors will need to allocate a certain amount of time to record their contribution efforts so they can be submitted and verified by the community.
* **Maximum score** - 3, Moderately important. The time it takes to submit the contribution logs needs to be reduced where possible. Over a longer time period there are a number of areas that could be automatically gathered such as with code commits, written work and other forms of digitally submitted work. The importance of submission effort should reduce over time as these new tools and processes get developed.
* **Scoring questions** - How long would it take on average for a contributor to make a submission? What total time would it take a group of contributors who are working on executing an idea?
* **Scoring** - Lower submission time required is good (Score - 5). Higher submission time required is bad (Score - 1).
# Task milestone based contribution logs
Recording contribution logs through the completion of milestone tasks involved in a project
**Overview**
Task milestone based contribution logs mean that a project has been broken down into milestones. Each milestone would have a set of tasks that need to be completed within that milestone. Contributors would submit evidence of any execution efforts when they have completed a milestone.
**Very low contribution measurability (Score - 1)**
The time taken to complete each milestone is different as it is defined by the contributors who are involved in the initiative. The amount of contributors involved in each milestone could be different. This approach is the least measurable and most difficult to compare with others as there is much higher variability in what can be submitted. A lot more work has to be done in isolation on a specific team's execution to work out whether they have in fact made fair and reasonable contribution efforts and whether they have been performant or not.
**Very low contribution log accuracy (Score - 1)**
Completed milestones can make it harder to understand exactly who has executed what outputs and exactly how long they spent on the tasks involved. Task milestones could include individual contribution information which would help to make it easier to compare individual performance. However this would also be the time periods involved in that execution. If both individual contributions and time periods are added then this ends up becoming an individual time based approach as well as a task milestone approach! Logs providing evidence for completion of task milestones by themselves do not provide much contribution accuracy.
**Low reputation building usability (Score - 2)**
Contribution logs would cover the milestones that a team completes. This contribution log structure makes it more difficult to create long term reputation as the milestones for each idea are different in scope and size, making it more difficult to make comparisons between different teams and make any historical comparisons. Limited measurability makes it more difficult to have confidence that the team is performing well and improving over time without community members doing a sufficient amount of observation themselves. The other issue is that teams can also change and introduce new people and lose others. Teams change naturally over time so this factor reduces the confidence in this structure of contribution logs as an approach for reputation building. Milestone based contribution logs would be more useful for reputation building in the situations where the teams stayed the same and ideas being executed were similar to previously executed ideas. The more that these teams and ideas change over time the less valuable these contribution logs are for building reputation.
**Very low performance measurement usability (Score - 1)**
For comparing different teams performances there is a complexity in comparing the contribution efforts of these teams when milestones based contribution logs are used. This is due to the differences in the milestones and the amount of work involved. The only easy way to understand whether a team is performing is to review how effectively they complete their milestones against other similar milestones. Ecosystems could also review how long they predicted the milestone would take against how long it actually took to complete. Teams can change over time and individuals could each have differing levels of performance within a team. Milestone based contribution logs don’t help with determining how performant each team member has been. There could be an increased difficulty in determining whether a team change was a positive or negative outcome for improving the performance of that team without knowing how performant each individual was.
**Low future voting usability (Score - 2)**
Milestone based contribution logs would be more useful when the team stays the same and the ideas they are executing are similar. If the team or ideas change over time there is a reduced amount of relevance for the contribution logs being a good indicator on whether the team will be effective at executing a more recently suggested idea. As teams and ideas change over time the value of previous contribution logs for voting could be limited. This factor can make the contribution logs less useful for ongoing funding decisions.
**Very high game theory risks (Score - 1)**
Contributors can manipulate and exaggerate both the time it takes to complete any given task or the scope of what is being executed. Giving contributors the full ability to set the scope and time period maximises their ability to manipulate these inputs. The fact that each milestone will be different from the other milestones and with any of the other projects only increases this ability to manipulate these inputs in a way that would benefit the contributors. Maximising flexibility for this specific area in funding means maximising the difficulty for the community to determine what is fair and reasonable across all of the unique milestones that get submitted.
**Very low verification time required (Score - 3)**
Moderators would only need to verify the milestones of each project which could result in verification checks being needed less than once a month. This approach would likely require the least amount of verification time due to the infrequency of the milestone submissions. The average time required to verify submissions for any verification approach should also reduce over time as the tools and processes improve.
**Very low submission effort (Score - 3)**
Task based milestone contribution submissions need to confirm that a predefined milestone has been completed. All that is needed for a contribution log submission is the evidence showing that each task within a milestone has actually been completed.
**Total score = 13 / 36**
# Project time based contribution logs
Recording contribution logs for a projects execution outputs after a set period of time
**Overview**
Project time based contribution logs are when contribution outputs are submitted together in a single project submission to capture what has happened over a certain time period such as every month. This could be for addressing an existing priority or executing an idea.
**Low contribution measurability (Score - 2)**
This approach does have time consistency as it is being recorded every month. However what it lacks is scope consistency. The number of people involved in each initiative can be different meaning it is now much harder to compare the submissions from different projects as the scopes involved in each submission can be vastly different. This now makes it harder to work out the best and worst performers across the ecosystem and also makes it more difficult to understand whether the ecosystem is improving in its contribution outputs over time or getting worse.
**Low contribution log accuracy (Score - 2)**
It is far easier to lose information with this approach as the information is submitted as a single submission. This could result in a lack of depth being added to better understand who exactly did what and how much effort was made by each of the individuals involved. This makes it harder for the community to look back in time and know exactly who was responsible for what without further questioning.
**Moderate reputation building usability (Score - 3)**
Teams would build up their reputation based on time based contribution logs. Keeping a consistent amount of time between each contribution log can help with making it easier to compare the performance of different teams and the same team over a period of time. The contribution logs could then be more useful as a reputation building tool for these teams. Each team can have a different amount of contributors involved in the execution of each idea. This can make it more difficult to easily compare these contribution logs which would limit the effectiveness of this information for reputation building as it is less easy to compare. Without using individual contribution logs it would be difficult to have high confidence that a team's reputation will still be relevant and accurate if the team changes.
**Low performance measurement usability (Score - 2)**
A team's contribution efforts recorded in time based logs can limit the usability of these logs for performance measurement. If the team changes over time it will be difficult to know whether this was a positive or negative outcome for the team in terms of future performance when the performance of each individual is not well known. Team based contribution logs also do not help with solving the problem of fairly distributing the compensation between the contributors in that team. Using time based contribution logs across multiple teams can at least help with comparing those teams and their performance more easily however as contribution efforts are grouped together from different sized teams this comparability is somewhat limited.
**Moderate future voting usability (Score - 3)**
Project time based contribution logs would be more useful when the team stays the same and the ideas they are executing are similar. If the team or ideas change over time there is a reduced amount of relevance for the contribution logs being a good indicator on whether the team will be effective at executing a more recently suggested idea. As teams and ideas change over time the value of previous contribution logs for voting could be limited. The advantage of project time based contribution logs is that a fixed time period could help with making the logs more comparable with other teams logs and with the same teams historical contribution logs. Increased measurability can help with making it easier for voters to make more informed voting decisions on which teams have been the most performant.
**Moderate game theory risks (Score - 3)**
Groups of contributors working on a single project would not be able to manipulate the time period for when each contribution log is being submitted. However what they can manipulate and more easily exaggerate is how long the work took in total as all of the outputs for that project are combined into a single submission. This makes it more difficult to track exactly how long each individual spent on each area which then also makes it harder for a moderator to know whether this was fair and reasonable and whether this was good or bad performance compared to the average.
**Low verification time required (Score - 2.4)**
Moderators would only need to verify the submissions made by each project which could consist of efforts made by multiple contributors. This reduces the number of total submissions to handle so reduces the overall time. If these submissions are made monthly there would still be at least moderate verification time required. The average time required to verify submissions for any verification approach should reduce over time as the tools and processes improve.
**Low submission effort (Score - 2.4)**
Only one person in a group of contributors needs to bring together the information requested about what was done in a certain time period of contribution. More than one contributor could of course still be involved in the creation of any given submission.
**Total score = 19.8 / 36**
# Individual time based contribution logs
Recording contribution logs for an individuals execution outputs after a set period of time
**Overview**
Individual time based contribution logs mean that each individual would submit evidence of their contribution efforts after each set time period. A time period of once per month could be a suitable starting point for most ecosystems.
**High contribution measurability (Score - 4)**
Contribution logs would be recorded after a certain time period such as each month and also would always be scoped to a single individual. This makes it easy to measure and compare how much contribution output one contributor has made against others.
**Very high contribution log accuracy (Score - 5)**
This approach gives the highest accuracy on exactly who has contributed what in an ecosystem which improves the discovery for the community to find people who have worked on certain areas. This can be useful for asking questions, getting feedback, or helping with future collaborations where other contributors would benefit from knowing who exactly did what so they can reach out to the right people.
**Very high reputation building usability (Score - 5)**
Individual contribution logs record an individual's own efforts meaning their logs are relevant to the contributor regardless of which idea and team they are working on. Contribution logs would follow the contributor around and can be considered by anyone in the ecosystem when they are looking to work on different ecosystem initiatives. Individual contribution logs can help with increasing the confidence that a given contributor has been responsible for certain contribution outcomes meaning this approach could be highly effective for building reputation over the long term for an individual. These contribution logs could then also be very useful for voters when determining whether a new idea or new team is likely to be effective or not based on the reputation of the individuals involved in that idea which they have built up over time through each of their own contribution efforts.
**Very high performance measurement usability (Score - 5)**
Contribution logs that are attached to individual contribution efforts makes it much easier to compare the efforts of each individual within any working team and across other teams. This approach would mean that every individual who is contributing to the ecosystem would be recording their contribution efforts in the same structure. Even if teams and ideas change regularly the contribution logs would always represent an individual's contribution efforts over a fixed time period. This consistency in the structure of the contribution log makes it easier to understand how the performance of an individual contributor and team can change over time.
**Very high future voting usability (Score - 5)**
If voters are selecting contributors to receive funding the logs would be useful for identifying and selecting the best performing talent. If voters are selecting ideas with a number of contributors involved in executing that idea then the logs would help with showcasing the talent of each of those contributors who are involved in the idea which would then help to achieve the same outcome of working out how competent and effective each team could be. If ideas and teams change over time the individual still has the contribution logs that were relevant to them and that they were responsible for. It is much easier to track an individual's contributions and performance over time. Voters can respond to this information by selecting the individuals and teams that have the most consistent high performers. Individual contribution logs can also indicate what idea and part of execution they have been working on which can mean that individual contribution logs could be viewed in different ways such as to see who has been executing a given idea, who executed a certain part of an idea and which ideas a contributor has been involved in.
**Low game theory risks (Score - 4)**
Every contributor submitting monthly contribution logs would mean it would become far easier to spot contributors who are trying to game the system and do less work but receive the same compensation. This reduction in risk is achieved by using a constant time period such as monthly periods and then also by keeping the contribution scope focussed on individuals. This makes it hard to hide from the truth of what a contributor has actually done in a month's worth of contribution.
**High verification time required (Score - 1.6)**
Individual time based contribution logs would mean capturing the highest depth of information compared to the other approaches. This would result in it taking longer than the other approaches for moderators to verify this information. The average time required to verify submissions for any verification approach should reduce over time as the tools and processes improve.
**High submission time required (Score - 1.2)**
Each contributor would need to keep a note of what they have done each month and provide that as evidence in their contribution log. This is something that should become easier over time as more processes and tools become available to automate this information gathering.
**Total score = 30.4 / 36**
# Impact measurement approaches
Comparing the different impact measurement approaches that could be used for determining how much impact has been generated by different initiatives
A funding process should help with allocating funds to initiatives that can help to generate impact for the ecosystem. Ecosystems benefit from being able to reliably identify and understand which initiatives are helping to generate the most impact. The better an ecosystem can achieve this the more they can then apply this information during funding to make better decisions about where to allocate future funding.
Many parts of the funding process could be measured to determine what impact has been generated. Priorities that get addressed, ideas that are executed and contributors who make execution efforts to support the ecosystem can all be relevant areas that could be measured to determine how impact was generated due to the funding process.
This impact measurement approach comparison is not suggesting the adoption of one approach over another. Instead this comparison helps to identify some of the complexities involved in impact measurement across these different areas. All of these measurement approaches can be an important part of an ecosystems strategy to better understand how they can consistently generate for their ecosystem through their funding process.
The importance of contribution measurability is a relevant topic when thinking about impact measurement approaches:
{% content-ref url="/pages/s74gBOcE4Yc8Z7jtKhbH" %}
[Contribution verification](/contributions/contribution-verification)
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There are many different ecosystem areas and contributor areas that could be tracked to help with understanding and measuring what impact is being generated. For ecosystem areas and contributor areas there are a number of quantitative and qualitative examples that can be considered:
{% content-ref url="/pages/Cd506e9H6kGpVKrJzSzb" %}
[Ecosystem areas for impact measurement](/approaches/impact-measurement-approaches/ecosystem-areas-for-impact-measurement)
{% endcontent-ref %}
{% content-ref url="/pages/12rLA5apJeUoz8USAOsO" %}
[Contributors areas for impact measurement](/approaches/impact-measurement-approaches/contributors-areas-for-impact-measurement)
{% endcontent-ref %}
## Approaches for measuring impact
There are three main approaches that have been compared to consider how impact could be measured in the funding process:
* [Priority impact measurement](/approaches/impact-measurement-approaches/priority-impact-measurement) - Addressed priorities can be measured to determine which priorities helped to generate the most impact for the ecosystem.
* [Idea impact measurement](/approaches/impact-measurement-approaches/idea-impact-measurement) - Executed ideas can be measured to determine how much that idea helped to address any existing priorities and also how it helped to generate any other forms of impact for the ecosystem.
* [Contributor impact measurement](/approaches/impact-measurement-approaches/contributor-impact-measurement) - Contributors efforts can be measured to determine how much impact they have generated for executing ideas and making any other forms of impact for the ecosystem.
To compare these impact measurement approaches a number of [factors have been considered](/approaches/impact-measurement-approaches/impact-measuring-factors-for-consideration) and then applied to each approach to better understand the similarities and differences between each approach.
**Key takeaways**
* **Importance & complexity of all approaches** - All of these approaches have measurability complexities, game theory risks and a moderate to high amount of verification time required. Ecosystems can benefit from improving how they measure all of these different areas that are relevant to the ecosystem and its contributors. Increasing the accuracy of impact measurement means creating more insights for the community to consider that can help with improving future prioritisation and funding allocation decisions.
* **Large opportunity to get contributor impact measurement right** - The problem for priorities and ideas in terms of impact measurement is that the priorities and ideas will change over time and new ones will need to be introduced. A funding process wouldn’t want to repeatedly fund the exact same priorities and ideas once they have already been addressed and executed. Priorities and ideas should naturally change and evolve over time. Due to this factor, knowing which priorities and ideas have made the most impact does not mean that future funding decisions will necessarily be any easier. There might be correlations in allocating future funds to similar ideas and priorities however this will not always create impactful outcomes. Contributor impact measurement does not have this problem. The selected contributors who get compensated by the treasury can continue to support the ecosystem for a long period of time. This means if ecosystems are able to effectively identify which contributors are more consistently making impact for the ecosystem those same contributor can be repeatedly selected by the community to receive future funding. Another opportunity with improving how a contributors impact is measured is that it would mean an ecosystem can more reliably increase the amount of incentives they receive. The increase or decrease in compensation people receive could potentially even be automatically changed over time as their performance and impact gets measured. Increasing the compensation being paid to the most impactful contributors can help with aligning the incentives by increasingly rewarding contributors that are able to make larger amounts of impact.
* **Impact measurement is one of the most complex areas for funding** - Measuring impact can be complex and nuanced. Numerous new tools and processes will be needed to help with reducing these complexities involved with impact measurement. There are currently very limited resources and tools that help with accurate impact measurement. A funding process that has the right tools and processes for measuring impact should be able to more accurately and reliably identify which initiatives are generating the most impact. Making this knowledge readily available will help save voters time by helping them more quickly become more well informed about what initiatives and contributors could be the most suitable for generating impact in future funding decisions. The more effectively a funding process is able to measure the impact it generates the more predictable and accurate the compensation can become for rewarding contributors that helped to generate those outcomes.
**Impact measurement approaches analysis**
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[Impact measuring factors for consideration](/approaches/impact-measurement-approaches/impact-measuring-factors-for-consideration)
{% endcontent-ref %}
{% content-ref url="/pages/kGaUBY3iEAfoVjbhxIwq" %}
[Priority impact measurement](/approaches/impact-measurement-approaches/priority-impact-measurement)
{% endcontent-ref %}
{% content-ref url="/pages/uxXC7jIu2vKk76PN03v2" %}
[Idea impact measurement](/approaches/impact-measurement-approaches/idea-impact-measurement)
{% endcontent-ref %}
{% content-ref url="/pages/wo7RlgBhypVlv1GoslxC" %}
[Contributor impact measurement](/approaches/impact-measurement-approaches/contributor-impact-measurement)
{% endcontent-ref %}
# Ecosystem areas for impact measurement
Areas that can measured to identify what impact has been generated within an ecosystem
Impact could be generated for ecosystems in a number of ways. Some quantitative and qualitative examples help to highlight some of the potential considerations an ecosystem could make when measuring the impact that has been generated in different areas for different initiatives. These areas for measuring impact are relevant to both priorities and ideas.
**Quantitative**
* **Network** - Active users or wallets, transaction volume, growth rates, number of deployed smart contracts and smart contract execution frequency.
* **Decentralisation** - Number of nodes or validators, geographic distribution of nodes, coin supply distribution, average coin holding duration and governance participation diversity.
* **Financial** - Market capitalisation, trading volume, liquidity metrics, total value locked, staking rewards, DeFi yields and stability of liquidity pools.
* **Scalability & stability** - Number of security incidents, total lost value from security incidents, number and scale of any network issues, total network issue resolution time, network uptime and network fees generated.
* **Usability** - Average onboarding time, active users on protocols and DApps, user retention rates, user generated content volume, number of ecosystem use cases and number and usage of privacy preserving features.
* **Development** - Number of active developers, code update frequency and number of development tools and developer tools and libraries usage metrics.
* **Governance** - Number of participating governance users, total network percentage participating in governance, distribution of influence and voting power and average time taken for decision making processes.
* **Community** - Views and engagement for ecosystem news and updates, number of educational initiatives and speed and availability of any community support.
* **Interoperability** - Number of interconnected ecosystems, time and cost to transact across chains and DApps, number of ecosystem partnerships and number of cross-chain transactions.
* **Research** - Number of novel innovations and research findings.
**Qualitative**
* **Questionnaires & surveys** - Capturing community experiences, sentiment and feedback through targeted questions about the ecosystem and network.
* **Interviews & focus groups -** Conducting interviews and focus groups with different stakeholders across the ecosystem to understand different viewpoints, perceptions and experiences, especially regarding usability, challenges, and community dynamics.
* **Usability feedback** - Network and DApps ease of use feedback, support satisfaction and feedback.
* **Narrative & sentiment analysis** - Analysis of current community sentiment from different communication channels and analysis of any user stories that help to highlight different themes and user perspectives and experiences.
* **Ethnography studies** - Investigations that explore how a Web3 ecosystem has integrated into people daily lives and what societal impact these ecosystems are having.
* **Case studies** - Case studies that cover different Web3 ecosystem topic areas such as finance, identity, governance or any other relevant areas to identify success factors, ongoing challenges and any opportunities that exist.
* **Observational research** - Observing network and user behaviour to look for any correlating trends and patterns and analysis that looks into which of those trends and patterns could be influenced by changing user behaviours or cultural changes.
# Contributors areas for impact measurement
Areas that can measured to identify what impact has been generated by a contributor
Impact can be generated through the contribution efforts that people make for an ecosystem. Some quantitative and qualitative examples help to highlight some of the ways that a contributor's efforts and outputs could be measured to understand the amount of impact they have helped to generate.
**Quantitative**
* **Code contributions** - Number of developer tools, protocols, architecture changes and libraries created or supported and downloaded or usage metrics for any code repositories they have contributed to.
* **Community engagement** - Total amount of community following and engagement, amount of content shared, growth of engagement metrics and retention rates.
* **Documentation** - Number of contributions made to documentation sources, total views and user time spent reading documentation and any ratings about documentation quality.
* **Product & design** - Designs contributions (logos, wireframes, high fidelity images, infographics etc), product improvements made and user experience suggestions or changes made.
* **Mentorship & support** - Total time spent supporting and educating other contributors or community members and amount of educational resources and content created and viewed by community members.
* **Strategic thinking** - Number of suggestions made and conversion rates of any suggestions made that get adopted.
* **Research & analysis** - Number of novel findings and innovations produced and number of findings that get adopted and integrated into the ecosystem.
* **Cultural contributions** - Time spent participating and improving community discussions and events.
* **Governance participation -** Total participation in governance decisions and amount of time spent advocating and discussing parameter and policy changes.
**Qualitative**
* **Quality of contribution outcomes** - The quality of outcomes generated by a contributor can be analysed and then compared with other contribution efforts to better determine how impactful their contribution outcomes have been and how well their time has been allocated for supporting and improving the ecosystem.
* **Cultural & social impact** - Community sentiment about the impact made by any contribution outcomes, contributions made towards improving ecosystem inclusivity and diversity and feedback given from recently joined community members.
* **Morals & ethics** - Quality and depth of contributions towards improving inclusivity and diversity of opinion, participation across the ecosystem showing leadership or any contributions that help to support different important issues such as environmental, social and ethical issues.
* **Mentorship & support** - Community feedback about the quality of mentorship and support provided.
* **Governance & policy influence** - Depth and thought demonstrated during governance decisions and amount of effort demonstrated that positively influenced those decision processes.
* **Leadership, vision & strategic thinking** - Evidence of thought leadership from the depth and diversity of ideas being suggested, demonstrations of impactful vision planning and ability to embrace and foster collaborative efforts that gather and share the different opinions and preferences about how to address different important ecosystem goals.
* **Creativity & innovation** - Uniqueness and creativity of any contributions made and analysis that demonstrates the potential importance and impact of novel innovations and research findings.
* **Relationships & communication** - Examples of community relationship building efforts that helped to improve team synergies and collaborative efforts, evidence of effective communication skills when sharing important information and evidence of ability to professionally handle conflicts and prevent the need for mediation efforts.
# Impact measuring factors for consideration
Listing the different factors that will be considered for each impact measurement approach
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Impact measurability**
* **Description** - When priorities get addressed, ideas get executed and contributors make contribution efforts an amount of impact can be generated that benefits the ecosystem. A measurable outcome occurs when the extent of the impact generated by a certain initiative can be more easily understood and compared with other similar initiatives.
* **Maximum score** - 5, Very important. Measuring whether impact has been generated effectively or not can have a direct influence on better informing a community on where future funds could be allocated to generate further impact for the ecosystem. An ecosystem will want to be as effective and targeted as possible in identifying what outcomes and efforts were the most effective for generating impact.
* **Scoring questions** - What total impact has been generated? How easy is it to measure the different areas of impact? How comparable is the impact generated compared to other initiatives?
* **Scoring** - Higher measurability is good (Score - 5). Low measurability is bad (Score - 1).
**Future impact opportunity**
* **Description** - Calculating the return on investment is more easily achieved when the outcomes of an initiative can be measured. If the impact generated is well understood then this information can be useful for determining what future similar opportunities might be suitable for generating impact in the future.
* **Maximum score** - 5, Very important. Effective impact measurement can directly help with identifying how future incentives could be more accurately allocated to generate more impact for an ecosystem.
* **Scoring questions** - How easy can impact be repeatedly generated by applying the information about how much impact was generated by different initiatives? Does the impact measurement of that approach help to improve how treasury assets can be allocated in the future?
* **Scoring** - Higher opportunity is good (Score - 5). Low opportunity is bad (Score - 1).
**Game theory risks**
* **Description** - The metrics and perceived outcomes of any funded initiative could be manipulated or exaggerated to make it seem like that initiative had made more impact than it actually has. Bad actors might attempt to do this to increase their chances of receiving future compensation.
* **Maximum score** - 5, Very important. An ecosystem will need to identify and prevent bad actors from lying to and deceiving a community about what has actually made an impact for the ecosystem. A community that can effectively prevent bad actors will be able to more reliably identify impactful initiatives and improve future funding decisions.
* **Scoring questions** - How could contributors lie or be deceptive about the different areas that are measured for determining what impact has been generated? How could contributors exaggerate about a certain outcome and the impact it helped to generate?
* **Scoring** - Lower risk is good (Score - 5). Higher risk is bad (Score - 1).
**Impact verification time required**
* **Description** - Verifying how much impact has been generated can take a varying amount of time for each approach. Considering the total effort and time it might require to verify the impact generated can help to reveal how complex the impact measuring process could be to execute.
* **Maximum score** - 5, Very important. The longer it takes to gather and verify the amount of impact that has been generated for different initiatives the more costly that given approach will be.
* **Scoring questions** - How much time is required to measure and verify the impact that has been generated? What parts of that measurement could be automated? What manual verifications might still be required now and in the future?
* **Scoring** - Lower time required is good (Score - 5). Higher time required is bad (Score - 1).
# Priority impact measurement
Impact measurement approach for measuring the amount of impact that's generated by priorities that get addressed
**Overview**
Priority impact measurement focuses on determining the amount of impact that has been generated when a priority gets addressed.
**Moderate impact measurability (Score - 3)**
* **Total impact measuring complexity** - There are many potential areas of impact that a priority could help with. A priority getting addressed can create impact outside of the intended areas of focus meaning it can be difficult to fully capture what total amount of impact was generated.
* **Ease of measurement** - Most of the quantifiable areas of potential impact should be easy enough to track however there is still a need for interpreting these numbers as Web3 ecosystems can have many different priorities and ideas being executed at once as well as other changing environmental factors. This means it can be more difficult to attribute certain outcomes to a single priority that has been recently addressed.
* **Comparability** - Comparing the impact between different priorities can be highly complex due to situations where there are many ideas that could help with addressing a priority. If each priority has numerous ideas that have been executed this means there can be a large range of data points and considerations that need to be made to determine which priorities have been the most impactful when they were addressed.
**Moderate future impact opportunity (Score - 3)**
* **Usefulness for future decisions** - An addressed priority that helps to generate large amounts of impact does not necessarily mean an ecosystem can create a new priority that will generate a similar amount of impact. The environment and preferences of an ecosystem can change over time and what has worked in one ecosystem previously does not mean it will definitely work again in another ecosystem. There could be some correlation in some priorities that are more effective than others for generating impact and others that are much more wide ranging in what impact they generate.
* **Repeatability** - There is at least some repeatability in situations where priorities can help to address certain market segments and could be more effective and impactful than other priorities. These priorities could be potentially extended and updated to take advantage of the full opportunity available. However in some cases this impact generation could be difficult to repeat. The challenge will be to determine what the next logical steps are in terms of prioritisation for the different market areas that an ecosystem has seen success with.
**Moderate game theory risks (Score - 3)**
* **Manipulated outcomes** - Most of the quantifiable metrics could be potentially manipulated with bots or external actors. The larger the metric, the more complex or costly it could become to hide any manipulated actions. An example could be increasing the total number of transactions or chain utilisation as this could have far higher cost implications for generating those extra transactions if someone was trying to manipulate that metric. Bad actors could also try to influence qualitative measurement approaches by purposefully identifying and gathering certain feedback and responses to influence others in the community.
* **Exaggerated outcomes** - Bad actors could conduct research and generate analytical resources that are biassed with identifying certain outcomes that could benefit themselves in future funding decisions. As more data becomes available these actors could cherry pick certain information that exaggerates a certain narrative that aligns with what they are trying to influence.
**Moderate impact verification time required (Score - 3)**
* **Automated verification** - Much of the quantifiable metrics can be automatically verified due to the fact the information will be stored on immutable ledgers and blockchains. Tools can help with reducing the time it takes to get this data, format it and then present it in a digestible format.
* **Manual verification** - The qualitative areas of impact measuring will need a more organised and collective effort to record, analyse and verify any relevant information. Tools could eventually help with identifying biases, flaws and potential conflicts of interest that emerge from the contributors who participate in collecting this information.
**Total score = 12 / 20**
# Idea impact measurement
Impact measurement approach for measuring the amount of impact that's generated by ideas that are executed
**Overview**
Idea impact measurement focuses on determining the amount of impact that gets generated when an idea is executed.
**Moderate impact measurability (Score - 3)**
* **Total impact measuring complexity** - An idea can often have a narrower set of potential outcomes and areas of impact than an ecosystem wide priority might have. Even though this might be the case there would still be many different areas for generating impact that an executed idea could help with. Executed ideas could also have secondary effects on other areas and generate impact for an ecosystem in a multitude of other ways. This makes it harder to determine what the total impact is for an executed idea.
* **Ease of measurement** - Most of the quantifiable areas of potential impact should be easy enough to track however there is still a need for interpreting these numbers as Web3 ecosystems can have many different ideas that are trying to address the same priorities. For any of the metrics that an idea is trying to help with, another factor to consider is how other initiatives could have also impacted those metrics in the same time frame.
* **Comparability** - The more targeted and specific a priority is the more easy it could be for ideas to be compared with each other when determining which of the executed ideas was most impactful for helping to address an existing priority. In other situations comparability is difficult as ideas can help with generating impact outside of any existing priorities and may cause other outcomes that generate more impact than the initially intended area. Ideas that have completely different execution outcomes, like an event and a software protocol, would be more difficult to compare as they have different outcomes and ways they would be measured for generating impact.
**Moderate future impact opportunity (Score - 3)**
* **Usefulness for future decisions** - If an executed idea helps to generate a large amount of impact there could be some correlation that incremental improvements to that same idea or similar ideas could also generate further impact as well. Another way that measuring impact could be useful is if it helps to identify the contribution approaches that generate the most high quality outcomes. Future ideas could learn from these previously impactful ideas which were executed in a certain way. Future decisions will involve selecting different and novel ideas which means there can be a limit in the usefulness of previous ideas that generated a certain amount of impact as these new ideas are trying to generate different outcomes. Some learnings can be gathered from these previous examples however it would be difficult to have any high certainty on what future ideas will definitely generate impact or not.
* **Repeatability** - Previous ideas can help with generating learnings about what quality of outcomes are needed to generate impact and how different ideas could be executed from a process perspective. What is less repeatable is the outcomes and impact generated as different ideas will generate different outcomes. This makes it difficult to accurately predict the impact that these outcomes will generate with any certainty. Some potential areas for repeatability could be identifying successful approaches that other ecosystems have adopted and integrating those approaches into the ecosystem. Another area could be extending an already successful idea by identifying the next logical steps of execution for that idea to improve and generate more impact.
**High game theory risks (Score - 2)**
* **Manipulated outcomes** - Ideas that are perceived to be more impactful than others could impact the funding process by influencing a community to select the contributors who were responsible for executing those ideas. Due to this there is an incentive for contributors to manipulate the metrics and feedback that emerges after an executed idea is measured so that they can increase the chances that they get selected for compensation in future funding decisions. Ideas can be more narrow and targeted in what they are trying to achieve. This smaller surface area of execution can help with making it easier to manipulate the numbers involved about how much a certain executed idea has been adopted or generated impact for the ecosystem.
* **Exaggerated outcomes** - Bad actors could target the most active participants that have used their executed idea to get testimonials and feedback that better align with their own narrative about how impactful their idea is for the ecosystem. Contributors can be expected to try and promote their own ideas positively to generate more interest and opportunity to receive future compensation. The risks around these efforts will be when that same targeted selection of narrative turns into excessive exaggeration and false observations and statements at the detriment of the ecosystem in being able to identify the most impactful opportunities to support in the future.
**High impact verification time required (Score - 2)**
* **Automated verification** - Much of the quantifiable metrics can be automatically verified due to the fact the information will be stored on immutable ledgers and blockchains. Tools can help with reducing the time it takes to get this data and format it into a digestible format. As ideas are often more targeted and focussed than priorities it should require less time to gather and verify this information.
* **Manual verification** - The qualitative areas of impact measuring will need a more organised and collective effort to analyse and verify the information gathered. Tools could eventually help with identifying biases, flaws and potential conflicts of interest that emerge from the contributors who participate in collecting this information. As ideas are often more targeted and focussed than priorities it should require less time to gather and verify this information.
**Total score = 10 / 20**
# Contributor impact measurement
Impact measurement approach for measuring the amount of impact a contributor makes through their contribution efforts
**Overview**
Contributor impact measurement focuses on measuring the amount of impact that gets generated by someone's contribution efforts across an ecosystem.
**Moderate impact measurability (Score - 3)**
* **Total impact measuring complexity** - The other approaches help to reveal that it’s at least moderately complex to determine the total impact an executed idea or addressed priority has helped to generate. This complexity is relevant for determining a contributor's total impact generated as it would be useful to know what impact their contribution outcomes have made for the ecosystem. It could be achievable to understand what percentage of outcomes a contributor is responsible for by tracking their quantifiable contributions. This still doesn’t mean it will be easy to determine an accurate amount of total impact generated. A contributor can help with supporting many different execution outcomes which could further increase the complexity due to having overlapping efforts on the different ideas. The quality of the contribution efforts is also another important factor which would influence the actual amount of impact a contributor has generated.
* **Ease of measurement** - The quantifiable contributions could be somewhat easy to measure. The problem with these measurements is they are not highly valuable on their own without further analysis about the quality of contributions being made. One developer writing twice as much code as another developer means very little without understanding the complexity, novelty and thought that was required to write that code.
* **Comparability** - If contributions can be measured sufficiently there is a moderate ability to compare the contribution outcomes and potential impact of different contributors. One way that comparability can be improved is by adopting a monthly contribution log approach so that it becomes easier to compare one contributor's outputs to another.
**Very high future impact opportunity (Score - 5)**
* **Usefulness for future decisions** - Measuring the impact of different contributors effectively will mean identifying which contributors are most highly correlated with generating impactful outcomes. This is highly useful for a funding process as it enables a community to align the future incentives with the contributors who are more consistently generating impact. Contributors being aware that the incentives are aligned with generating impact further compounds the reasons that these contributors will look to better identify and execute initiatives that can generate the most amount of impact.
* **Repeatability** - A highly performant and effective contributor will be those that are able to execute ideas more quickly and to a high quality. A contributor's abilities can gradually improve over time as they continue to learn more skills and have more experience about how to best contribute in these ecosystems. Due to this there is a high chance that these contributors could repeatedly help with generating impact for the ecosystem.
**Very high game theory risks (Score - 1)**
* **Manipulated outcomes** - Each contributor would be responsible for submitting their own information about what contributions they have made that help to generate impact for the ecosystem. As this is an independent process it could be far easier for people to lie about what they have actually done for certain contribution outcomes that can’t be automatically tracked online.
* **Exaggerated outcomes** - Some more challenging areas to properly verify is the quality of contributions made and verifying the qualitative areas of impact. A contributor could help with many ecosystem areas and overstate their contributions and amount of influence in achieving impactful outcomes. It could be more likely for a contributor to exaggerate their contributions if that increased the chances they are selected for future compensation.
**Impact verification time required (Score - 1)**
* **Automated verification** - A lot of the digital contributions could be tracked and verified automatically which will help with keeping an accurate log of what each contributor has done. This only covers some of the contribution areas as others are more difficult to track such as collaborative efforts during discussion and planning.
* **Manual verification** - Many of the contribution outcomes that could be verified automatically would still require manual verification to assess the quality of contribution. It wouldn’t matter if a developer had delivered more code than any other developer if that code was not to a high quality or was comparatively much easier to develop than more complex problems that other developers had been solving. Qualitative contributions would also benefit from being verified in some capacity to ensure that contributors have not lied or exaggerated. A large amount of effort could be required to accurately verify the impact that contributors generate.
**Total score = 10 / 20**
# Knowledge process
Overview about the importance of a knowledge process for funding
Knowledge enables a community to understand what is happening inside and outside of an ecosystem. When knowledge is digested by a community it can then be applied to determine what priorities, ideas and contributors are the most important and suitable for that ecosystem to thrive. The knowledge process is concerned with identifying, creating, gathering, aggregating, presenting and selecting the most relevant and useful information that an ecosystem should consider to make well informed funding decisions.
Knowledge systems would be any system that helps with gathering, aggregating or presenting information. Knowledge systems can help with tackling the increasing challenge of handling a large amount of complex information that can exist across Web3 ecosystems. To scale an ecosystem's decision making ability it will be important that voters are able to quickly get access to and understand important information so they can become well informed before making governance decisions. Making voters more well informed can help with improving the communities decision making ability to identify the most important priorities for the ecosystem and how treasury assets could be disbursed towards impactful initiatives that help to address those priorities. The more informed a community becomes about what is happening both inside and outside the ecosystem the better they can become at deciding what priorities, ideas and contributors will be most suitable for making more impactful outcomes. Quality knowledge systems can provide a scalable solution for making it easier to participate in governance decisions. An outcome which could help with further decentralising these emerging networks and their governance processes.
## Process steps
* **Identifying relevant information** - Identify the most relevant areas of information that an ecosystem could benefit from knowing about when making funding decisions. It can be worthwhile to group this information together based on what sources it comes from. One example grouping could be any on-chain data, this grouping would include any information that can be retrieved directly from public ledgers and blockchains.
* **Gathering & aggregating information** - Systems and processes can be created that help with collecting and verifying the relevant information from different sources. These systems will ideally be open sourced and publicly verifiable to improve the trust that end users have in using the information that has been gathered. Knowledge systems can help with the gathering and aggregation of different sources of information. If no knowledge systems exist then individuals in an ecosystem would themselves need to do any research to find relevant information to help with becoming more informed for their own decision making.
* **Presenting information** - Systems that help with collecting knowledge can also be responsible for presenting this information in a way that is easy to understand and quick to interpret. How data is presented can impact the amount of insights and utility that information provides. Another factor is how the information being presented can be easily compared or intersected with other relevant information to identify new findings. The faster that voters can read and understand important ecosystem information the more scalable it becomes for many voters to become well informed in a short period of time before making important funding decisions. An ecosystem will benefit from ensuring the community is well informed on what knowledge systems exist and how that information can be most easily accessed and digested.
* **Digesting & selecting information** - Community members will consciously and unconsciously use the information they digest to make future decisions. The more information that someone is able to digest and understand the more informed their opinions can become assuming the information sources are relevant and accurate. Community members will determine which pieces of information are most relevant and important when making their own funding decisions. Some ecosystems could optionally choose to also explore a knowledge selection system where community members openly select and vote on the most useful or important pieces of knowledge.
* **Updating information** - Information can become outdated quickly if it is not maintained. Some information such as on-chain data can be gathered automatically and can more easily be always kept up to date. Research and analysis on what is happening in the ecosystem is one area that would need to be updated as time progresses so that any new trends and insights can be identified.
## Desirable outcomes
* **Accuracy** - The accuracy of any knowledge that gets created or aggregated will be an important outcome for any contribution efforts that bring new knowledge to an ecosystem. Available knowledge will be used by voters to make priority, idea and contributor selection decisions. Due to this the accuracy and correctness of any knowledge produced will need to be high.
* **Higher information quality** - Achieving higher information quality will mean that all of the relevant areas of information are covered when a new piece of knowledge is created. As an example a transaction explorer would benefit from including all of the information about transactions so that it’s very clear what is happening instead of only a subset of the available transaction information. High quality knowledge sources should ideally provide full coverage of any relevant information.
* **Verifiable** - Many knowledge sources can come from systems and processes that provide factual data about what happened during execution. Ensuring that any code and logic behind any knowledge sources is open source and verifiable can help with increasing the amount of trust in these knowledge sources. Making it easier for voters to determine what information is fact and opinion will also mean that voters will have an enhanced ability to better decide which pieces of information they believe is the most important and useful when making certain funding decisions.
* **Maintained information** - Knowledge can quickly become out of date if it is not updated over time. A knowledge process will need to consider how it incentivises community members to keep important knowledge sources up to date so that the information remains relevant and useful.
* **Automated systems** - Knowledge which can come from automated systems can often provide information as soon as it’s recorded. Opportunities to create any automated systems that gather, analyse and present data can be highly beneficial for voters to use when making their own funding decisions. These systems can also be foundational for deeper analysis that help with identifying important problems and opportunities. Automated knowledge systems also provide an opportunity for smart contracts that might want to rely on these sources of data to enforce certain rules that have been defined in the contract.
* **Timeliness of new information** - Knowledge can impact any part of the funding process so having access to useful information as quickly as possible can make a big difference in how effectively assets can be disbursed and how fast existing contributors can respond to new information. Knowledge processes that are effective at encouraging the ongoing creation of insightful knowledge can be highly beneficial for an ecosystem to become more responsive to changes and when making any future decisions. Supporting knowledge sources that can become automated through software is one way in which the timeliness can be improved.
* **Diversity of information sources** - Quality information that can be used for making well informed decisions can come from a multitude of sources. Using sources of knowledge that come from both inside and outside the ecosystem can be highly beneficial for making an ecosystem more well informed.
* **Voters become more well informed** - Comprehensive knowledge systems that cover the different areas in an ecosystem can help voters become more well informed about what is happening inside and outside the ecosystem and across other different topic areas. This increased depth of knowledge can help with improving a voters decision making ability.
* **Reduced time required for voters** - The better that information is structured and presented the less time it should take for voters to become well informed about different topic areas. Achieving this outcome can help with making governance processes more scalable as more voters will be able to quickly learn about the relevant information and then participate in governance decisions.
* **Decreased time for new information to propagate** - Many knowledge systems could have live data being fed into them which could then be immediately sent to and digested by a community. A blockchain explorer that lists all the recent transactions is a good example of this type of real time information. The more that these services are made available and easy to use the faster a community will be able to receive and respond to new information.
* **Reduced information complexity** - The quantity and depth of information relevant to these growing Web3 ecosystems is vast, often meaning it can be difficult to understand enough of the information available to be well informed. Knowledge systems could help with how information is presented and structured to pull out the most important facts and insights. Achieving this will make it more simple for people to understand and apply the most useful information.
* **Scalable solutions for informing voters** - Creating systems and processes to better aggregate and present information relevant about an ecosystem is a more scalable solution than voters trying to complete this research and analytical work themselves independently.
* **Increased transparency & awareness** - Information that may have otherwise been difficult to find or locate could now be made more publicly available through the usage of knowledge systems that help to aggregate and present a diversity of relevant information. This transparency and awareness of the available information can help with increasing the trust in these ecosystems and help with making it more open and accessible for community members to respond to new and important information.
* **Integration opportunities** - Knowledge systems could be integrated into a range of different systems and processes. For instance, solutions building with AI technology could integrate the information provided by knowledge systems to then analyse or combine that information with other relevant information sources to generate new insights or an improved understanding of what is currently happening.
## **Concerns**
* **Relevance** - The true value of different sources of information may not be immediately obvious when deciding whether or not to support the efforts behind a certain knowledge initiative. Sometimes it is the intersection of multiple pieces of information that help bring more clarity or new understandings about what problems and opportunities exist. Due to this complexity there is a concern that potentially import and impactful knowledge sources are not supported or alternatively that too many knowledge initiatives get supported that do not generate large enough levels of impact with making an ecosystem more well informed.
* **Information complexity** - Knowledge relevant to an ecosystem can cover a wide range of topics with different levels of complexity. Part of the challenge with the creation and maintenance of different information sources is ensuring that the outcomes of that work are not overly complex for others to digest and understand. Ecosystems will need to consider how they encourage contributors to spend sufficient time in increasing the ease of use and readability of any new pieces of knowledge that get created.
* **Correctness of information** - As the scale and assets under management of Web3 ecosystems increase over time there is an increasing importance in making sure the information that is made available and that is relied upon is correct. If the information is biased, exaggerated or incorrect this could directly influence the outcomes of certain funding decisions. Knowledge sources would be an ongoing potential attack vector that will need to be constantly considered so these potential issues can be avoided.
* **Conciseness** - The larger the amount of knowledge available the longer it will take for voters to become well informed about all of the different sectors and topic areas that are relevant to an ecosystem. The most important knowledge will need to be clear and concise due to the difficulty in expecting voters to digest vast amounts of information. The conciseness of knowledge will be an important factor for the scalability of participation in any funding decisions and governance more generally.
* **Complexity in aggregating information** - Existing nation state and corporation treasury systems that have fewer people involved in decision making can more easily adopt more manual based processes for individually aggregating information they think is important before making well informed decisions. If this knowledge needs to be distributed between a much larger group of participants a manual approach becomes far too costly and difficult to scale. Web3 ecosystems will need to find efficient and effective ways to aggregate relevant information about the ecosystem so that participants in the funding process can review and understand what is happening. Considerations will be needed on how information can be most effectively presented to communicate the key points quickly and correctly so that the funding process can be scalable. If the ecosystem is unable to get access to the right information when making funding decisions it will be more difficult to make optimal decisions. This factor is one reason why it is easier to centralise decision making in existing systems due to the complexities involved with making a large group of people well informed about many different pieces of information.
* **Time cost of learning & knowledge sharing** - It takes time for people to read and understand any information that has been shared to them and even more time to then apply that knowledge when making their own decisions with treasury funding. The more information there is available the more time it would take for each person that wants to participate. These factors makes it difficult to scale decentralized governance due to the cost of trying to be well informed when participating. One of the challenges for Web3 ecosystems is being able to identify what information is the most important for the different decisions that must be made and how can that information can be most accurately and easily presented to participants when making any decisions. Bringing the time cost down for sharing and understanding knowledge will make these emerging systems more easy to participate in scalable.
* **Ongoing attack vector** - There would be an ongoing risk that malicious actors try to maliciously influence different knowledge systems to achieve personal gain or to compromise a system and its governance processes. These actors could try to insert biased or incorrect information into different knowledge systems in a multitude of ways. Knowledge systems will need to have an ongoing amount of moderation and verification to review how these systems are being used and how they get changed over time to identify where attack vectors may have been introduced or where problems have already emerged.
* **Dependency risks** - As knowledge systems become more effective at gathering and presenting information there is an increasing risk that governance processes become over reliant and dependent on these systems. Having alternative options will be one approach to help reduce this risk. Adopting a mission critical mindset and development approach when creating these systems and processes will be another approach to try and reduce these dependency risks further.
* **Centralisation risks** - Not all information gathered will come from informational systems, some information will not be easily verified and audited. A lot of information relevant to ecosystems can come from analytical sources and be created through the understanding, intersection and analysis of the current information available. This expert led analysis can create an ongoing risk where a centralised group of actors could establish a growing amount of influence over what analysis gets created and communicated across an ecosystem. Checks and balances will be needed to ensure any contributors with higher influence are not misleading people or sharing biased, incorrect or exaggerated information.
# Priority process
Overview about the importance of a priority process for funding
Prioritisation is an important process in funding where an ecosystem determines which areas and initiatives are the most important and urgent for the ecosystem to focus on. Ecosystems benefit from being able to express their preferences on what the most impactful areas are in the ecosystem that funding could support with treasury assets. Good prioritisation can help with identifying the most impactful initiatives that would help with addressing the biggest problems or opportunities that exist in the ecosystem. Prioritisation of these different problems and opportunities can have a direct impact on where treasury assets get disbursed. Priority systems that help to gather and record the preferences of a community help with gathering and presenting the current sentiments and opinions of the community. This process alone can help spark further discussion and debate about what areas and initiatives are most important and potentially impactful for the ecosystem.
Treasury funds could be disbursed to a wide range of different initiatives that each have their own opportunities, risks and tradeoffs. Good prioritisation can make the difference between sustainability and growth over the long term for an ecosystem versus stagnation and decline due to poorly allocated treasury assets. Community members involved in any funding decisions will want to apply the available knowledge about the ecosystem to better identify and compare which problems and opportunities are the most important at that certain point in time. The priority process can provide a way for a community to express their exact preferences and opinions so that the community can better identify where alignment and compromises might be needed when disbursing limited resources.
## Process steps
* **Identifying problems & opportunities** - Problems and opportunities can be identified by digesting and analysing the available knowledge in the ecosystem. The more that the community can understand what is happening inside and outside the ecosystem and what is working well and what isn’t the more they will become well informed about the most important problems or opportunities that could be prioritised in the ecosystem.
* **Creating priorities** - Community members will create priorities to share the different problems and opportunities that the rest of the community will benefit from considering. Priorities could be targeted at a high level to help with communicating a preferred general direction an ecosystem wants to take. Priorities could also be lower level and be more targeted towards exact areas of focus that the ecosystem could benefit from spending more attention and resources on.
* **Selecting priorities** - Selecting priorities could have a big impact on the funding process as these preferences could heavily influence where funds get allocated. An ecosystem benefits from being able to communicate why certain priorities are important at the moment and then seeing the level of support those priorities receive from other community members of an ecosystem.
* **Maintaining priorities** - As ecosystems start executing ideas to address the most important priorities there will be new emerging information and changing factors that influence the progress and importance of those priorities over time. As well as this external factors or community preference changes could also influence the importance of priorities. Priorities will need to be kept up to date with relevant information that shows the progress of initiatives that are helping to address existing priorities or any other changing factors.
* **Measuring outcomes** - Although it is not always possible for priorities to be measurable in whether they have been exactly achieved or not there is still benefit in trying to measure the outcomes of any priorities that have been addressed or that are close to completion.
## **Desirable outcomes**
* **Diversity of thought** - The priority process can benefit from attracting a diversity of thought from the community about which problems and opportunities exist. Diversity of thought in the priorities submitted can help with better enabling the voters to consider which priorities are actually the most important at that moment. Enabling a full range of opinions in the priority process will help with creating a more expressive system that effectively represents the opinions of an entire community.
* **Quality submissions** - Adding the right depth of detail along with all of the relevant supporting information sources will be an important part of creating insightful and relevant priorities that a community can then consider. A priority process can benefit from trying to increase the quality of the priorities being submitted and that any suggestions are sufficiently justified.
* **Inclusive** - A prioritisation process can help with enabling a community to express their thoughts and opinions. Making a more inclusive prioritisation process will mean making it simple to use and participate in so that a wider diversity of people can contribute to the process.
* **Timely submissions** - If an ecosystem wants to be more responsive to a fast changing environment it will benefit from ensuring that any suggested priorities can be submitted at any point in time for community consideration. Priority processes should be effective at encouraging a community to submit priority suggestions quickly so that emerging problems and opportunities can be addressed more promptly.
* **Priorities are feasible** - Priorities that get submitted and then selected should be feasible for the ecosystem to address. This means that ideas that could be executed to address these priorities can actually be executed. Having priorities that are measurable is one approach that can help with ensuring that priorities are feasible. If the priority was not measurable it could alternatively use a voting mechanism so that the community could indicate that they believe a priority has been addressed. The focus on certain priorities could also naturally increase or decrease over time as the importance of those priorities change based on how the community is voting and spending their time on the different existing priorities.
* **Well maintained information** - Keeping priorities up to date with the most relevant and important information will help with keeping the community well informed about what is happening across each priority. The better this information is kept up to date the more responsive a community can become in increasing or decreasing the importance of certain priorities as new information starts to emerge.
* **Improved decision making** - Adding new information to existing priorities can help with making voters more well informed about what is happening across each existing priority. The more informed that voters become on what is happening in the ecosystem the more well informed they can become when making future prioritisation decisions.
* **Reallocation of contribution effort** - Updating priorities can help with the reallocation of contribution efforts from one priority to another as the importance of each priority changes over time. Good prioritisation systems can help with enabling this behaviour of contributors migrating their attention and focus towards the most important priorities.
* **Important priorities get addressed** - A priority process should ideally have enough influence over the funding process to ensure that the most important priorities get addressed. A priority process will need to consider how the incentives are aligned to encourage and support the initiatives that help to address the most important priorities.
* **Measurable outcomes** - Although it might not always be easy or possible, it is at least desirable for priorities to be measurable when possible so that the progress and completion of any priorities can be more easily tracked and reviewed upon completion.
## **Concerns**
* **Lack of engagement** - A process for priority setting that takes too long or that is too complex could be a reason for a lack of engagement. Another reason is if existing priorities are not getting addressed people may choose to disengage with the priority process. If the priority process has a large influence in how treasury assets are disbursed it will be important there is a sufficient amount of engagement from the community so that the most important priorities are suggested and selected.
* **Process complexity** - Prioritisation is an important part of funding for community members to express their thoughts and preferences. The diversity and depth of these different opinions could lead to the creation of an overly complex process due to the amount of different priorities that need to be reviewed and maintained. Considerations will be needed about how the submission of priorities can remain relevant and concise but still highly informative.
* **Information complexity** - The diversity of opinions and information relevant to each priority could be vast and potentially be highly overlapping. A priority system will need to consider how it manages and incentivises more collaboration around bringing together similar opinions rather than a system that leads to a lot of duplicated information. It will also be important to encourage people to add the most relevant and concise pieces of information to a priority rather than to incentivise people to add as many pieces of information as possible that could lead to bloating the prioritisation process. Too much information could make it difficult for voters to easily and quickly understand what is happening with each priority and which priorities are currently the most important.
* **Malicious and biased contributions** - An ongoing concern with prioritisation is how bad actors could try to influence what gets prioritised through submitting priorities or maintaining existing ones with information that is biased, incorrect or misleading. Priorities could highly influence how treasury assets get allocated meaning there would be an ongoing incentive for bad actors to try and influence this process in their favour. A priority process will need to consider how the identity of contributors is being verified and reviewed and how the process could potentially be gamed and exploited.
* **Measuring priority completion** - Priorities are not necessarily easy to measure or mark as completed. For instance a community could want to prioritise more DeFi innovation in their ecosystem but ahead of time don’t know exactly what innovation is possible. A priority process will need to consider how it can handle different forms of prioritisation and whether it intentionally encourages one approach over another and what ramifications that approach might have on the funding process.
* **Execution scope complexity** - A number of ideas could exist that help with addressing different priorities. The diversity in ideas that could be focussed on increased the range of execution scope that might be involved in a given priority. This can make it difficult for a priority process to determine how much effort or resources will be needed to address a priority.
* **Changing priority complexity** - If the scope of a priority changes over time due to new information or a changing environment the amount of incentives that are required to address that priority can change. Accepting the fact that priorities can change over time makes it more difficult to estimate accurate budgets ahead of time. It also means it is beneficial for a priority process to accept an ongoing amount of suggestions and information so that it becomes actively responsive to these changes rather than only enabling these changes at certain periods of time.
* **Stifling other forms of innovation** - Community set priorities can have a large influence on how treasury assets get disbursed. Community set priorities could increase the risk that novel and less well known areas of contribution get ignored that have the potential to create highly impactful changes to an ecosystem. A priority process will need to consider the risks around groupthink and how prioritisation could encourage or prevent novel contribution efforts towards less recognised but important ideas.
* **Increasing priority selection complexity** - As a Web3 ecosystem starts to scale the complexity of selecting priorities could increase over time due to an increasingly diverse community that have a wider range of backgrounds, opinions and preferences in how the ecosystem could move forward. This increase in thought diversity will make priority selection more complex as there could be an increasing number of competing priorities to choose from. This increase in the number of priorities also increases the complexity for voters to become well informed when they are deciding which are the most important ones.
* **Priority selection scope complexity** - Web3 ecosystems will need to become increasingly capable of determining what scope of execution efforts the ecosystem can feasibly handle. The community will not want to select too few priorities that would be too easy to achieve and result in stagnation of potential change and progress. On the other side an ecosystem would also not want to be overly ambitious and set too many priorities as this might not be feasible nor practical in the short to medium time frame.
* **Maintaining overall mission and purpose** - Growing the number of community members involved Web3 ecosystems will mean increasing the diversity of opinion and preferences about how that ecosystem could evolve over time. If the ecosystem was set up for a particular purpose this initial mission and purpose could fade over time and be lost as the ecosystem scales. Ecosystems will need to determine whether this is important or not for their ecosystem and if so how they can maintain a culture of trying to achieve that mission over the long term. A constitution is one approach in which the mission and values of an ecosystem could be recorded, the [United States constitution](https://www.senate.gov/about/origins-foundations/senate-and-constitution/constitution.htm) being one example.
# Idea process
Overview about the importance of a idea process for funding
The idea process is concerned with identifying the initiatives that could help address the existing priorities or generate impact for the ecosystem. Contributors can suggest ideas to get feedback and collaborate with the ecosystem. The idea process aims to help with identifying the most promising ideas that should be executed by contributors in the ecosystem. The community should be able to respond to these suggested ideas with their preferences, feedback and opinions on which ideas could be the most promising for generating impact in the ecosystem.
Inspiration for promising ideas can come from many sources. One important source of inspiration will be the knowledge process where community members are able to reflect on the available knowledge of what is happening inside and outside the ecosystem and then consider which ideas could generate impact for the ecosystem. One example could be a contributor spotting functionality or approaches that have proven to be effective in another ecosystem that could also then be integrated into the ecosystems own applications. Another important source of inspiration will be the priorities that the community has suggested and selected. The idea process can help with capturing and recording the different ideas shared in the ecosystem and then help with supporting the collaborative efforts needed to determine which ideas have the most promising potential outcomes. An idea process can benefit from being flexible and enabling ideas to change as preferences, information and the surrounding environment changes over time.
## Process steps
* **Identifying promising ideas** - Communities will need to apply the available knowledge they have about what is happening inside and outside the ecosystem to understand the current landscape of what ideas already exist, what is being worked on and what other areas could be explored. Using this information the community can start to suggest and define different ideas that could be executed to address the priorities that exist or that could generate impact for the ecosystem. The identification of new ideas could happen at any point in time. Some ideas could be fully planned out ahead of time with all of the potential intersecting ideas. Others could be more difficult to fully plan out where they instead could often change and adapt over time as the idea is executed and new learnings are made.
* **Creating ideas** - Creating well thought through ideas requires a sufficient understanding of the opportunity or problem that the idea is focused on. Having the right experience and skill sets will help in being able to properly break down an idea into the required steps of execution. Contributors who are creating ideas will need to consider information such as the complexity of the idea, how long it might take to execute, what evidence there is that it could be impactful for the ecosystem, what skills would be needed to execute the idea and how any outcomes of that idea could be potentially measured. Contributors can share their idea with the wider community to get feedback on the intended use cases and value proposition of the idea. This process of sharing ideas can help with identifying the projects which share any mutual problems and opportunities. For instance two projects could both benefit from a certain utility software library from being created and decide to collaborate on the planning and execution of that idea to prevent duplicated efforts.
* **Selecting ideas** - There are many ideas that could help with addressing ecosystem priorities or generating impact. Effort is needed to properly articulate and document how one idea could be effective for addressing different priorities. Community members that are participating in the selection of the most promising ideas will need to be able to compare these suggested ideas against the existing priorities and any other opportunities for generating impact to determine which of these ideas is the most promising for the ecosystem to allocate more attention and resources towards.
* **Maintaining ideas** - As ideas are executed there is new information that emerges such as new learnings that will influence how the idea gets executed over time. External factors and changing environments and preferences could also influence how an idea evolves and gets executed as it progresses. An ecosystem can benefit from seeing how and why different ideas are changing over time.
* **Measuring outcomes** - Understanding what impact an executed idea has produced is inherently complicated due to the wide range of ways an idea could be executed and the range of factors that could influence whether a solution has generated impactful outcomes or not. An ecosystem will benefit from getting better at measuring the impact of executed ideas so that these learnings can be fed back into the funding process to improve future decision making and contribution efforts.
## **Desirable outcomes**
* **Detailed idea information** - Ideas can be complex and require a lot of information to effectively articulate how that idea could be executed and what benefits it would bring against other ideas and approaches. The idea submission process will benefit from the encouraging proposers to provide a sufficient depth of information to justify why their ideas are well thought out and promising solutions.
* **Feasible ideas** - Some ideas can sound fantastic on paper but could be overly complex or impractical to execute. An idea process will need to encourage the submission of ideas that are practical and achievable over ideas that over promise and are not realistic. One potential solution area for handling problems around feasibility could be the inclusion of a reputation based approach so voters are aware of the previous track record of idea proposers and how often the ideas they suggest have been feasibly executed and resulted in impactful outcomes.
* **Inclusive** - There are often many different ideas that could help with addressing the existing priorities in an ecosystem. Those ideas can have different trade offs and implications. Ecosystems can benefit from inviting the submission of a diversity of different ideas for the ecosystem to consider and iterate on. Incentives will need to consider the trade offs of being inclusive and inviting wider participation whilst also making a practical process that doesn’t become overwhelming with too many ideas.
* **Supports idea development** - Too many ideas that lack sufficient justification could result in the need for a moderation process so that proposals meet a readiness or quality threshold. A multi step process for idea submission could help with handling ideas that are in a draft state before a final version is submitted. An idea process could benefit from increasing the amount of collaboration between contributors when suggesting and iterating on different ideas to help with team building and merging overlapping ideas together.
* **Timely submissions** - New ideas could emerge at any point and could offer a novel approach for generating impact for the ecosystem. Due to this an idea process can benefit from encouraging people to submit ideas at any stage to start some collaboration efforts and discussion around those ideas.
* **Aligned with addressing priorities** - Priorities can often get addressed through the execution of promising ideas. The systems and processes used for idea submission and selection can help with increasing the alignment of contributors with suggesting ideas that can help with addressing important priorities. The idea process will also need to be careful to not to exclude ideas that don’t align with the existing priorities as these efforts could still be highly impactful and innovative.
* **Well maintained information** - The idea process can benefit from encouraging contributors to keep information about an idea up to date so the ecosystem is well informed about what is happening regarding any idea being executed. This information could include any reports about progress and completion, community feedback and discussion and any justifications about why the execution outcomes of some ideas are changing due to new learnings of information.
* **Improved decision making** - Keeping information up to date during the execution of an idea can help with improving future decision making as voters could become more informed about how well the progress is going for the different ideas being executed across the ecosystem.
* **Reallocation of contribution effort** - Some ideas will generate large amounts of impact for an ecosystem whereas others may struggle and become stagnant. It can be difficult to know ahead of time whether an idea will truly get the right response and adoption and then generate high levels of impact. It is due to this variability in what could actually happen that contributors will benefit from being able to be more flexible in how they execute ideas and what ideas they work on. New and relevant information could also be added to the ideas being executed which could help with making it easier for contributors to identify when there is an opportunity to generate more impact for the ecosystem by focussing on a different idea. The idea process can benefit from considering how it makes it easy for contributors to add and maintain important information about ideas so they can then more easily realign their contribution efforts towards the ideas that help generate the most impact.
* **Impactful ideas get executed** - The idea process should help with encouraging contributors to identify and execute the most promising ideas that could generate the most impact for the ecosystem.
* **Measurable outcomes** - Executed ideas that can demonstrate the impact they have generated will be useful for keeping voters well informed when making future funding decisions about where to disburse treasury assets.
## **Concerns**
* **Availability of contributors to execute** - The execution of promising ideas can only happen when suitable contributors are available to help with the contribution efforts required. The idea process will need to consider how the most promising ideas will also have the right contributors to help with the execution efforts. This factor will also mean an idea process will need to consider how many ideas should practically be encouraged and selected based on the actual capacity and funding available to compensate contributors who could then execute those ideas.
* **Leadership** - Complex ideas that are larger in scope might need the right leadership in place to ensure the execution of an idea is as intended and that problems are mitigated and resolved more effectively. An idea process will want to consider how leadership forms around ideas being suggested and how that leadership might need to change over time.
* **Idea information complexity** - Ideas can require a lot of information to explain and justify why the solution is promising. There is a risk that an idea process becomes overwhelmed with too many ideas and information if it does not effectively incentivise and encourage the submission of high quality submissions instead of a growing number of average submissions. Funding processes will need to think about how these ideas can be more easily communicated in a way that a sufficiently wide audience can interpret and understand what is being suggested and executed. Achieving this will be important for an ecosystem to make more informed decisions about how to disburse funds.
* **Accurate information updates** - Much of the information that gets added to an idea will focus on what is being executed over time. This information can be added by the contributors that are working on that idea. The idea process will need to consider how it encourages and verifies that these information updates are honest and correct. There is a risk that if the incentives are closely attached to ideas it could create a stronger incentive for contributors to exaggerate or lie when communicating how well an ideas execution is going if that meant it increased their chances of future compensation.
* **Changing idea complexity** - New information and knowledge or changing priorities can quickly influence whether an idea continues to make sense or not in the current environment. Ideas might need to change how they are executed due to this new information or learnings. An idea process can influence whether ideas can easily change and adapt over time and what processes are involved for making these changes. The idea process will need to be flexible enough to ensure contributors are able to respond to changing factors and environments and align their contribution efforts with making as much impact as possible.
* **Stifling other forms of innovation** - There are risks around stifling innovation if the selection of ideas that get executed are decided by a larger community. The larger the group of voters the higher the risk there is of groupthink and a reduction in awareness of the different ideas that might have been suggested. The idea process will need to be careful that it does not stifle innovation and novel ideas from being explored and executed.
* **Idea selection complexity** - As the number of ideas increase over time the complexity in choosing between those ideas can often also increase. This can make governance more complex as these ecosystems try to scale as the same voters would need to compare and vote on a larger number of ideas over time. The idea process will benefit from removing the duplication of ideas where possible and finding ways to keep ideas concise but sufficiently detailed so they can be easily compared with other ideas.
# Idea ownership approaches
Comparing the different approaches that could be used for idea ownership
The ownership of ideas can heavily influence how they will be governed, executed and maintained over time.
Some of these different idea ownership approaches include:
* [**Owned ideas with fixed leadership**](/ideas/idea-ownership-approaches/owned-ideas-with-fixed-leadership) - An idea is owned by a group of individuals and they make most or all of the decisions.
* [**Owned ideas with distributed decisions**](/ideas/idea-ownership-approaches/owned-ideas-with-distributed-decisions) - An idea is owned by some individuals but some decisions get distributed between other contributors or community members.
* [**Shared ideas with elected leadership**](/ideas/idea-ownership-approaches/shared-ideas-with-elected-leadership) - The idea is owned by the community and any leadership gets elected by the community.
* [**Shared ideas with emergent leadership**](/ideas/idea-ownership-approaches/shared-ideas-with-emergent-leadership) - The idea is owned by the community and any leadership is an emergent outcome that changes as needed.
To compare these approaches a number of [factors have been considered](broken://pages/yMiEAL2cRwqAiTmMq7QW) and then applied to each approach to better understand the potential advantages and drawbacks of each approach.
**Idea ownership approach analysis**
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[Broken mention](broken://pages/yMiEAL2cRwqAiTmMq7QW)
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[Owned ideas with fixed leadership](/ideas/idea-ownership-approaches/owned-ideas-with-fixed-leadership)
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[Owned ideas with distributed decisions](/ideas/idea-ownership-approaches/owned-ideas-with-distributed-decisions)
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[Shared ideas with elected leadership](/ideas/idea-ownership-approaches/shared-ideas-with-elected-leadership)
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[Shared ideas with emergent leadership](/ideas/idea-ownership-approaches/shared-ideas-with-emergent-leadership)
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## The importance of idea leadership
**Handling complex ideas**
The more complex an idea is, the more likely it is that strong leadership could be beneficial to take that idea from inception through to execution. As ideas grow in complexity the number of factors for consideration increase, factors that each need to be considered when making informed decisions. The larger the amount of variables for consideration the more difficult it can become for leadership to be distributed amongst a large group of people due to the complexity and amount of information each participant would need to digest and then apply to make their own informed decisions.
**Ideas that require highly specialised skill sets**
Some ideas require highly specialised skills to effectively execute an idea. Finding people who have these specialised skill sets can be difficult. Leadership which is highly informed around the ideas topic area can be important in these scenarios for helping create a suitable team that can execute the idea as intended.
**Choosing the right leadership is hard**
Selecting leadership is difficult irregardless of whether it is an owned or shared idea. An ecosystem would need to select the leadership either through selecting owned ideas which have the leadership predetermined or select the leadership for any already shared idea. Some difficulties around choosing leadership include:
* **Limited knowledge** - The voters who are selecting ideas with predetermined leadership or selecting the leadership for shared ideas will only have so much knowledge around the topic area for the idea. Voters can easily be lacking information that could help with more fully understanding whether the leadership is in fact suitable for executing a certain idea.
* **Interpersonal skills** - The voters may only see a small part of how the leadership interacts with the community and other contributors. It can be difficult to know ahead of time which leadership will interact and collaborate with other contributors and community members most effectively.
* **Fast changing environments** - An ecosystem itself can change rapidly, resulting in changing requirements in what will create impact for the ecosystem. Voters will often not know ahead of time how effective the leadership will be in being able to respond and handle these quickly changing factors.
## Owned ideas
**Advantages of idea ownership**
* **Decreases vision complexity** - Having a smaller number of owners responsible for an idea will help reduce the complexity in achieving clarity of vision for an idea as less people are involved in the decision making.
* **Decreases governance complexity** - A smaller number of owners for executing an idea can help with increasing the speed in which governance decisions are made as less people are participating that each need to be well informed to make decisions.
**Drawbacks of idea ownership**
* **Decreases change of leadership flexibility** - The owners of the idea cannot be changed by the community. The community would need to execute a similar idea with different leadership if they wanted to support other leadership or the existing leadership would need to voluntarily give ownership to other people themselves. An issue with this lack of flexibility is that as an idea is executed and grows into a more mature solution over time the requirements and skills needed to operate and keep improving that solution can change. A community would not be able to respond to these changing requirements and elect new leadership and instead would be reliant on the existing leadership involved being able to adapt to a changing environment and requirements.
* **Decreases contributor participation flexibility** - The owners of the idea will determine or at least highly influence who is involved in the execution of the idea. This could limit the amount of participation in the execution of an idea and the diversity of experimentation and thought involved.
* **Increases contribution outcome openness risks** - If owned ideas are competing for business opportunities there is a higher risk and likelihood that not all contribution outcomes such as software or other intellectual property is fully open sourced and made freely available. Owned ideas can encourage more competition over collaboration as sharing contributions outcomes publicly could likely reduce their competitive advantage.
**Other potentially emergent outcomes from funding contributor owned ideas**
* **Increased execution speed** - Handling the vision and governance decisions quickly can mean a higher focus of time is directed towards the execution of an idea and creating a solution. For some ideas the speed of execution could play an important role in determining whether a solution gains significant traction or not compared to alternative competing solutions.
**Why idea ownership might be preferred**
* **Business opportunities** - Having idea ownership can be effective when people want to address a business opportunity. A business opportunity could benefit from quicker decision making and a high clarity of vision so their executed solution can effectively fill the identified gap in the market.
## Shared ideas
**Advantages of shared idea ownership**
* **Increases change of leadership flexibility** - Shared ideas either have elected or emergent leadership meaning that it is easy for a community to decide on the leadership involved when it is needed. This helps prevent any centralising control of influence over the execution of ideas.
* **Increases contributor participation flexibility** - Shared ideas aren’t owned by a small group of individuals and any execution outcomes would be made fully open and public. Due to this there is much higher flexibility for contributors to participate in existing efforts on these shared ideas and also can easily work on their own variations and experiments by building upon existing work.
* **Removes contribution outcome openness risks** - Any contribution outcomes from shared ideas would be open source by default which removes the risk of different parts of the execution being centrally controlled and hidden from the rest of the ecosystem. A key benefit to this outcome is that it should help reduce duplication of efforts, any teams wanting to work on that topic area would be able continue and iterate on the work that has already been executed rather than having to do similar work themselves.
**Drawbacks of shared idea ownership**
* **Increases vision complexity** - Shared ideas increase the amount of community participation in governance of the execution of an idea, setting a clear vision can become more complex due to this increase of opinions and wider input. This could be problematic for more complex ideas where strong leadership can be beneficial if they have a strong grasp of the problems or opportunities they are addressing and have the right skills to help with effectively executing a solution. The importance of idea leadership is a reason why elected leadership for shared ideas can be considered as an important approach. Giving contributors some stewardship over important ideas can help with ensuring those ideas get executed more effectively.
* **Increases governance complexity** - The more that people are involved in the governance of the execution of an idea the more complex the decisions can become in handling the diversity of opinion and preferences. These scaling amounts of differences can make it more difficult to achieve alignment for the direction an idea should be taken when being executed.
**Other potentially emergent outcomes from funding contributors for shared ideas**
* **Increasing collaboration** - Shared ideas are owned by the community over a small number of individuals. This can help increase collaboration as the outcomes of any contribution efforts are publicly available for other people to iterate on and improve. Many people benefiting from the outcomes from contributing towards shared ideas can help with increasing the likelihood that those beneficiaries also support the execution of that idea as it is in their self interests to do so if they are also adopting those outcomes. Increasing the number of contributors involved in thinking about and supporting an idea could help increase the speed of problem solving, increase the diversity of thought and skills involved and also could be effective for encouraging continuous feedback.
* **Increasing solution approach diversity** - Execution outcomes such as source code being made publicly available will help with enabling any contributor in an ecosystem to create variations of that work to experiment with new solution approaches. Making these experiments easier to execute will create more data points and insights for the ecosystem to consider and respond to. More experimentation can help with more quickly finding the most optimum solution approaches.
* **Increase contributors flexibility to help with multiple ideas** - Contributing towards a more collaborative effort to execute different shared ideas could help with boosting individual motivation and morale due to a shared feeling of ownership and achievement for creating impactful outcomes. The flexibility for contributors to support the execution of one or many shared ideas could also help with enabling them to more quickly generate impactful outcomes by being able to allocate their time to where they are most needed in the ecosystem.
**When sharing the idea may be preferred**
* **Open source software** - Protocols, tooling and infrastructure that is openly available for other developers to use in an ecosystem can be massively valuable in making it easier for anyone to experiment with new ideas and improve their existing solutions. Teams that are considering whether to adopt certain software will often have a higher level of confidence in adopting software solutions that are fully open sourced and that are being actively contributed to by a wide number of community members.
* **Public goods** - Shared ideas provide an effective approach for creating public goods due to the lack of central ownership of the ideas being executed. Instead any value generated from the execution of a shared idea would be available for anyone in the ecosystem to benefit from. Openly available education, research, analysis and software are all potential example public goods that a treasury could support through funding.
## Preferred outcomes for Web3 ecosystems
**Importance of open source protocols, tooling & infrastructure**
Open source software plays an important role in Web3 ecosystems in allowing people to verify, trust and audit the code they are running. For this approach of open source software to scale there will be a need for emerging solutions to eventually turn themselves into fully open source projects. This factor means most ideas will need to migrate to a shared idea ownership model where there are no controlling owners that can conceal or revoke access to software or information that is relevant to the operation of the application, protocol, tooling or infrastructure that has been produced.
**Removing centralised control**
Another key trend in the Web3 movement is the empowerment of individuals to own their own money, data and digital identities rather than a small handful of corporate owners. These centralised actors are currently a potential point of failure. The leadership could become corrupt, malicious or incompetent over time. Mitigating these issues around centralised control will mean that any executed ideas will eventually need to change to become shared ideas that are owned by the community rather than a handful of individuals.
# Idea ownership factors for consideration
Factors for consideration for different idea ownership approaches
The [methodology](https://docs.treasuries.io/analysis/approach-comparison-methodology) used for this approach comparison is documented separately.
**Clarity of vision complexity**
* **Description** - The idea ownership approach will influence how the vision for an idea is determined and maintained over time.
* **Maximum score** - 5, Very important. This clarity around vision will influence what outcomes are prioritised from the different contributors involved in executing an idea. A higher clarity in vision can help with increasing alignment on what contributors are executing.
* **Scoring questions** - How easy would it be for a clear vision to be set and maintained? How will that vision get updated over time as the environment and external factors change? Who is involved in the decision making for setting the overall direction?
* **Scoring** - Low complexity is good (Score - 5). High complexity is bad (Score - 1).
**Governance decision complexity**
* **Description** - An idea will need governance to determine what direction to take, how the idea gets executed, and who is involved in the operation of that idea over time.
* **Maximum score** - 5, Very important. Making the right decisions to execute an idea will highly influence the potential impact of the contribution efforts made. The speed of decision making can be an important factor that influences the execution speed and how easy it is for voters to make informed decisions is another important factor that will influence what gets executed and how it gets measured for generating any impact.
* **Scoring questions** - How many people are involved in the decision making for executing an idea? How difficult is it for those voters to be well informed when making decisions? How long might it take for decisions to be made and how fast can the voters respond to a changing environment?
* **Scoring** - Low complexity is good (Score - 5). High complexity is bad (Score - 1).
**Change of leadership flexibility**
* **Description** - The idea ownership approach will influence how easy it is for the community to change the leadership involved in executing an idea.
* **Maximum score** - 5, Very important. Leadership can play a vital role in the execution of complex ideas however the community may prefer different leadership as the requirements and environment change. Some ideas also might not require leadership for a period of time due to the maturity of the solution that has been executed.
* **Scoring questions** - How easy is it to change the leadership involved in the execution and operation of an idea? How can a community support new leadership when it makes sense to do so? What steps would be required to execute that change?
* **Scoring** - Higher flexibility is good (Score - 5). Lower flexibility is bad (Score - 1).
**Contributor participation flexibility**
* **Description** - Idea ownership will influence how easy it is for different contributors to participate and help with the execution of an idea.
* **Maximum score** - 5, Very important. Ecosystems will benefit from competent and skilled contributors being able to participate in supporting important ideas which can help with creating impact for an ecosystem. The ownership approach may enable or prevent people from being able to contribute.
* **Scoring questions** - How difficult is it for a contributor to help with the execution of an idea? Do contributors need permission to contribute?
* **Scoring** - High flexibility is good (Score - 5). Low flexibility is bad (Score - 1).
**Openness of execution outcomes risks**
* **Description** - Idea ownership can influence the likelihood of whether all of the contribution outcomes are provided freely to the community such as open sourcing the code and processes or sharing any operational insights.
* **Maximum score** - 5, Very important. Making the contribution outcomes from executing an idea freely available means that other communities should be able to easily take those outcomes and iterate upon them to make further improvements. It also means that the ecosystem would be able to more quickly learn about how that idea can be better executed and what problems and opportunities might exist for future contribution efforts.
* **Scoring questions** - Why might the voters for governance decisions decide to not make contribution outcomes freely available? What amount of competition does the idea ownership approach often lead to?
* **Scoring** - Low openness risk is good (Score - 5). High openness risk is bad (Score - 1).
# Owned ideas with fixed leadership
**Overview**
Owned ideas with fixed leadership are where the creators keep full control over the vision for the idea, the approach for execution and the contributors involved. The owners of the idea will make all of the key decisions when executing the idea and govern all of the systems and processes involved.
**Very low clarity of vision complexity (Score - 5)**
The owners of the idea have full control over the direction of the idea and exactly how it gets executed. Full control over the vision between a smaller number of people will minimise the clarity of vision complexity. Other contributors or the community would not be able to dispute or overrule the owners decision making and would be reliant on them accepting any suggestions made. The potential issues with central ownership over the vision is it could easily lead to less experimentation, any suggestions for improvements and further testing must be approved by the owners of the idea.
**Very low governance decision complexity (Score - 5)**
Any governance decisions are made by the smaller number of owners for the idea meaning the complexity is at its lowest. Only a small number of people would need to be informed when making important decisions. The owners could also invite participation in the governance decisions from a wider audience within the ecosystem, however this would be at the full discretion of the leadership, who could also easily revoke this approach at any point.
**Very low change of leadership flexibility (Score - 1)**
The community and other contributors involved in the execution of an owned idea would not be able to change the leadership as it is fixed. The only way that leadership could be changed is if a similar idea was executed by another team or the leadership voluntarily decided to migrate ownership of the idea to someone else or the community.
**Very low contributor participation flexibility (Score - 1)**
Contributors who are looking to participate in the idea would be reliant on the owners of the idea accepting their offer to contribute, the owners of the idea could also likely have been openly inviting contributors to join at that time.
**Very high openness of execution outcomes risks (Score - 1)**
If the owned idea is competing as a business opportunity there is a much higher risk that some or all of the contribution outcomes are not made publicly available. If there is source code or proprietary information that gives that team an advantage in the market they are less likely to share that publicly for the good of the community as this would reduce or even remove their advantage. Higher competition between competing teams could also lead to less collaboration and higher duplicated efforts.
**Total score = 13 / 25**
# Owned ideas with distributed decisions
**Overview**
Owned ideas with distributed decisions are when the ideas are still owned by the creators of the idea however some or many of the decisions concerning the operation and execution of the idea have been distributed to community members.
**Low clarity of vision complexity (Score - 4)**
The owners of the idea could still have full control over the idea under this approach however some parts of the governance could have been pushed towards the community. For instance prioritisation or contributor selection could have become on-chain votes. Inviting more community members to participate in setting the direction of an idea can lead to higher complexities for that community to come to consensus around direction.
**Low governance decision complexity (Score - 4)**
Governance decisions could be made by the idea owners or by the community under this approach. Some or many of the decisions could have been directed towards the community which would increase the complexity of governance but would also make the process more inclusive and representative of the communities preferences. In these situations the idea owners may still hold admin keys and the authority to revoke certain processes if they are not functioning well as the idea is still ultimately owned by the creators.
**Low change of leadership flexibility (Score - 2)**
The community and other contributors involved in the execution of an owned idea would still not be able to change the leadership under this approach as it is still fixed. If certain decisions have been pushed to the community there could however be some flexibility for an ecosystem to influence the prioritisation and contributors involved in the execution of an idea.
**Moderate contributor participation flexibility (Score - 3)**
If processes around contributor selection and prioritisation get pushed towards community decision making the ability for different contributors to participate will increase. Distributing the decision making also makes it easier for a wider range of the community to participate in governance. This participation flexibility is limited to the decisions that have been distributed and is also reliant on the leadership not revoking those processes and decision making in the future.
**High openness of execution outcomes risks (Score - 2)**
If the owned idea is competing as a business opportunity there is a much higher risk that some or all of the contribution outcomes are not made publicly available. If there is source code or proprietary information that gives a team an advantage in the market they are less likely to share that publicly for the good of the community as this would reduce or remove their advantage. This risk could be reduced somewhat through distributed decisions as if community members interested in numerous similar ideas are able to contribute towards these ideas they might be able to generate an increased amount of openness for any contribution outcomes they help generate.
**Total score = 15 / 25**
# Shared ideas with elected leadership
**Overview**
Shared ideas with elected leadership can occur when the community is suggested an idea from members of the community and the leadership involved in managing the execution of the idea gets elected by that community. Any outcomes from the execution of that idea are not owned by the individuals involved in execution and instead the outcomes are for the benefit of the community.
**Low clarity of vision complexity (Score - 4)**
The election of leadership can help with lowering the complexity of achieving clarity of vision about the execution of an idea. The leadership could be responsible for making key decisions about the direction, execution and operation of an idea. Elected leadership could share a similar amount of complexity as owned ideas as the leadership in both ownership approaches will need to consider any community suggestions and feedback.
**Moderate governance decision complexity (Score - 3)**
A moderate amount of complexity would come from any decisions that get distributed across the wider community. Leadership that is elected could help with reducing the complexity for governance decisions that are more complex. As leadership would be elected there is further emphasis on the importance for leadership to respond to and represent the needs of the community who elected that leadership in the first place. Elected leadership for a shared idea could help with simplifying and guiding the governance processes however adopting an election based approach would help with making them more responsible for involving community opinion and suggestions.
**Very high change of leadership flexibility (Score - 5)**
If the community is unhappy with the leadership that is operating and executing an idea they would be able to elect new leadership to take over their responsibilities.
**High contributor participation flexibility (Score - 4)**
The elected leadership could be given responsibility for choosing which contributors are most suitable for working on the execution of an idea. This might be a suitable approach for more complex ideas where having too many contributors could be problematic. Leadership that is elected by the community will have an even greater need to be thorough in their decision making when deciding which contributors should join the execution efforts. Any decisions made that are deemed unfair could result in different leadership being elected. This can help increase the likelihood of contributors having high flexibility to join the execution of any shared idea providing they are able to show sufficient evidence that they would be a valuable contributor.
**Very low openness of execution outcomes risks (Score - 5)**
A shared idea is owned by the community meaning all contribution outcomes would be made public and freely available. This means all software, processes and insights should be open sourced and freely available. Any contribution outcomes are available for anyone in the community to iterate and experiment on themselves.
**Total score = 21 / 25**
# Shared ideas with emergent leadership
**Overview**
Shared ideas with emergent leadership occur when the community has shared ownership of any of the ideas being suggested by members of that community and any leadership for those ideas is an emergent outcome that happens naturally rather than through election and that could change at any time.
**Very high clarity of vision complexity (Score - 1)**
No elected leadership means the community would need to decide the direction of any idea. This means the maximum number of participants could be involved in setting direction which could result in a very high complexity to reach alignment towards a shared vision. Having no official leadership could be challenging in situations where the idea complexity is high.
**Very high governance decision complexity (Score - 1)**
Complexity would be at its highest for decision making as the entire community would be able to participate in the decisions being made about the execution of the idea. This is effective for ensuring decisions are more representative but also comes with the cost of higher complexity in making those decisions. A large number of community members would now need to be well informed to make good decisions on how an idea should be executed and operated.
**Very high change of leadership flexibility (Score - 5)**
Leadership is not elected under this shared ideas ownership approach, decisions would be governed by the community, contributors may lead some of these efforts to help guide the execution but they would not be elected to be any form of authority over decisions.
**Very high contributor participation flexibility (Score - 5)**
A shared idea with emergent leadership would mean that any contributor could participate in supporting the execution of that idea. Contributors who are doing any sizable amount of work could be elected and compensated through the treasury. No small group of individuals or leadership would prevent anyone from being able to contribute towards an idea.
**Very low openness of execution outcomes risks (Score - 5)**
A shared idea is owned by the community meaning all contribution outcomes would be made public and freely available. This means all software, processes and insights should be open sourced and freely available. Any contribution outcomes are available for anyone in the community to iterate and experiment on themselves.
**Total score = 17 / 25**
# Idea execution considerations
Some considerations about the execution of ideas across a Web3 ecosystem
There is a wide variety of different ideas that could be executed in Web3 ecosystems that each could benefit an ecosystem in different ways. Thinking about the different types of ideas that could be executed can help with thinking about the differences they might have in scope, how ideas might have many intersecting solutions and how contribution efforts could be started and paused on ideas at different times during execution.
**Idea examples**
There are a wide variety of different ideas that could be executed to benefit a Web3 ecosystem:
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[Idea examples](/ideas/idea-execution-considerations/idea-examples)
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## Idea execution considerations
**Different idea scopes**
The scope of contribution effort required to execute an idea could range from being small to very large. One software solution could be a very simple utility solution that solves a common use case for different projects, this idea might only take a few weeks to develop with one or two contributors. Another software solution could take multiple months to execute, such as a transaction building library that helps to optimise and reduce the fees required when making more complex multi application transactions.
A funding process can benefit from considering how these different scopes ideas are supported and incentivised. If an ecosystem attaches the incentives to the idea process it will need to think about how that process handles the funding of different scoped ideas. For smaller ideas it could be more challenging to scale the voter participation to a large population if there is a large amount of these smaller ideas that could be executed. All of those ideas would need to be reviewed and voted on. Using contributor time based incentives is one way that this problem can be avoided as contributors are able to allocate their time to any number of small ideas whilst executing any existing idea and would not need to get funding for each idea that they suggest.
**Intersecting solutions between ideas**
Many ideas are not fully executed in isolation without the use of external solutions. Ideas often rely on and integrate with many different solutions and processes to increase the speed of execution and the reliability and effectiveness of their own solution. For instance many DApps could rely on the same utility libraries, wallet integrations or data oracles. A funding process can benefit from considering how it can help to enable a more collaborative effort to identify the shared problems and opportunities that exist between the protocols and applications being developed. If each group of contributors working on different ideas make their own solution to the same problem there is a higher likelihood that their contribution efforts are being wasted due to a large amount of duplicated outcomes from building similar solutions.
**Idea contribution allocation changes**
Ideas can become more or less important over time based on the surrounding environment and needs of an ecosystem. Some ideas might also not need further execution efforts if the current executed idea delivers on any expected outcomes. For instance a utility library for building transactions that is used by numerous applications may not need to be updated for a long period of time. That same library could also suddenly benefit from a new set of features to address new use cases that are now required by different applications. A funding process can benefit from making it easier for contributors to migrate their contribution efforts to the ideas that have the highest opportunity to make impact for the ecosystem. This means the execution of some ideas may get paused so that those efforts can be directed towards other more impactful ideas. An executed idea, such as a utility software library, that doesn’t have any additional requirements from the other projects would be a good example of an idea that could be paused in terms of its execution. Contributors involved in the diversity of these ideas can benefit from being able to easily allocate their efforts to other ideas when the requirements change and further contribution effort is needed.
## Key takeaways
**Idea sharing & openness**
A Web3 ecosystem can have many ideas that have intersecting problems and opportunities that each could be executed as separate ideas collaboratively. A funding process can benefit from making it as easy as possible for community members to share and discuss different ideas so that these points of intersection can be more easily identified. More collaboration and higher quality shared solutions could then be more easily created due to this openness and frequent communication.
**Importance of flexibility**
Impactful ideas could be identified at any point in time whether that’s during exploratory planning phases of an existing idea or during the execution of another idea. Contributors will struggle to predict every idea that could be impactful ahead of time. A funding process can benefit from making a flexible environment for contributors so they are more easily able to respond to these changing environments. This is one reasons why attaching the incentives to contributors can be an effective way for ecosystems to handle fast changing environments where impactful ideas can suddenly emerge that could be beneficial to immediately execute for the benefit of the ecosystem.
**Incentive alignment**
Ideas can emerge at any time and the contribution efforts required for an idea can start and stop based on the changing needs of each idea. Ecosystems that want to enable a faster changing allocation of contribution effort between many ideas will need to consider how the incentives are attached to the execution of those ideas. If incentives are attached to ideas then the funding process will need to find a way to become faster at handling submissions, selection and funding so that contributors can act quickly enough on executing impactful ideas. The benefit of attaching incentives to contributors is that they would be able to respond to these changing requirements immediately as they emerge. How incentives get handled in funding can make it easier or more complex for contributors to allocate their efforts to different ideas.
**Persistence of idea information & outcomes**
The large amount of intersecting solutions between ideas that can help to support and speed up the execution of ideas can help with highlighting the need for information about ideas to be shared widely across an ecosystem. Information about these ideas and the shared problems and opportunities can persist and be shared to future contributors for consideration when suggesting and executing their own ideas. Future ideas could benefit from adopting the outcomes from the ideas that have already been executed to help with improving their own execution speed and outcomes. Persistent information about the outcomes of previously executed ideas can improve the quality of future ideas due to those shared learnings.
# Idea examples
List of different types of idea that could be executed in a Web3 ecosystem
The following are some different ideas that could be suggested during funding. Each could help with solving different problems an ecosystem is having or they could help with addressing certain opportunities. This list is not exhaustive and instead just provides some example ideas.
**Technical**
* Network infrastructure tools and changes
* Protocol development
* DApps application
* Smart contract development
* Security reviews & code audits
* Bug fixes & bug bounties
* Hackathons
* Tools, libraries & SDKs
* Technical research & analysis
* Interoperability solutions
* Data oracles, indexers & explorers
* Scalability solutions
**Community & education**
* Articles & blog posts
* Community events & hosted discussions
* Public outreach
* Government outreach & engagement
* Interviews & podcasts
* Demos & onboarding resources
* Community and contributor mentorship
* Community hubs
* Workshops & courses
* Ecosystem educational resources
* Translation support
**Products**
* DeFi
* Gaming
* National governance systems
* Climate change solutions
* Transport & logistics
* Social media
* Marketplaces
* Insurance
* Mediation
* Legal
* Healthcare
* Wallets
* Metaverse
* Business software
* AI
* Hardware
* Real world assets (RWA)
* …Many others!
**Research & development**
* Research & analysis
* Academic research & review
* Standardisation
# Contributor process
Overview about the importance of a contributor process for funding
Contributors help with the execution of the most promising ideas that can generate impact for the ecosystem. One of the most important parts of disbursing treasury assets is deciding which contributors are the most suitable to help with execution efforts. Attracting, selecting and retaining high quality contributors can drastically help with speeding up the evolution and improvement of an ecosystem over the long term.
Addressing ecosystem priorities and creating impact is achievable when the right initiatives get executed and improved over time. An ecosystem will need to decide which potential contributors are most suitable for executing the most promising ideas. Many funding processes will choose to adopt some form of contribution verification process to ensure that progress is being made by the funded contributors working on these ideas. The outcomes generated by any contribution efforts can help with creating more data and insights about what’s working and what isn’t, and could also help with improving how contributors work together. These learnings can then be fed back into the ongoing funding process to improve how future funds get allocated. Ecosystems that are effective at attracting and retaining high quality contributors should be able to execute and evolve their ecosystems at a faster rate than competing ecosystems.
## Process steps
* **Submitting contributor information** - People that are interested in being compensated by a funding process to help with execution efforts will want to share their relevant professional and background information to showcase why they would be suitable candidates for the ecosystem to consider.
* **Selecting contributors** - The process for an ecosystem looking to select contributors would start with considering the educational and professional background of those who would like to contribute along with any information around their recent contributions or involvement in the ecosystem with any other relevant experience. Voters would then need to compare these contributors against the priorities and ideas currently preferred by the ecosystem and determine which of these contributors would be a good fit for helping to address the priorities and execute promising ideas. Selected contributors would be compensated for their contribution efforts in executing ideas.
* **Execution of ideas** - The next phase is to start executing any ideas and collaborating with relevant contributors and communities that might benefit from those executed ideas. Contributors will need to determine who has any control or influence over different parts of the execution efforts and where any checks and balances might be needed. More complex ideas may often require competent leadership that can handle the nuances of planning and coordinating a more complex project.
* **Improving contribution process** - The selected contributors will need to reflect and improve how they approach the execution of ideas on an ongoing basis. This can include reflecting on what the current best practices are, how to best communicate and coordinate with each other, how low level priorities and goals are set and how to mitigate potential future issues amongst numerous other considerations. Contributors will need to strike a balance between focussing on getting work done with updating their operating approach and following best practices.
* **Measuring outcomes** - The contribution history, performance and impact that a contributor makes can generate insightful data that helps to inform an ecosystem on which contributors helped to generate the most impact. Measuring these types of outcomes can help with future decision making on which contributors should be selected again.
## **Desirable outcomes**
* **Inclusive** - High quality contributors could come from any background and geographic location. The process for submitting contributor information can benefit from inviting submissions from a full diversity of different people with different skill sets so that the voters are able to select from a range of potential candidates. Ensuring that the opportunities are available to a wider amount of potential contributors will help with increasing the chances that the contributors that get selected are both skilled and also more representative of the diversity that exists in the community.
* **Attract & retain quality contributors** - The contributor process wants to offer the right incentives to meaningfully attract and retain high quality contributors to the ecosystem. Retaining high quality contributors can have a compounding impact on an ecosystem's growth as their knowledge and skill sets make them more performant and useful to the ecosystem over time. Getting the incentives, culture and working environment right for contributors can make the difference between where contributors allocate their contribution efforts.
* **Well maintained contributor information** - The contributor process can help with encouraging contributors to keep their personal and professional information up to date along with any of their contributions they make. Making the ecosystem aware of the information available about each potential contributor can help with improving the communities decision making ability to select the best contributors to help execute promising ideas.
* **Tracked contribution outcomes** - Voters benefit from seeing the contribution outcomes made by the contributors that have been previously selected and compensated to help with execution. The contribution process will need to consider how it identifies poor performers and how it retains and rewards high performing contributors.
## **Concerns**
* **Unavailable skill sets** - A contributor process needs to consider the risks around not having the right skill sets available to execute ideas as intended. How different skill sets are incentivised to participate in the ecosystem could influence the amount of contributors there are for each skill set. A balance will need to be struck on selecting the amount of contributors for each of the skills that are needed to execute impactful initiatives.
* **Inaccurate skill levels** - Contributors have an incentive to exaggerate their own skill level and ability to increase the chances that they get selected and compensated. The contributor process will need to think about how any claims submitted by contributors can be automatically verified or whether other forms of incentives are needed to manually moderate the contributors submitted information.
* **Biased & missing information** - Contributors have an incentive to exaggerate their competencies or the impact they have generated to secure future funding from the treasury. The process for selecting contributors will benefit from making it clear who added the information and which pieces of information are factual and have been verified.
* **Replacing poor contributors** - How contributors are incentivised and the terms of engagement that get adopted will influence how easy it is for the ecosystem to remove poor contributors over time. If an ecosystem elected people in perpetuity to receive compensation for their contribution efforts there would be the problem where a vote would be needed to remove that contributor. This is one reason why term based contribution periods could be beneficial however if these term lengths are too short this reduces the contributors financial stability. The approach for incentivising contributors will need to balance the need to attract high quality contributors with sufficient income stability against ensuring the ecosystem has an easy and effective ability to remove and replace existing contributors who aren’t performing.
* **Team synergies** - The contributor process can influence how teams are formed and selected which can influence the synergy between the contributors in each team and between different teams. The contributor process will want to consider how these teams can form and how leadership emerges so that a collaborative environment can be supported. Another risk exists around how long contributors are working on certain ideas or being replaced by other contributors. An environment that keeps changing the contributors who are involved in the execution efforts risks those teams being less performant due to a need to rebuild team rapport and working structures each time the team dynamic gets changed. Treasury funding will need to factor in how it can retain high quality contributors and also minimise the disruption of highly performant teams.
* **Need for flexibility to change execution** - New information and knowledge as well as changing priorities and ideas could occur at any time during the execution of any initiative. In fast changing environments such as Web3 ecosystems the contributors who are executing ideas will need to be responsive to the changing environment and needs of an ecosystem to better align their efforts with creating impactful outcomes. The contributor process will need to consider how it supports this need for flexibility in where contributors are allocating their time to generate impact.
* **Measuring performance & impact complexity** - Each contributor can have a very different set of skills and value that they bring to an ecosystem. A contributor process will want to find ways to capture these different ways of impact generation so that impactful contributors can be recognised and rewarded.
# Self sovereign identity opportunities
Self sovereign identity solutions could help with creating a range of impactful outcomes for Web3 ecosystem. The following is a list of different opportunities that could be explored.
**Elected contributor credentials**
If contributors are selected for funding during funding they could be issued a credential to prove they are an active contributor for a certain period of time.
* **Read & write access** - Credentials could become an access control tool to enable contributors to make documentation changes, code commits and pull requests into code repositories amongst other areas of work.
* **Contributor voting** - Contributors could conduct votes to make decisions about their allocation of contribution effort or for implementation decisions.
* **Reviews & work sign off** - A contributor could sign off another persons work an agree that it’s completed or that it meets a certain quality threshold by issuing a credential.
* **Proof of payment** - Attaching relevant wallet addresses to a digital identity could provide proof of any payments made from the treasury to a given contributor.
**Reputation building**
Credentials could turn into a great tool set for enabling contributors to build up their own reputation.
* **Contribution history** - As contributions are recorded any ongoing build up of these contribution based credentials can help with building up someones reputation.
* **Impact generated** - Credentials can help with linking someones contribution efforts to specific ideas they worked on. This evidence of what ideas a contributor has worked on provides a direct path for a community to identify which contributors have helped to execute the most impactful ideas.
* **Exact contribution outcomes** - The aggregation of someones credentials could help to provide evidence about the exact total amount of contributions they have made for an ecosystem. This could be useful for understanding the distribution of effort they have made across many different areas whilst working in each ecosystem.
* **Total contribution time** - The time spent making contribution efforts could be recorded through the usage of credentials such as a monthly contribution log which could be verified by different sources of contribution. This could be used to providence evidence of the total amount of time someone has spent contributing.
**Education & skills credentials**
* **Bachelor, masters and doctorate degrees** - University degrees may soon be provided as verifiable credentials that other people can then use to verify someones educational certifications.
* **Skills credentials** - Credentials could demonstrate someone has competencies in certain skills whether online or from in person verification.
**Contributor attestations**
Credentials could be issued peer to peer by contributors to each other.
* **Mentorship & support** - Someone could create an attestation to provide some evidence that another contributor has helped them with mentoring and support.
* **Skill & performance** - Contributors could vouch for someones skill and performance by vouching for it through a credential they issue them. This could be useful for highly technical pieces of work where there is a more limited number of people who can verify the quality of someones work.
**Community attestations**
Community members could issue credentials about contributors in the ecosystem to share useful information about those individuals and their contributions.
* **Gratitude** - Community members could have a gratitude based credential for sharing stories and experiences they have had with a contributor that could be valuable for the community to know about.
* **Skill & performance** - Community members may have observed certain skills and performance outcomes from certain contributors and want to leave feedback or their thoughts in the form of a credential. This could help with providing the contributor more evidence to show what other people have said about them.
* **Impact** - Community members may want to document the impact that someone has made by issuing them a credential with that information. This could be useful for situations where the impact is not numerically easy to document and verify. Some contribution efforts could lead to more qualitative outcomes such as improving the culture in the community. Credentials could be a way to record these types of contributions and outcomes.
**Privacy preserving**
* **Zero knowledge proofs** - Contributors should be able to prove facts about themselves without fully revealing all of their credentials and personal information. Zero knowledge proofs can help with enabling people to keep their personal information about their health, age and medical history more private whilst still being able to prove certain things such as that they are above a certain age. This extends to professional information where a contributor may want to prove they have worked with certain clients but don’t want to reveal the full details about the agreement and transactions.
**Cross-platform identity solutions**
* **Self sovereign data ownership** - Self sovereign identity standards help with enabling solutions that can be more interoperable across many ecosystems. Following these specifications can mean that one contributor should be able to take their credentials and the reputation they have built and then use those same credentials in other ecosystems. This outcome is great for contributors as they now can maintain a single identity and can move to other ecosystems more easily with the reputation they have built up across one or many ecosystems.
## Synergies with funding approaches & suggestions
**Contribution approaches - Independent submissions**
Keeping the submission of information used in a funding process separate means that contributors will be more easily be able to start building their own reputation by making contributions in different areas and recording those contributions immediately on their own profile. Enabling a contributor to build up their reputation regardless of what’s happening in the funding process can better enable those contributors to more easily compete with the existing funded contributors when they request funding in the future.
**Decision approaches - All approaches**
Having good identity solutions integrated into the funding process could make it easier for any of the different decision approaches that have been already identified. Voters would be able to access more reliable and up to date information about different contribution efforts people are making and what impact they are generating. More access to this information can help with improving funding decisions about where funds could be more effectively allocated. Identity solutions are particularly useful for the delegated idea selection approach as it would help take an already more scalable approach for voters and now make it even more scalable by making it quicker and easier for them to have confidence in the reputation and capabilities of the different contributors. Sophisticated and accurate identity solutions make it easier for community members to participate and become more well informed when selecting contributors to help with execution.
**Incentive approaches - Contributor time incentives**
If the incentives are attached to an individuals contribution efforts instead of priorities and ideas the contributor is able to direct their efforts towards the most impactful initiatives. Increasing the usage and quality of credentials that can be issued could offer a great way for contributors to prove the value they have been creating by helping in numerous areas across the ecosystem and receiving credentials to prove that contribution. This could mean having attestations about contributor mentorship or for helping with difficult technical challenges across multiple ideas. The easier it is for a contributor to get these credentials the faster they will be able to build up their reputation and provide evidence of the impact they have generated.
**Contribution verification approaches - Individual time based contribution logs**
Integrating self sovereign identity solutions into a contribution verification process has a big opportunity for making it easier to verify which contributors did which piece of work with a mixture of self attestations, peer to peer attestations and automatically issued credentials from digitally verifiable sources. Increased accuracy of contribution history helps to greatly support the individual time based contribution logs approach by making it easier for this process to be improved, automated and scaled over time once the right tools and processes get developed.
**Impact measurement approaches - Contributor impact measurement**
Self sovereign identity solutions could help with capturing a wide range of information that can be relevant to a contributor. Being able to attach different pieces of contribution history and evidence about the impact a contributor has made can help a community more easily determine which contributors have been the most performant and impactful. Self sovereign identity solutions can help to realise some of the future impact opportunities that exist with being able to determine which contributors have been the most impactful for the ecosystem.
**Voter preferences & opinions - All community feedback**
Community feedback about any of the information submitted during funding could help with identifying problems, new ideas and different approaches that are worth considering. Credentials could be a great addition to this feedback process as now community members could verify and prove that they have given feedback to a range of different areas. Community members engagement and participation in the funding process could help them build up their own reputation in one or many ecosystems based on the quality of their feedback and suggestions.
# Contribution verification
Exploring the opportunities and importance of contribution verification
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Web3 treasuries have been increasing in value over time as ecosystems continue to grow and get more adoption. The amount of funding that Web3 ecosystems are disbursing each year is also often increasing. Ideas that a community wants to execute can often take longer than a month's worth of contribution effort. Complex ideas can require multiple months or years of contribution effort and involve numerous phases of development.
Ecosystems that are disbursing larger amounts of assets upfront to pay for executing different ideas can face a growing risk that the contributors involved in executing those ideas start to misuse or steal the funding they receive. The larger the amount of funding being distributed the larger the incentive there is to misuse or steal these assets.
Recording and verifying peoples contribution efforts can help with reducing this problem of misuse and theft of treasury assets. Instead of disbursing a large amount of assets in a single transaction an ecosystem could instead distribute funding over a number of smaller increments. Splitting up the payment for contribution efforts into different milestones or time periods means that any recorded contribution effort can be verified and measured before future funding is then released. This enables an ecosystem to check that their treasury assets are being used for purposes that they were intended for. Contribution verification can help an ecosystem with better identifying bad actors or poor performers that could be wasting or misusing treasury assets.
As Web3 ecosystem treasuries continue to grow in size the importance of managing and disbursing these assets effectively will also continue to increase. Contribution verification is a foundational reason why contribution efforts should be recorded and verified so that treasury assets are better protected and used as intended.
## Contribution log usage
Contribution logs represent a record of the recent contribution efforts that an individual or project team has made over a certain time period or they could capture the efforts involved in completing a certain milestone. Contribution logs could be used across Web3 ecosystems in a number of ways.
**Contribution verification**
Contribution verification is one of the reasons to record contribution efforts that we just mentioned already. Contribution logs help to enable an ecosystem to verify contribution efforts. This verification can help Web3 ecosystems with ensuring that treasury assets are being used as intended and not being misused or stolen.
**Performance measurement**
Contribution logs could help with measuring and comparing the contribution efforts from different contributors and teams. Increasing contribution measurability can help with identifying the most performant contributors and teams based on the quality and consistency of their contribution efforts. Contribution logs could help with increasing the accuracy of measuring the performance of individuals and teams. Top performing contributors could then be more easily rewarded.
**Impact measurement**
Some contribution efforts can lead to more impactful outcomes than others. Knowing which contributors and teams are responsible for each contribution outcome can help with identifying the contributors who have been the most consistent and effective at allocating their time towards initiatives that have helped with generating the most impact for the ecosystem. Contributors who are more effective and consistent at generating impact could be increasingly rewarded for their contribution efforts.
**Reputation building**
Contribution logs can be a great way for contributors and teams to build up their reputation and showcase their skill sets across different areas. Recording contribution efforts so that other people can verify those contributions means it can become easier over time for anyone to identify who has what skill sets and competencies. Contributors that build up a reputation of being highly performant through a provable history of contribution effort could use their reputation to more easily move to projects and ecosystems that they want to work in. Contribution logs could replace CVs and interviews as they can provide a more verifiable and useful information source to review someones professional background and competencies. A software developer could decide to make contributions to an ecosystem's code base that help to prove their competencies through their open source code commits. This could replace the need for them to take a tech test in an interview process. These code contributions are beneficial to the contributor as a way to build up their own reputation, it’s beneficial for the ecosystem as it receives impactful contributions and it’s valuable for projects interested in working with this software developer as they get to see how the developer makes contribution in real life scenarios.
**Social trust networks**
Contributors could make attestations about other contributors. These could be comments, reviews or statements about someones contribution efforts. Attestations could provide valuable information and insights about each contributor. Interlinking connections between contributors and the different contribution related information could then help to build a form of trust based network where people can more easily collaborate with other contributors due to the mutual connections they both share and the attestations those contributors have received from their shared connections.
**Detailed contribution insights**
Having an increasingly comprehensive record of contribution efforts could help with creating highly insightful information about an individual contributor or a cohort of contributors. Contribution log data could be useful for looking at a cohort of contributors overall performance and their impact over a set time period or for identifying any gaps in contribution effort or skill sets that might be missing.
**Historical contribution comparisons**
Recording contribution efforts that can be compared with other contribution efforts means that better historical comparisons can be made. These comparisons could become increasingly useful to an ecosystem. An ecosystem could look at how the overall performance of contributors is changing over time as different factors change such as the amount of compensation being offered, the tools, processes and infrastructure that they’re using, the total number of contributors in the ecosystem and the average duration of each contributor's participation. Making contribution outcomes easier to compare makes it possible for an ecosystem to identify any trends more accurately and then determine which approaches and outcomes are most correlated with improving contributor performance. If an ecosystem introduced a new incentive to improve the performance of contributors, having a way to easily measure the change in output over time would be highly insightful for determining whether that new incentive was actually effective or not.
## **Contribution verification analysis**
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[Current landscape](/contributions/contribution-verification/current-landscape)
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[Recording & measuring contribution efforts](/contributions/contribution-verification/recording-and-measuring-contribution-efforts)
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[Individual monthly contribution logs](/contributions/contribution-verification/individual-monthly-contribution-logs)
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# Current landscape
How contribution is often measured in company and sport environments
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## **Company contribution measurement**
Each company could approach contribution measurement and verification very differently. On one side of the scale some companies might have no or very few processes in place for verifying employee contribution efforts. These companies often rely more on observations made by leadership and management which can be a faster and simpler approach to get started with. Smaller companies may use more of an observational approach due to its simplicity and when they have a limited number of contribution efforts from different employees to review. Observations have an upper limit for how measurable they are due to the fact that the people doing the observing have a limited amount of time and capacity to observe each and every employee and what they’re working on. Some companies will introduce more formal processes to better record and measure each employees contribution efforts. Formal processes for measuring contribution effort could help a company with identifying and rewarding high performing contributors. Processes for reviewing contribution efforts and performance can become increasingly more important for larger teams and bigger companies due to the complexity of working out how peoples compensation should change over time and which employees have been the most performant and impactful. If top performers are not adequately recognised and rewarded there is a risk they become demotivated or simply move to another company. The problem with making observations about someone's contribution efforts is it requires a higher amount of trust in the management and leadership's decision making. These observations could be deciding what employees are paid based on their contribution efforts. Relying solely on observations can come at the expense of the accuracy in measuring each person's contribution efforts and can introduce the risk that some employees do not get compensated fairly for their performance or that the leadership is biased towards certain individuals over others. Companies that do introduce processes for measuring contribution efforts and performance benefit from making it clearer to employees what efforts and outcomes are most valuable for the company. Rewarding top performers could come in the form of job promotions or salary increases based on skill based pay bands. It could also include bonuses or stock options. Companies with more structure and process could be more accurate with grouping employees into different skill level groupings and performance thresholds however these processes can also be limiting for employees who exceed those expectations or their contributions and overall performance is not well captured in a more rigid process.
**Issues with company contribution measurement**
* **Easier exploitation** - For companies that use more observations and trust in the leadership instead of a formal process for measuring performance and contribution efforts there is an increased risk that employees could be exploited for their skills and performance as they would be relying on another person's judgement rather than a defined performance process. Leadership could try to retain more revenue for the business or inaccurately review someones performance and contributions. Employees might need to dispute the leadership's judgement if they felt like they deserved more compensation due to their performance.
* **Lack of measurement accuracy** - Companies that rely on observations for verifying employee contribution efforts and performance have an increased risk of lower accuracy around compensation decisions due to a lack of awareness and understanding of each person's contributions and performance. A lack of process means the company would be relying heavily on observations and contribution outcomes. These observations could lack the full information and context needed to know what has actually happened.
* **Lack of public and self owned contribution logs** - Contribution efforts that aren’t publicly recorded and owned by the employees mean there is limited value in these contribution logs for the employees. Employees could have benefited from being able to prove that they have made certain contributions for the business that they could then showcase to others across the company or even to other external companies. One obvious reason that companies would not inherently want this openness of competencies and performance is because it would increase the potential risk that other companies try to pouch their top performing talent. That approach might be good for the business, but it is not beneficial for the contributor.
* **Separate process for leadership and management** - Some companies might not apply the same verification process for measuring contribution efforts and performance with management and leadership as they do with employees. This can be unfair for employees as each person's contributions to the company are not being treated equally in terms of how they are recorded, measured and verified. A lack of equal process can lead to inaccurate or unfair compensation outcomes. Employees could have been far more performant and impactful than the leadership roles yet the employees might not receive fair recognition and compensation for their contribution efforts.
* **Rigid incentive process** - Companies that do have a thorough process for measuring and verifying contribution efforts have the risk that their process could be overly rigid. Some employees may exceed the value and expectations of defined compensation thresholds or generate impact in ways that aren’t well accounted for in the current contribution measurement process. Making a process that is flexible enough to handle different outcomes and varied contribution efforts would be an important part of rewarding the top performers fairly and aligning the incentives with the employees who have been the most performant and impactful.
## **Professional sports contribution measurement**
Professional sports can provide a useful comparison to company environments due to how contribution efforts are measured. Sports are inherently far more easy to measure than many employee roles found in company environments. Sports have a clear objective in what efforts often help with generating a winning outcome. Individuals involved in these sports can have their contribution efforts measured accurately to determine how they contributed towards generating a winning outcome. Football, or soccer, is a great example to consider. Each team member's contributions can be measured such as how long they have the ball, the number of passes, the number of shots and shots on target, the number of ball interceptions and then many more different metrics. These numerical measurements can then be paired up with visually recorded data about how these players move around the pitch, how good their awareness is of team mates and competing players and how they interact and collaborate with other players on the pitch. The value in all of these measurements is that these players can be more easily grouped based on their performance. Measurable performance can then lead to an increase in compensation for the top performers. Sports athletes, especially those in team sports, benefit from their contribution measurements being fully public and widely accessible as now every other team and anyone else in the world can easily verify someone's performance and the impact they made whilst playing for a team.
**Top performing contributors**
An important part of making a great team is identifying and retaining the top performing players. Top performing sports athletes can often be paid a meaningful amount more than other athletes. For individual sports the contribution measurement is not as valuable as team environments as the individual is responsible entirely for any wins or losses. Their contribution efforts don’t need to be measured and compared with other team members. For team sports, contribution measurement is highly valuable and important. If a team wins it is beneficial to understand which players have been the most performant and effective at helping that team win. Measuring a players contribution efforts effectively will help with identifying the most impactful players. These players can then be increasingly compensated for their high performance.
## Comparisons between sports teams and company environments
**Sports teams can often have more open data that is highly measurable**
Sports are inherently easier to measure numerically and visually compared to common company roles such as software development, product management, design and marketing. Roles that exist in companies do not have the same simple objective that sports do. Employees can generate impact in a multitude of ways and also can make a wide range of contributions that could have varying implications over the short and long term. However the difference in the ease of contribution measurability does not diminish the fact that increasing contribution measurability can be highly beneficial for more accurately identifying and rewarding the most performant and impactful contributors. Increasing the contribution measurability in any environment will help with more effectively identifying and rewarding the top performers. The less effective a company is at measuring the contribution efforts the more there is a risk of inaccurate compensation outcomes and creating environments where leadership and management could more easily make incorrect, unfair or biased compensation decisions.
**Sports teams often don’t need to do as much skill and competency verification**
Sports player contributions are often accurately recorded and publicly available. This makes it easier for other teams and people across the world to understand and compare the value of each player. This access to reliable and verifiable information means a team could make contract offers to other team players with more confidence due to the fact that they know the potential value of that player for their own team. In company settings the value of an employee is not as publicly shared to a wide audience. A company is not incentivised to make others aware of their top performers. Employees will often have to apply to other companies and prove their skills and competencies each and every time they do this. There are also some situations where companies might decide to not do much upfront skill and competency verification when interviewing employees. Employees who have worked at FAANG companies can often find it easier to get a job elsewhere due to the association with one of these larger tech companies. Other companies are aware of the difficult interview processes that these people must have gone through to be employed at those companies. Companies will sometimes use that information as a proxy to verify that someone has a certain skill level and competency. This is a great example of how public contribution and professional information can be beneficial for employees. The example of public contribution logs from sports environments help to highlight the potential value of making contribution efforts publicly available. For employees this can be an effective way to showcase their contribution history so that other employers can verify their contributions, performance and potential impact they could generate.
**Sports team environments can be more reliable and effective for top performers**
Companies are not incentivised to share how good their employees are publicly as then competing companies could more easily try to poach their top performers. This isn’t a good outcome for the employee as they might be worth much more than they are currently being paid. Top performers benefit from others being able to easily identify and verify that they are highly performant and effective. Public measurement of contribution efforts can help with creating a highly beneficial environment for top performers to thrive as everyone becomes aware of how good they are. Top performing sports team players receive the benefits from their contribution efforts being made public and easily accessible. In sports environments these players can be measured and reviewed by other teams much more easily. Accessible information about top performers helps to give them more ability to work with the teams and people that they want to work with. In company environments this could mean that top performers could more easily work in the teams and on the ideas that they are most interested in. Making this information more public also helps to create a more open and competitive market for contributors as everyone can now see the value of each individual. This is good for top performing contributors as it can help to minimise the influence of other people deciding what their value is. Instead these top performing contributors can now showcase and verify their value to others more easily.
## Comparisons between sports teams and Web3 ecosystems
**Web3 ecosystems also have open data due to open source software**
Web3 ecosystems highly benefit from developing open source software. If projects were predominantly open source the contributors in these projects would have their contribution efforts publicly recorded. Contribution efforts towards open source software would be public by default. This is a great outcome for contributors as now the value of their contributions can now be more easily recorded and showcased to anyone else in the ecosystem and wider industry. This is an improvement over existing company environments where contribution data is often private and not as publicly accessible. Contributors could now more easily build up a public and global reputation based on their contribution efforts and be paid more accurately based on their actual performance and the impact they generate. This openness of data can help with creating an environment that is similar to team sports. Contributions would be public and top performing talent could benefit from being more easily identified and compensated for their skills and competencies.
**Web3 ecosystems can make it easier for contributors to build a public reputation**
Sports team players benefit from their contribution history being measurable and publicly available. Public and measurable contributions make it easier to see how the performance and impact of a player changes over time. Web3 ecosystems could benefit from this same environment if many projects are open source and the contribution history can be made publicly available. Contributors in Web3 ecosystems could build up a reputation based on their contribution logs which demonstrate their performance and the impact they generate. This reputation can help to empower contributors and make it easier for them to work with who they want to work with and to be paid fairly.
**Web3 ecosystem contributions are far more difficult to measure**
Similar to company environments, Web3 ecosystem contributions are still inherently much more difficult to measure for performance and impact. Contributors could support and improve an ecosystem in many different ways and their contributions could generate impact over the short and long term. It is currently difficult to have any reason to believe that contributions in Web3 ecosystems will ever be as measurable as they are for player contributions in sports teams. However this does not diminish the opportunity and benefit of increasing contribution measurability where possible. Contribution logs could help with pushing more power to the edges as contributors could now have more control and influence over building up their own reputation that can showcase their performance and impact.
# Recording & measuring contribution efforts
Approaches for recording contribution efforts and how contribution efforts can become more measurable
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Making contribution logs more measurable can help with drastically improving their usefulness and long term value. Increased measurability means making it easier to compare the contribution efforts from each contributor. It also means it should become easier to make historical comparisons to see who has been the most performant and whether individuals or groups of contributors are getting more performant or not over time. Higher measurability can help with increasing the accuracy in identifying the top performers who can then be rewarded for their high performance and impact they generate.
## **Contribution effort recording approaches**
**Observationally recorded contributions**
Leadership and management as well as other contributors that work with a contributor are able to observe the contribution efforts and outcomes that another contributor is responsible for. These observed contribution efforts might not be written down or digitally recorded. Instead the people who observe these efforts may just try to remember what each contributor has been working on. Companies may often use an observational approach as a simple way to monitor what contribution efforts each person is making and how performant those people are. Leadership and management would look to observe the efforts and outcomes that people are generating over time. The problem with this approach can emerge when the people doing these observations are given a lot of control over the performance and impact measurement. They could be given a large amount of influence and power over determining other peoples compensation. Observationally recorded contributions rely on people making accurate and fair observations about someones contributions. This approach can be highly time consuming for those that are responsible for making these observations as they will need to record and verify each persons contribution efforts themselves.
**Manually recorded contributions**
Contributors could manually make a submission about the contribution efforts they make and provide any evidence that supports those claims. Manually recorded contributions are necessary for situations where it is not easy to automatically record and verify someones contributions. In person events, meetings or other forms of mentorship and leadership could all be examples of contributions that are more difficult to record without using a manual submission process. Contributions that are added manually by a contributor or by other community members could benefit from having attestations attached to those claims. Other community members could vouch for the contributions made by others. This could be a useful addition to manually recorded contribution efforts to make it easier to verify that a contributor has done what they say they did. Peer to peer attestations can introduce the risk that this process will be abused by malicious actors. The identities of the community members giving these attestations would ideally need to be verified and trusted for these attestations to become more reliable.
**Automatically recorded contributions**
A number of contribution efforts can be recorded automatically and provide evidence about what a contributor has been working on. Digital contributions can be easier to record and verify. Examples include code contributions, designs, articles, blogs and documentation changes. These digital contributions can be tied to an individual account which makes it easier to verify who made certain contributions. Online recorded meetings could even be eventually automatically transcribed and verified to prove someone's attendance and the contributions they made towards a discussion. Automatically recorded contributions can be highly useful for contributors as it can make it effortless for them to record and showcase the contributions they have made.
## Ranked preference of contribution recording approaches
All the contribution recording approaches mentioned previously could be used in combination to help with recording someone's contribution efforts. These approaches can also be preference ranked.
**1. Automatically recorded contributions**
Automatically recorded contribution efforts are the preferred approach to help with making it easier and faster to create and also verify contribution logs. Automatically recorded contributions can help with reducing the risks around incorrect or exaggerated efforts if those same contributions were manually recorded. Automatic contribution records can also help to reduce or even remove the time needed for a contributor to record their contribution efforts. Where possible contribution efforts should be automatically recorded.
**2. Manually recorded contributions**
Manually recorded contributions are useful to fill in the gaps for contribution areas that are not as easy to automatically record. Manually recorded contribution efforts can help with providing the full information about someone's contributions. Processes will be needed that introduce the right checks and balances and the right incentive design to make sure these self recorded contributions get verified. There will always be a risk that someone tries to game this system in an attempt to unfairly improve their own reputation and future chance of receiving funding.
**3. Observationally recorded contributions**
Observationally verified contribution efforts would be the most time consuming approach to scale to a large number of people. This approach can also be more easily abused if certain individuals are given more influence over deciding other peoples compensation. Observational recording and verification of contribution efforts will happen naturally as contributors work with each other and as community members look at what the funded contributors have been working on. Observations will be useful for community members to more thoroughly understand and verify the contribution logs and efforts that people have been making. These observations should also help with identifying bad actors in the ecosystem.
## **Contribution measurability complexities**
**Short vs long term outcomes**
The value and impact generated by contribution efforts is not always obvious. Some contributions can have longer term implications that benefit an ecosystem over time.
**Wide impact potential**
Contribution efforts could help with producing a variety of different outcomes that each could make an impact in a number of ways. Contribution efforts could make impact through improved ecosystem functionality, usability and experience or they could be generate impact in the wider community and positively influence how community members think, discuss and collaborate. It can be difficult to fully understand the impact that someone's contributions could make in the ecosystem.
**Contribution variability**
A contributor could make a wide variety of different contributions to generate impact for an ecosystem. Each of these different types of contribution effort could require very different skills and approaches for those efforts to be recorded, measured and verified.
**Leadership based contributions**
Some contribution efforts could be focussed on inspiring and aligning the efforts of a group of contributors. These types of contributions can be more difficult to measure due to the fact that each individual could respond very differently to these leadership efforts.
**Social based contributions**
How contributors interact with one another on a social level can have a big impact on the team's rapport and the overall cohesion and alignment between a group of contributors. Positive contributions to social environments are harder to measure and verify accurately yet these contributions could be highly valuable to an ecosystem if they help to make a more welcoming and enjoyable place for people to collaborate and solve complex problems.
**Peer to peer measurement & verification**
Manually self-reported contributions and group based social and leadership contributions are both example contribution areas that can benefit from peer to peer attestations to better determine and verify what actually happened in a group working environment and what impact was generated by different peoples contribution efforts. There is a complexity in ensuring that these attestations are legitimate and not purposefully incorrect or biased as there is an incentive for people to try and exploit this system to financially benefit themselves.
## **Making contribution logs more measurable**
**Execution scope**
Grouping the type of work that is being completed is one way to try and increase measurability. Keeping a contribution log entry focused on a certain skill set such as coding or design could help with making it easier to compare and understand how different contributors have executed certain outcomes versus other contributors. The challenge with trying to make the execution scope more measurable is that each idea being executed is often different from other ideas and thus can require different skills and expertise to execute them. Executing these different ideas can also produce very different outcomes. Infrastructure and protocol development alone could have a lot of variation in how the different problems are solved and what skills are required.
**Time**
Contribution outcomes could be recorded within a certain time period so that there is more consistency in the amount of work that is being completed within each contribution log. Fixed time periods can help to increase measurability as now contribution logs can be more easily compared.
**Number of people**
If the contribution outcomes are from multiple people and their efforts are being combined into the same contribution log it would become more difficult to understand who did what and how performant and impactful each of their contributions were. Keeping contribution outcomes recorded separately as individual contributions can help with making it easier to measure and compare the differences between one person's contribution outputs with other contributors.
**Summary**
Recording one person's contribution efforts at a time and recording contributions within a fixed time period, such as monthly, are the two stand out approaches mentioned above that can help with consistently making contribution efforts more measurable. In terms of execution scope, it is more difficult to separate out every type of contribution effort into a separate submission. However the execution scope could at least be improved by tagging the skills that are being used when recording any contribution efforts. For instance, design and code contributions could be recorded separately or correctly tagged to make it clearer about what different skill sets have been used.
# Individual monthly contribution logs
Exploring the opportunity of adopting individual monthly contribution logs
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This page contains the same information that is covered in the above video
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Exploring how to make [contribution efforts more measurable](/contributions/contribution-verification/recording-and-measuring-contribution-efforts) and comparing different [contribution verification approaches](/approaches/contribution-verification-approaches) led to the conclusion that individual monthly contribution logs could be a highly effective approach for recording, measuring and verifying contribution efforts. This approach can help with making it far easier to compare peoples contribution efforts across an ecosystem and also compare how the performance of each individual changes over time as more contribution logs get submitted.
## **Individual contribution measurement is often unavoidable**
Applications, protocols, community initiatives and many other ideas can often require a number of different contributors to help with execution. The key problem with group based contribution logs is that groups of contributors that are executing ideas would still need to fairly determine how compensation is distributed between the contributors working on that idea. This is one reason why individual contribution measurement and verification is often unavoidable. If contribution efforts are not recorded through contribution logs this group of contributors will be doing it through observational measurement. Making it easier to record, measure, verify and present individual contribution logs can help with more accurately rewarding contributors within a group based on the merits of their contribution efforts rather than it becoming a popularity contest or being influenced by biased decisions that might benefit certain individuals over others.
If individual contribution efforts are not measured in any capacity it will be difficult to know who has done what work and who has done the most work overall. It would also be difficult to know who has performed the most effectively when executing the idea and who has made the most impactful contributions. This outcome is problematic as this could mean hard working and high performing contributors aren’t correctly rewarded for their effort. These top performers could simply decide to not work with this group of contributors in the future. Alternatively they might just decide to not work as hard as their efforts are not being recognised and rewarded. A lack of recorded and measured contribution efforts could also make it more difficult to spot which contributors are not performing well.
When contribution efforts are not recorded the process of verifying and measuring peoples contribution efforts can become more time consuming and end up being handled by project owners in the group. Observational measurement from project owners gives them more power and influence over what each individual will be compensated. Alternatively, if the decision process for what people get paid was democratic then the main issue with a lack of recorded contribution efforts is that people would need to observe other contributors and be much more aware of what everyone has been working on to make an informed decision on what is fair and reasonable in terms of compensation.
Recording individual contribution logs improves both of these scenarios. If a small group of individuals have more influence over how much contributors get paid the recorded contribution logs would provide more evidence that can help with fairly determining the value of each persons contribution efforts. Using individual contribution logs can mean that contributors have a more reliable way to prove their own value. In a democratic decision process for distributing compensation the contributors would all benefit from having more access to accurate contribution logs as now they can showcase what each of them have been working on. Understanding how people have contributed towards an idea can be a foundational source of information for making more informed decisions about who has been the most performant and effective in the team.
## **Steps for recording individual contributions**
**1. Automatically recorded contributions**
Automatically recorded contributions are a great foundation for creating contribution logs. Digital contributions such as code commits, designs and written submissions can be automatically tracked and tied to an individual account holder who made those contributions. Digital contributions such as these can be recorded and verified the most easily. Automatically recorded contribution logs alone could be very insightful for understanding what each contributor has been working on.
**2. Manually recorded contributions**
Contributions that are more difficult to automatically record and verify could be added as a manual submission. Manually added contributions could include in person event attendance, collaboration efforts or research efforts that don’t produce a digitally recorded outcome that can be easily verified. Self reported contribution efforts will either need to have some evidence to support the claim or those contributions should have been observed by other contributors or community members. If contribution efforts cannot be verified their usefulness and reliability would be much lower.
**3. Observationally recorded contributions**
Contributors will often work with a number of other contributors when they collaborate to execute ideas. These contributors will be able to observe the contribution efforts of others. These observations are important as contributors will be able to more easily identify mistakes or purposefully incorrect claims in someone else’s contribution logs.
**4. Peer to peer attestations**
At this point contribution efforts should now mostly be observed and recorded. The next step is focussed on peer to peer attestations. Contributors should now be able to make attestations about other peoples contribution efforts that they have observed and verified themselves. These attestations could help with creating a clearer image on how contributors have been working together and how each person's contributions have impacted others. Peer to peer attestations could add more clarity and evidence about the relevance and impact of different peoples contribution efforts. Peer to peer attestations do have the risk of people trying to game this system to try and financially benefit themselves by lying about what they have worked on and then trying to get misleading and incorrect attestations from others. Checks and balances along with the right incentives would be needed to try and mitigate these risks as much as possible.
**5. Community reviews**
As a final step, community reviews could help with verifying peoples contribution logs and any attestations that are attached to those logs. Individuals that don’t actively work with the contributors in an ecosystem could still have relevant expertise and experience that might be useful for reviewing peoples contribution logs. Community reviews of peoples contribution efforts could help to highlight opportunities for improvement, new ideas and also help with identifying bad actors that could be trying to abuse the system. Impact could be generated slowly over time and it might not be obvious how an executed idea will make impact across the ecosystem. Community reviews could also be done over a longer time period to review what impact has been generated by different contributors over time. Community reviews of other people's contribution efforts could help with improving the communities ability to more accurately identify the top performers. These contributors could then be more fairly compensated for their performance and impact.
## **Advantages of individual monthly contribution logs**
**Effective contribution verification**
In group based contribution logs it can be easier to hide poor performance as the contribution logs won’t necessarily break down who has been working on what with enough evidence. Logging an individual's contribution efforts can be a more effective solution for verifying that each individual involved in a project is actually making sufficient contribution efforts towards executing that idea. If contribution efforts are recorded every month this can also make it easier to compare those outcomes with other contributors. Monthly contribution logs help to make these logs more measurable, which can help with making it easier to identify the best and weakest performers. Support could be provided to contributors that need to improve their performance. If the performance of a contributor doesn’t improve or the individual is purposefully being a bad actor then it would be unlikely that they receive future funding due to the evidence of poor performance shown in their contribution logs.
**Improved decision making**
Measurable contribution logs can help with making it easier for voters to spot the best and worst performers amongst a group of contributors. It can also help with identifying trends in the performance of contributors as a whole or where certain skill sets might be missing. This information can help with improving future funding decisions about where to allocate more resources and focus. Individual monthly contribution logs also become increasingly useful over time where a contributor will build up a reputation based on their contribution history. These logs can help with making voting decisions even easier over time as the community will simply be able to repeatedly select and fund the most performant contributors in the ecosystem.
**Retaining top performers**
Every idea won’t be successful and some teams won’t perform well together. Individual contribution logs can help with identifying the most performant contributors in those situations where an idea fails or where there is a breakdown in a team's communication. Contribution logs would help to provide evidence of which contributors were the most effective in those teams. If those contributors can more easily prove they were effective at executing ideas it will be easier for them to be considered as a good candidate to help with other better performing ideas and teams.
**Higher self awareness & accountability**
If contributors can easily see their own performance against other contributors they are able to become more aware and self accountable for trying to achieve a similar or higher level of contribution output as the other contributors in the ecosystem.
**Empowers individual contributors**
Being able to demonstrate high performance or impactful contribution outcomes is empowering for building a contributors reputation. Competent and high performing contributors that are able to easily demonstrate their capabilities and performance should be able to more easily receive fair compensation for their efforts. Rewarding contributors who are working harder or more effectively than others is an important way that the available incentives can be more effectively aligned with generating impact for the ecosystem. Another way that evidence of contribution efforts can help to empower the individual is that it provides a public facing record that demonstrates what a contributor has achieved and what skill sets they are most competent at. This can make it easier for different teams and projects to verify that a contributor is well suited to help them with their own execution efforts. The easier it is for an individual to prove their ability and competencies the more control and influence they will have on being able to pick the most suitable initiatives to work on that they are most interested in. Their reputation will also help with ensuring that they will get paid fairly for their skill level.
**Removed intermediaries**
Web3 ecosystems have the opportunity to make a more democratic and peer reviewed process for assessing performance and impact. Achieving this can help to reduce the need for intermediaries such as management and leadership positions and prevent them from having excessive amounts of control and influence over determining someone’s compensation. Effective contribution measurement can help with creating a more open and free market for individuals to compete in. Self ownership of contribution data can more easily be used by contributors to influence the compensation they receive and their career trajectory. More self ownership of contribution data can help with preventing individuals or small groups of individuals from being able to unfairly determine someone else’s value. Self owned contribution data can help with pushing more power to the edges by enabling contributors to have more control over their data and reputation.
**Flexible information usage**
Information about an idea being executed can be highlighted in someones contribution log. This can also include which milestone would be relevant to the contribution efforts. This added context means that an aggregate of different peoples individual contribution logs can help to create project based information such as the total contribution efforts towards an idea in the last month or the amount of contribution efforts that have been made towards a certain project milestone. This flexibility in information composition means it becomes much easier to view contribution efforts in a format that is most useful to the viewer.
## **Opportunities for Web3 ecosystems**
**Open source contribution data**
Open source data could help with creating highly insightful information for better understanding the performance of a contributor or cohort of contributors. Public contribution data could help with identifying skills gaps and areas of improvement that the contributors could work on to become more performant or to generate more impact. Measurable contribution data will become increasingly valuable over time as now historical comparisons can be made and these learnings can then lead to more experiments that identify system and process improvements.
**Self sovereign identity adoption**
Contribution logs could be attached to the identity of the contributors who submit these logs. These logs could be a great use case that helps with building up useful identity tooling within an ecosystem. Contributors could start submitting contribution logs to start building their own reputation at any time. Permissionless identity tooling with verifiable contribution logs could really help with enabling emerging talent from anywhere in the world with getting recognised and rewarded for their efforts.
**Trust based networks**
Verifiable contribution data could be used to initiate some form of a trust based network that people use to prove someone's competency and reliability. Communities could start using this information as a form of identification and a way to trust certain individuals due to the reputation they’ve built and the common connections they share. These networks of provable contribution effort could lead to new working arrangements between contributors based on the trust in these verified contributions. These emerging networks could also result in the development of number of new identity related use cases that build on top of these connections and data.
# Voter preferences & opinions
Understanding the importance of voter preferences and opinions and how they can be useful for funding
Voter preferences and opinions can greatly help with providing insightful and actionable information to the rest of the community and the existing contributors about what submissions could be improved and how the funding process could potentially generate higher amounts of impact. Enriching a funding process with the ability for voters to easily share their preferences and opinions can help with making a funding process more responsive to new information, changing community sentiments and constructive feedback.
Communities will have a number of preferences and opinions about what priorities are most important, what ideas look the most promising and which contributors they believe will best help with generating the most impact. These preferences and opinions can constantly change as new information emerges and the ecosystems and their environments evolve over time. Preferences and opinions could be represented as the current community sentiment, approval or disapproval of anything submitted during funding or be direct feedback given by a community member.
Capturing and recording community preferences and opinions does not mean that a final decision is being made that leads to any defined outcome. Sharing voter preferences and opinions could occur in the same vote as one that is generating a defined outcome or these could be handled separately. Communities being able to express their preferences and opinions means that anyone in the community will be able to share what they’re really thinking without necessarily being involved in a formal decision about what outcome should occur. A community could have a vote that highlights there is a majority preference that there needs to be more DeFi applications in the ecosystem. Indicating this preference does not necessarily mean an incentive is being allocated to address that preference directly. Awareness of these communities preferences and opinions helps to expand and enhance the mutual understanding across the community on what the wider community is currently thinking. Having this understanding can then help with other formal selection processes such as the contributors who are involved in executing those priorities as now the community can reflect on whether the contributors they are selecting will help with addressing the most important priorities. In general these preferences and opinions can help with identifying what areas might need more or less attention in upcoming funding decisions.
Votes that result in a specific outcome could be handled by either voters or contributors. The ecosystem will always benefit from the community being able to express its preferences and opinions on what ideas they currently believe are the most promising. However who actually selects which ideas are executed is a funding system design choice. The responsibility of the actual outcome of which ideas are executed could be given to the contributors who would need to reflect and take into account all of the preferences and opinions that have been shared by the community. It is these example situations where the ongoing value of gathering the preferences and opinions of the community becomes more obvious as now the accountability can be left with the contributors but the system can still be fully expressive and inclusive by inviting all forms of preferences and opinions from the community to help with supporting the selection of ideas.
## Importance of capturing voter preferences & opinions
There are a number of reasons why voter preferences and opinions should be captured throughout a funding process and a couple of concerns to keep in mind.
**Advantages**
* **Clearer sentiment & approval** - If the community is able to express their preferences and opinions clearly this information will be available for the wider community and for any existing contributors to consider. These preferences and opinions can help make it clearer about what the current sentiment is within the community about different topic areas and information that is available across the ecosystem. Contributors can respond more quickly to these changes of sentiment and approval when it makes sense to do so.
* **Faster feedback & learning** - Allowing the community to provide their preferences and opinions to any of the submissions made throughout funding enables the community to provide feedback and learn about what other community members are thinking. This increases the speed of feedback sharing which can help with increasing the rate in which any of the submissions made in the funding process get improved over time.
* **Inclusive** - Inviting community wide participation within an ecosystem means the funding process becomes more inclusive towards the diversity of thought and opinion that can exist across the community. No person's preferences and opinions need to be excluded if the funding system enables that information to be shared freely.
* **Representation & accountability** - If the wider communities preferences and opinions are known this makes it easier to identify and select contributors that would become responsible for representing and responding to those needs and wants from the community when they are executing ideas for the ecosystem. Preferences and opinions being widely available and understood helps to also increase the level of accountability, contributors would become more aware of the communities preferences and opinions that they need to consider.
* **Community engagement** - The more it becomes obvious that each individual's preferences and opinions are heard and taken into account the higher the chance there is that community members choose to engage in the funding process because they know their input will be heard and valued. Enabling voters to always express their preferences and opinions is an important part of ensuring the voicers of voters can always be heard.
* **Responsiveness** - Enabling the community to provide their preferences and opinions around different areas across funding more immediately helps an ecosystem in becoming more responsive to new information and any changing community opinions. Capturing these preferences and opinions across the funding process can help with mitigating problems that emerge before they become more problematic or could also mean identifying opportunities that can be explored more quickly and responding to those opportunities sooner rather than later which could mean creating more immediate positive outcomes for the ecosystem.
**Concerns**
* **Information overload** - Capturing community preferences and opinions creates invaluable amounts of information and data for the community and contributors to consider when executing different ideas. However the larger these funding processes become the higher risk there is that there is an excessive amount of information to handle. Systems and processes will need to consider how this information is structured, organised, moderated and presented to the community so that any preferences and opinions which are shared are sufficiently concise but informative.
* **Sybil attacks** - How identity is handled in funding processes will impact how easy it becomes for sybil attacks to occur. The preferences and opinions of voters could have a direct influence on how assets are disbursed. If this is the case, there is an incentive for bad actors to try and game that system by creating multiple identities to try and manipulate those community preferences and opinions in their favour.
## Priority preferences & opinions
An ecosystem will benefit from voters always being able to immediately express their current thoughts and opinions about what problems or opportunities there are in the ecosystem that should be considered. This is especially important for responding to changing environments or emergencies. The speed of information flow can help with increasing the responsiveness of the contributors that are helping to tackle these problems and opportunities. Ensuring that the community's voice can be heard through the submission of priorities along with other community members indicating their preferences and opinions means that execution efforts can be more easily aligned with responding to those priorities to generate impact for the ecosystem. Capturing community preferences and opinions around prioritisation can help contributors gain higher clarity on where they could best allocate their efforts to best address these priorities. The faster and easier it is to see what the biggest problems and opportunities are, the faster that the contributors can be in responding to this information.
## Idea preferences & opinions
The execution of ideas will help to address the existing priorities in an ecosystem. These ideas could differ greatly in terms of the technicalities and approach being taken. The diversity in potential initiatives that could address a priority makes it difficult for a large population of voters to fully understand the differences, tradeoffs and nuances of every idea that might be suggested across a large ecosystem. There will likely be individuals within the community that are well informed and can fully understand the implications of different ideas due to having the relevant expertise and experience. As an ecosystem grows and the diversity of priorities and ideas expand this however does become more challenging for many voters to be well informed on all of the different topic areas and the ideas in each area.
Although there is a complexity for voters to participate in the selection and understanding of a growing amount of ideas there is still a great benefit in enabling the community to share their preferences and opinions about which ideas are most promising. The community sharing their preferences and opinions is important as it opens up the opportunity for the people who have a particular interest or expertise in a given area to participate in how those ideas are refined and get executed over time through their own feedback and participation. There is no need to prevent community members from trying to offer their opinions to help improve or support an idea. It can be accepted that there will only be a certain number of people in a larger voting population that will have both the capacity and willingness to engage in these ideas in high depth, however it is beneficial to enable any of these potential voters in being able to participate as they could provide highly useful and impactful feedback. Another reason this approach of inviting preferences and opinions is important for ideas is it enables the situations where a voter becomes increasingly interested in an idea over time to the extent that they now want to become an active contributor. This type of outcome can be more easily achieved if voters can easily engage and participate in the process of discussing and providing feedback to ideas.
## Contributor preferences & opinions
The community benefits from being able to express their preferences and opinions on what contributors could help with making the most impact for the ecosystem. This could be preferences and opinions about new contributors that have yet to provide any contributions. Or they could be about existing contributors that already have a history of contribution. These preferences and opinions can help with sharing the current sentiment and thoughts around which contributors might be most suitable for generating impact in the ecosystem in upcoming funding decisions. The preferences and opinions about the most important priorities will also be something that influences these decisions. Identifying and responding to bad actors is another reason why the selection of contributors benefits from enabling community members to easily provide their preferences and opinions as new information and changes occur.
# Voter outcome influence
Exploring how the influence that voters have over outcomes can sit somewhere along a range of potential approaches
Voter outcome influence means thinking about what amount of influence the voters should have when making a decision and voting on a specific outcome. The amount of influence that a voter has on determining any specific outcome could sit anywhere along a range of low influence to high influence. This amount of influence will depend on how the funding systems and processes have been designed.
The higher the influence that the voters are given to decide the outcomes of decisions and planning efforts the more important it becomes for them to be well informed and heavily involved in the funding process. More voting outcome influence increases the cost of participation and complexity for the voters but gives them more control over the exact outcomes. A funding process will benefit from thinking about what level of influence is important for each part of a funding process to minimise the complexity and time it takes for voters to participate.
Some potential examples of different levels of influence a voter could have over different outcomes:
* **Light suggestion** - The voters are not expecting a specific response or outcome. A voter who is leaving feedback on a submitted idea could be an example situation where a specific response or outcome is not expected and the feedback is merely trying to be informative and helpful.
* **High influence suggestion** - The voters are expecting an aligned response based on the voting outcomes. A priority being selected by the community would be an example where the voters would expect the contributors who are being compensated in the ecosystem to respond to this outcome and align their contribution efforts with addressing those priorities.
* **Exact outcome** - The voters are expecting an exact outcome. A system level parameter change would be a vote where an exact outcome is expected.
The more influence the voter is given on the outcome the more responsibility they are being given to determine what funding submissions could help with creating the most impactful outcomes for the ecosystem. Voters will only have so much capacity and willingness to participate in voting. One key comparison that could be made with this in mind is which processes are of the highest importance that the voter has the highest level of influence over the outcomes and where is this less essential for the funding process. Achieving this will make a more scalable funding process as voters have limited time and capacity needs to be focussed on the highest impact areas that voters both can and want to influence.
AI will become an increasingly important factor that could change how both voters and contributors participate in governance decisions. Voters or contributors may decide to delegate some or all of their voting responsibilities to an AI when tasked with certain decisions. Voters could still personally each have the same influence over the outcome of these different decisions, however the approach they use to arrive at that decision could change drastically over time.
## Priorities outcome influence
**Influence importance**
High. When voters express themselves and help to suggest and select the most important problems and opportunities that exist in the ecosystem they will be expecting that the priorities that are most well supported will get addressed over time. The question then is should the outcome be a high influence suggestion or an exact outcome? Priorities being high influence suggestions instead of an exact outcome make sense for a number of reasons:
* **Prioritisation inaccuracies** - Priorities set by the community might not be accurate in understanding the underlying reasons why a certain desired outcome might have a different root cause. People who have higher levels of experience and expertise should be able to interpret and analyse these priorities to better determine what other areas of focus might address these priorities more effectively.
* **Highly restrictive** - If an exact outcome approach was used it would mean contributors would only be able to contribute to things that have been approved by the entire community. This can easily lead to situations where innovation is stifled. Novel but less well known areas of impactful contribution could be forgotten and prevented by this approach. Relying fully on the voters removes the agency and autonomy of a skilled and experienced contributor from being able to use there best judgement to identify how they can best generate high impact.
* **Execution uncertainty** - There is no absolute certainty that any priority set by the community is feasible. Some of those priorities may also take a longer time to be addressed if they are of higher complexity or contribution effort required.
**High importance environments**
If the incentives from funding are attached to the priorities being selected then the outcome of those decisions become of very high importance and mean a more exact outcome is needed. If the incentive is attached to ideas or contributors then the importance of voter influence could become a high influence suggestion as suggested above.
## Ideas outcome influence
**Influence importance**
Low. Voters highly benefit from being able to express their preferences and opinions about what ideas they believe are most promising. However the actual selection of ideas does not have to be determined by voters. Instead it could be decided by the contributors who are selected to help with execution. Some separate analysis has been added to compare the factors for utilising either contributors or voters for idea selection:
{% content-ref url="/pages/xYQAsghQw3dl2LQC0Ybe" %}
[Contributor vs voter idea selection](/approaches/decision-approaches/contributor-vs-voter-idea-selection)
{% endcontent-ref %}
**High importance environments**
If the incentives available in the funding process are attached to the priorities or ideas being selected then the outcome of those decisions become of very high importance and mean a more exact outcome is needed. If the incentive is attached to contributors then the importance of voter influence could be low as highlighted above and a light suggestion approach could be adopted.
## Contributors outcome influence
**Influence importance**
Very high. The contributors can’t select themselves! The community itself will need to be responsible for selecting the most potentially impactful contributors that can be compensated to work in the ecosystem. An exact outcome is needed to determine who will and will not receive compensation from the treasury to execute different ideas.
**High importance environments**
The selection of contributors is always of high importance as if the incentives are attached to priorities or ideas the incentive still mostly ends up being distributed to the contributors that execute those proposals. Voters will select contributors during funding whether or not the ideas or priorities are attached to that same decision. Contributors receive the bulk of the funding incentives to help with generating impactful outcomes. It is always of high importance that the voters can directly influence how those incentives are disbursed.
# Proposal submission incentive approaches
Comparing different approaches that could be used to incentivise proposal submissions
A proposal process can use incentives to help encourage the submission of proposals that can help with the different processes involved in treasury funding. Proposal submissions could be relevant for any of the knowledge, priorities, ideas or execution process steps. Each of these funding processes have a number of differences in the types of proposal information that could be collected, discussed, compared and then voted on.
These incentives only cover how people could be encouraged to participate in a proposal process with their own suggestions. The incentives that help with the execution of proposals are covered separately. Incentives that cover the operation of the funding process itself would also be covered elsewhere in some separate treasury operation analysis.
## Proposal incentive concerns
The following are some general concerns worth considering about the influence that incentives could have on a proposal submission process.
**Minimising submission bloat and duplication**
Allocating most of the incentive to the author of a suggested proposal creates a high risk of increasing the duplication of similar submissions. If it is only the author of a submission that gets sufficiently compensated there would be a reduced incentive for further collaboration on existing proposals. Due to this misalignment people may decide to duplicate the most promising submissions in an attempt to get their own version to become the selected proposal that then receives compensation. The complexity that emerges from trying to tackle this problem is determining the value of contributions from other people who provide feedback, discussion and supporting or conflicting evidence about a given proposal.
**Encouraging** **quality over quantity**
The incentives introduced into a proposal process can have a big impact on how people end up contributing. One ongoing concern will be to think about how any suggested incentive structure incentivises quantity or quality. For processes that are trying to scale to many participants the focus will often benefit from leaning towards incentives that promote more quality submissions over a higher quantity of submissions. This is because when you increase the number of people that are participating in a process the cost of having too many submissions becomes even greater as the number of either proposal submissions or participants scale. Adopting an approach that incentivises a high quantity of submissions should be well justified due to this scaling cost. In most cases the incentive approach should preferably help with encouraging higher quality submissions.
**Depth of thought & discussion**
Many Web3 ecosystems are trying to tackle big societal problems that cover important areas such as money, financial services and governance amongst many other areas. Creating effective funding processes will mean making considerations towards how any suggested incentive approaches can help with encouraging more depth of thought and discussion. The better this is achieved the more well informed the wider community can become on the nuances of different topics and potential decisions. Some of the complexity with this area of incentivisation is that each person can contribute vastly different amounts of value and allocate different amounts of time when making their own contributions and sharing their opinions.
**Supporting evidence for submissions**
A lot of effort and time can be needed to create and maintain resources that get used as evidence for supporting why a proposal is important. The incentives introduced to any funding processes will need to factor in how they are effective in encouraging the authors of a proposal to provide sufficient evidence to support their submission. This incentive could also extend to encouraging those authors or other contributors to keep the resources and any information up to date so that community members are kept well informed about the ongoing importance of a proposal over time.
## **No incentives**
Not adding an incentive to the proposal submission process means there would be no financial compensation for making proposal submissions. The incentive to encourage submissions is either dealt with elsewhere or relies on other forms of incentives.
**Reasons to adopt this approach**
* **Outcome based incentive** - Suggesting and supporting proposal submissions can be an impactful contribution to an ecosystem. Community members may not expect a financial incentive if they already have other intrinsic incentives that encourage them to contribute towards making positive change. The more complex a submission process is or the more that there is ongoing work involved in maintaining a proposal the more difficult it could become to attract many willing contributors without a sufficient incentive to support those contributions.
* **Simplicity** - Not introducing a direct incentive for submissions can help with simplifying the proposal process. This would mean the process is either relying on execution incentives for people to make the submissions or that other incentives exist. For some proposal processes having no incentive around the submission of proposals could be the simpler and more effective approach.
**Concerns for this approach**
* **Low incentive for complex submissions** - Not introducing any incentives to encourage proposal submissions or for handling the maintenance of existing proposals could lead to a lack of depth in the submissions being made. Proposals could end up lacking enough supporting evidence, critical thinking, research or analysis due to the lack of incentive. Under a no proposal submission incentive approach any incentive for supporting complex submissions would need to be handled elsewhere through other incentives.
* **Low incentive to maintain existing submissions** - No incentive for proposal submissions means community members would not have any direct incentive to maintain and improve existing proposals. This could be a problem if new information or factors become relevant for an existing proposal. An ecosystem can benefit from having the latest information connected to proposals so that they are able to make more informed decisions about the importance of a different proposal submission against alternatives.
* **Risk of under submission** - Having no incentives means the process is reliant on other forms of incentives existing that are effective for encouraging submissions. Execution based incentives would likely be one of the most prominent of these incentives to encourage a sufficient amount of submissions.
* **Contributor influence risks** - Having no incentives for submission means that there is less incentive for unpaid community members to submit their own proposals. If there are existing execution incentives that pay for contributors to support an ecosystem there is a risk that this lack of incentive for submission gives an increasing amount of influence to existing contributors. This would be due to the fact they might have more capacity to participate in a proposal process than other community members because they are already receiving compensation elsewhere.
## Submission incentives
Providing submission incentives means compensation is rewarded at the point of proposal submission. A verification process could also be part of this approach that determines whether a proposal submission meets a certain quality threshold before it gets accepted.
**Reasons to adopt this approach**
* **Incentivises a diversity of submissions** - Incentives at the point of submission could help with encouraging many members of a community to make a range of different proposals for that process. This could be effective for discovering the wide range of ideas and opinions that exist in the community.
**Concerns for this approach**
* **Risk of over submission** - There is a high risk that this incentive leads to encouraging contributors to suggest many variations of similar proposals as they would be compensated for doing so. This type of incentive could easily be abused as it could lead to low effort submissions that are suggested regardless of whether the contributor actually thought the proposal was important or not. Adopting a process for removing duplicated entries and ensuring quality thresholds are met could help to resolve this but could mean introducing an expensive moderation process.
* **Risk of duplication** - If the incentive is attached to submission there is a higher risk that people end up submitting variations of similar proposals instead of trying to improve existing ones. This could mean many existing proposals get duplicated with slight variation instead of those same contributors helping to improve existing proposals.
## Selection incentives
Incentives at the point of proposal selection means that compensation for making a proposal submission would only occur if that proposal is selected through voting. The voting process itself could operate in many forms such as confidence voting, preference rankings, yes / no outcomes or using numerous other potential voting approaches.
**Reasons to adopt this approach**
* **Aligned incentive for creating quality submissions** - If the only way to be compensated for a submission is through the proposal being selected by the voters there is a higher alignment for contributors to create quality proposals that are important and that would have higher chance of being selected.
* **Aligned incentive to handle complex submissions** - Spreading the available incentive amongst the winning proposals means there could be more of an incentive available to help ensure the complexities involved in a proposal are sufficiently covered with any supporting evidence.
* **Opportunity to help incentivise wider contribution** - Some proposals will be suggesting things that require a certain amount of contribution effort. The authors that submit a proposal do not have to be the same people that execute the proposal. This can be beneficial for increasing the amount of contribution involved as now the author doesn’t have to be responsible for executing the proposal. Instead they may only have the capacity and willingness to make good suggestions that they think are important. This is a lower threshold of required contribution which could help with increasing the amount of contribution across a community due to this separation of proposal incentives and execution incentives.
**Concerns for this approach**
* **Risk of over submission** - If there is an incentive rewarded at the point of selection there is still a risk of over submission of proposals as it might not take much effort to submit a proposal. The larger the incentive the higher the risk that this occurs. Some contributors may decide to make a wide range of proposal submissions to increase their chances of their proposals getting selected and then receiving some compensation.
* **Risk of duplication** - An incentive provided at the point of proposal selection instead of submission will still mean there is a risk that people suggest variations of similar proposals instead of making contributions towards improving existing ones. This could easily lead to higher levels of duplication where many variants of similar proposals get submitted.
# Contribution incentive approaches
Comparing different approaches that could be used to incentivise the execution of different ecosystem initiatives
There are a number of incentive approaches that can be considered when an ecosystem is looking to attract and retain people that are willing and capable of contributing to different areas of an ecosystem. Incentives that help with handling the execution of work are important for all of the funding processes (knowledge, priorities, ideas and contributors). These approaches are more focussed on how financial incentives are handled however further analysis could be beneficial to cover other types of incentives in more detail.
## Contribution incentive concerns
The following are some general concerns worth consideration that are relevant to incentivising execution.
**Rushed execution**
The incentives used for execution will be more effective if they help to encourage contributors to execute work to a high quality rather than rushing through the execution to just receive the compensation. Incentive mechanisms will need to consider how contributors may try to exploit a given process to get access to compensation more quickly with low effort or low quality contributions.
**Inflexible contribution approach**
Incentives used during execution will need to be considerate towards the fact that new information and changing environments may result in the need for the execution approach to change and that the final intended executed outcome may benefit from being updated. Incentives will benefit from accommodating these types of situations so contributors can most easily align themselves with creating high impact. Time consuming or overly complex processes that prevent contributors from executing impactful outcomes should be prevented where possible.
**Measuring impact**
Measuring impact will be an important part of identifying which incentives are most effective at consistently generating impact. The better that ecosystems become at measuring and improving how much impact they are able to generate through funding the faster they will be able to grow and evolve their ecosystem. The ongoing concern and complexity for ecosystems is ensuring that they are able to measure impact well enough so they can determine which approaches are more effective than others and which outcomes have actually been the most impactful.
**Under or over compensation**
Proposals that have a bigger scope of execution or that are more complex to execute can often have a higher likelihood that compensation for contributors could be under or over estimated. The incentive design for any adopted systems and processes will have a large influence on how often and how likely this outcome occurs. Good incentive design will mean making efforts to ensure treasury assets are not wasted. However it will also mean ensuring that the incentives provided are meaningful so that contribution efforts are not exploited.
**Unfair incentive distribution**
Numerous contributors could be involved in the execution of different proposals. Creating effective incentive mechanisms will mean ensuring that any contributors involved in execution are paid fairly for their contribution efforts based on the amount and quality of contribution they provided. A main area of concern and complexity will focus around how decisions are made to determine which contributions have been most important or impactful and how people's overall contribution is tracked and measured.
## **No incentives**
Not adding any incentives for the contribution process means there is no financial compensation for executing the work involved in completing a proposal that gets selected by voters. Contribution efforts would rely on other forms of incentives.
**Reasons to adopt this approach**
* **Outcome based incentive** - Executing a proposal to achieve some end goal can be both a time consuming and complex task for contributors to commit to. Some contributors might not expect a financial incentive if they may already have a different outcome based incentive that is important enough to them for them to then provide their contribution without financial incentive. Some examples could be community building efforts, public goods or contributing towards personal areas of interest. The more time consuming and complex the execution of a proposal is, the more difficult it could become for these other forms of incentives to remain sufficient. Contributors will likely not have unlimited capacity and willingness to offer large amounts of contribution effort if it doesn’t help support paying for their day to day bills.
* **Small execution scope** - Smaller areas of execution that require a low commitment in time and effort to support could be areas that are more suitable for having no incentives if there are other incentives that are compelling enough to attract willing contributors.
**Concerns for this approach**
* **Limited number of willing contributors -** If no financial incentive is offered there will likely be a much more limited number of contributors that are willing and capable of contributing to the execution of a proposal.
* **Limited execution scope** - Contributors have a limited amount of time in a given day and many will have a limited amount of time they can provide without compensation due to the day to day costs of living. This factor greatly limits the amount contribution effort an ecosystem could expect when adopting a process that does not include a financial incentive.
* **Low incentive to maintain proposals** - Some proposals will benefit from ongoing maintenance of the proposals information so that it is kept up to date. Achieving this will mean voters will remain well informed on what the current state of the proposal is. Adopting an approach that has no incentive will make it more difficult to maintain proposals that require any meaningful amount of contribution effort to keep the information up to date.
## Time incentives
Time incentives are when people are compensated based on the amount of time they contribute. Compensation could be determined based on hourly, weekly or monthly based arrangements.
**Reasons to adopt this approach**
* **Income stability** - Paying contributors based on the amount of time they contribute helps to provide more income stability to those who contribute. This makes it easier for them to focus on the work in front of them rather than constantly needing to chase different incentives to be compensated for their ongoing contribution efforts.
* **Gradual execution incentive** - Time based contribution results in the gradual release of treasury funds to pay for individuals contributions to the ecosystem.
* **Flexibility** - Incentivising peoples contribution through time can help with making it more flexible in what the contributor is working on. This flexibility can be useful for allowing a contributor to realign themselves with generating impact when a larger problem or opportunity presents itself.
**Concerns for this approach**
* **Only somewhat aligned with impact** - If contributors do not perform well or do not generate any impact they would be less likely to be selected again in future voting rounds to be paid as a contributor. This helps to provide some alignment with generating impact however their actual incentive is still based on the contribution time they provided. Time incentives on their own may not be sufficient to consistently generate highly impactful outcomes.
* **Low alignment with faster execution** - The longer a contributor takes to execute some work the more they will get paid using a time based incentive. This creates a misalignment for the contributor to execute at a fast rate. This could be beneficial for mission critical pieces of work that must be done carefully and not rushed, however this factor could also be abused. Providing there is a sufficient supply of willing contributors that want to participate it would be easy enough to replace low performing contributors with other potential candidates.
## Performance incentives
Performance incentives are when someone is compensated due to the speed or quality of their contributions. The contributor could have exceeded expectations in how effectively they executed a piece of work or the outcomes of their efforts were the most efficient or to the highest quality when compared to the efforts of other contributors.
**Reasons to adopt this approach**
* **Alignment for quality and speed of execution** - If the performance of a contributor is measured and then compensated accordingly there is a higher potential alignment for contributors to want to execute faster and to a higher quality to receive this compensation. Contributors would have an incentive to identify their biggest areas of strengths when contributing and to then focus on those areas of strengths to benefit the ecosystem but also to increase the likelihood that they get more performance based compensation. This approach could also help with creating an incentive to identify faster and easier ways to make contributions that lead to the same outcomes, achieving this would mean execution efficiency gains that could benefit the wider cohort of contributors that are doing similar work.
* **Continuous execution incentive** - A performance incentive could be an ongoing process or be something that is handled periodically such as every week, month or quarter. This ongoing execution incentive can help with creating clearer goals that contributors can strive towards when making contributions and could also potentially help with increasing the retention of good contributors. Rewarding good performance can help create a positive feedback loop where people who want to receive good compensation are consistently able to do so when they make meaningful contributions.
* **Flexibility** - Performance incentives do not need to specify exactly what a contributor is working on meaning the contributors are flexible to identify themselves exactly what areas they believe they are most effective in and could perform most effectively in.
**Concerns for this approach**
* **Performance measuring complexity** - Measuring each contributor's performance to reward high performers can be time consuming and complex. Each contributor's exact contributions will be different and the real benefit of their contributions might not be immediately obvious. If these incentives are not well managed and distributed fairly there is a risk of conflict between contributors and could also be discouraging for contributors to participate in the future if they don’t feel their contribution efforts have been truly appreciated.
* **Risk-taking behaviour** - If executing at a faster rate is part of the incentive structure there is a risk that contributors try to execute too quickly in an attempt to receive more of the incentive. This could be counter productive if the outcomes of the work are more mission critical for the ecosystem or the general risk tolerance is low.
* **Income volatility** - Performance based incentives could result in some contributors receiving far more compensation than others based on just their performance. Adopting a performance based incentive on its own could lead to high levels of income volatility which could be unsustainable for many contributors. Mixing this incentive approach with time based incentives could be one way to prevent this volatility.
* **Gaming the system** - Contributors could identify areas of contribution or ways to contribute that are more effective than others for receiving high levels of performance based incentive. These areas of contribution or ways of contributing may not lead to meaningful improvements for the ecosystem to justify the cost of the incentive. Any adopted incentive mechanisms will need to reflect on which areas are receiving more or less of the incentive over time and consider the ramifications of what might happen if those outcomes persist over time.
## Task incentives
Task incentives are when compensation is rewarded after the execution of some defined piece of work. Example areas of contribution could be for helping with moderation, providing valuable feedback & discussion, voting, making suggestions for information changes or reporting an application bug.
**Reasons to adopt this approach**
* **Targeted incentive** - Task incentives can be highly focussed on achieving specific goals and outcomes that can be beneficial to an ecosystem. Task incentives can be effective for consistently generating impactful outcomes when it is known that the contribution effort that helps with executing the defined task will be useful for supporting or improving the ecosystem.
* **Participation** **scalability** - A well defined task incentive can make it easier to scale the contribution efforts across a large number of participants. This is useful when it is beneficial to have a larger number of people help with the contribution efforts to achieve the intended outcome.
* **Low to medium sized tasks** - Task incentives will often be compensated at the point of completion - although not necessarily they could also be compensated prior to execution! If the scope of the task becomes too large the task incentive approach becomes less suitable due to the larger delay in the incentive for the contributors who participate. The larger the scope of the task the more it may benefit from other approaches such as time incentives or milestone incentives so that the incentive is more gradually and fairly released.
**Concerns for this approach**
* **Incentive size complexity** - A task incentive can increase the complexities around the scoping of work involved, understanding the time it will likely take and then matching this expected contribution effort with a sensible incentive amount.
* **Unforeseen outcome complexity** - Part of the complexity for task incentives is understanding the different ways a contributor might approach the task and how those outcomes could lead to suboptimal results that were not intended or beneficial to the ecosystem.
* **Gaming the system** - Contributors could find ways to exploit task incentives by either rushing the execution or identifying easier ways to arrive at an accepted outcome with less contribution effort just to receive the compensation more easily.
## Milestone incentives
Milestone incentives can be used to better group together pieces of work that can then be executed independently. Milestones will often be executed one after the other until the final intended outcome is executed and delivered.
**Reasons to adopt this approach**
* **Execution based incentive** - Creating milestones to plan out any contribution efforts will help with increasing the alignment that contribution efforts lead to the execution of a proposal to create the outcomes originally intended. Milestones create the need for the execution of future outcomes so that the contributors can receive the next milestones worth of compensation.
* **Thorough execution planning** - Adopting a milestone approach can be an effective way to break down complex ideas into smaller and more manageable pieces of work. Making milestone based plans can help with better informing any voters on whether the execution plan appears to be feasible and sensible. A milestone approach is not required to break down complex problems into different milestones of execution however this approach could be one effective way for ensuring that this always happens.
* **Clearer outcomes** - Planning ahead with milestones can help with communicating the exact intentions and future deliverables of each project. For situations where the voter wants to be highly involved in knowing exactly what gets executed ahead of time this would be an effective approach to ensure the voters are well informed prior to selecting any potential project.
* **Risk mitigation** - Breaking down complex projects into more manageable groupings of work can help with identifying potential risks that might occur and different skill sets that will be required. Understanding these different execution factors can help with identifying strategies to mitigate those risks.
**Concerns for this approach**
* **Planning & estimation complexity** - Planning out complex projects can be highly time consuming and complex. Attaching compensation to these estimations and plans increases this complexity further as any mistakes in the milestone planning could easily lead to under or over compensation for certain milestones. Large delays could occur with the release of compensation if existing works take longer than expected which could cause conflict or discourage existing contributors from participating in the future due to the upfront complexity involved. Proposers may also end up overestimating the time required on purpose to ensure they are always sufficiently compensated for their efforts or alternatively underestimating the time required to increase the chances they get selected for funding.
* **Change of execution plan complexity** - If milestones are set ahead of time at the proposal stage then complexity can easily emerge if the idea needs to change due to a changing environment or other factors. This adds complexity to the milestone approach as the milestones themselves may need to be updated or changed in the future after they are set. If a governance process is added to handle these requests to change the milestones this only further adds to the complexity as then these moderators could have an influence over how projects are able to pivot and adapt to different factors.
* **Rushed execution** - If compensation is released at the point of executing milestones then contributors may decide to rush the execution of milestones to get compensated more quickly. This could be because they are trying to game the system or be because the work was underestimated at the time it was planned. Now the contributors might need to rush the contribution outcomes in a milestone just to make sure they can pay for day to day bills.
## Impact incentives
Impact incentives provide compensation when contribution efforts achieve impactful outcomes. Generating impact could mean helping to achieve some predefined outcome that was already desired or alternatively it could be rewarding an emergent outcome that created impact that wasn’t originally planned.
**Reasons to adopt this approach**
* **Outcome oriented** - Offering compensation when impact is generated helps to align the incentives for contributors to direct their efforts towards generating as much impact as possible. The better this is achieved the more quickly and effectively an ecosystem might be able to grow due to contributors consistently generating impactful outcomes.
* **Flexibility** - Generating impact can come in many forms, impact could be generated across numerous areas in an ecosystem. Contributors have a lot of flexibility in determining how they will be able to direct their contribution efforts towards initiatives that they believe will be the most impactful.
* **Priority alignment** - Providing compensation to contributors who help address existing ecosystem priorities could be an effective way to align the incentives of contributors to generate impactful outcomes through addressing important problems and opportunities that exist in the ecosystem.
* **Encourages experimentation & innovation** - Impact based incentives can help with rewarding contribution outcomes that end up generating impact. This incentive could help with inspiring contributors to experiment with new and different approaches that open up new opportunities or improvements to the ecosystem.
**Concerns for this approach**
* **Impact measurement** - Impact can be difficult to quantify and measure. Some areas of impact could be more qualitative such as providing a certain experience or changing how a community feels about something. These outcomes can be difficult to quantify and measure but could still have a significant impact on growing and supporting an ecosystem. Other areas of impact could go unnoticed or be difficult to spot. Capturing feedback about different areas of impact would also be complex to scale, mostly due to the difficulty of trying to get a large number of people to provide feedback about many of their experiences in the ecosystem and which of those did or didn’t offer them value.
* **Gaming the system** - Contributors might try to game impact based incentives by looking for short term areas of contribution that align with what people are most thinking about at that moment. If a contributor focusses on where attention currently is at that moment it could be easier to get their contribution efforts seen by other community members to then be rewarded for those efforts. How impact gets measured and rewarded will influence how contributors allocate their time so this will be something to continuously consider and reflect on.
* **Delayed compensation** - It takes time for a contributor to create meaningful outcomes and for those outcomes to then be measured to determine whether they created impact. Only focussing on whether impact is generated could end up causing highly delayed compensation for larger projects.
* **Risk of no compensation** - If the entire incentive available is based on whether contribution outcomes make impact or not there is a high risk that some people's contribution efforts lead to no impact and no compensation for their efforts. This problem could be prevented by combining an impact incentive approach with time incentives or milestone incentive approaches.
* **External dependencies risks** - Generating impact can sometimes rely on external influencing factors that are out of the control of the contributors who helped execute some area of work. This makes it more problematic to rely solely on impact based incentives.
* **Unfair incentive distribution** - Due to the complexity of measuring impact it could be easy for certain areas of work to be overlooked and be less understood on the impact those efforts have helped to generate. If these impactful outcomes get unnoticed then the incentive could be distributed unfairly between the contributors involved. Unfair funding outcomes could lead to an environment that discourages contributors from participating in the future if they were not fairly rewarded for the impact they generated.
# Creating impactful outcomes
Example areas that a funding process may focus on to create impact
Ecosystems can each have their own set of principles, values, priorities and other areas of impact that they could be trying to address or support when disbursing treasury assets to different areas and initiatives.
There are a variety of different ways an ecosystem could create impact for its community members and other members of society. Some of these potential areas can include:
* **Supporting ecosystem principles & values** - A set of principles or values that the community members have or that are more formally adopted by an ecosystem.
* **Addressing ecosystem priorities** - Prioritisation of the most important problems and opportunities that will help an ecosystem achieve its longer term goals.
* **Creating positive impact** - Outcomes that generate a positive impact for other areas that society values such as the environmental concerns, human welfare or other public goods.
Initiatives that receive treasury funding to generate any of these outcomes could end up doing so in a multitude of ways - sometimes intentionally and sometimes not! One initiative may not be successful in addressing certain ecosystem priorities it was trying to address but might have been very successful in supporting and fostering strong principles and values held by community members and the outcomes generated ended up attracting more people into the ecosystem who shared those values. Others may succeed in addressing numerous ecosystem priorities however could still have more substantial success in other areas such as making impact for an environmental based public good outside of the ecosystem.
Thinking about what will create any meaningful impact from the use of disbursed treasury assets will be useful for exploring and analysing how future contribution efforts towards different initiatives can be measured against the impact they generate. Effectively identifying when funding is being directed towards impactful initiatives will help make it easier to continue directing funding to initiatives that are consistently generating meaningful outcomes.
## Supporting ecosystem **principles & values**
Individual community members may join some ecosystems based on the principles and values being exhibited from the ecosystem. An ecosystem may be doing this formally through a written set of principles and values, mission statement or constitution. Alternatively these principles or values may come from the community in a more bottom up approach where they are being demonstrated through the social and working dynamics of the community.
**Example principles**
* **Decentralisation** - Distribution of control and decision-making among a broad group of stakeholders rather than a centralised authority.
* **Transparency** - Prioritising open and transparent processes, from codebase accessibility to governance decisions.
* **Security** - Ensuring the highest levels of security to protect data integrity, users information and their assets.
* **Privacy** - Respecting user privacy and providing mechanisms for anonymous or pseudonymous interactions.
* **Open access** - Allowing anyone, regardless of their geographic location or socioeconomic status, to have equal access to the network and protocols.
* **Open source** - A commitment to making codebases publicly available for scrutiny and improvement.
* **Modularity** - Designing the ecosystem to be adaptable and extendable, so new features or upgrades can be integrated easily.
* **Resilience** - Building redundancy and robustness into the system to ensure it remains functional under any stress or attack.
* **Innovation** - Committing to a pursuit of ongoing research and development to support technological, social and scientific advancements amongst many others.
* **User-centric design** - Prioritising the needs and experiences of end-users in all phases of development.
* **Sustainability** - Making decisions with long-term viability in mind, including environmental sustainability.
* **Verifiability** - Ensuring that transactions and data are publicly auditable.
**Example values**
* **Community empowerment** - Creating a sense of ownership and involvement among community members.
* **Ethical conduct** - Upholding ethical standards in all activities, including partnerships, development, and community engagement.
* **Inclusivity** - Striving for a diverse and inclusive environment where everyone feels welcome and heard.
* **Collaboration** - Encouraging teamwork and partnership both within the community and with external stakeholders.
* **Integrity** - Maintaining consistency of actions, values, and outcomes, standing by commitments even when it's challenging.
* **Trust** - Building and maintaining the trust of users, developers, and other stakeholders through consistent and transparent actions.
* **Sovereignty**: Empowering individuals to have control over their own data, assets, and decisions.
* **Responsibility** - Being accountable for the ecosystem's impact, whether social, economic, or environmental.
* **Fairness** - Implementing algorithms, governance models, and features that help to generate and maintain equitable outcomes.
* **Excellence** - Striving for the highest quality possible for code, user experiences and community interactions.
* **Flexibility** - Willingness to adapt to new technologies, regulations, and community needs.
* **Experimentation** - An open mindset towards trialling new governance models, economic theories, or technical solutions.
* **Resource efficiency -** Effective and responsible use of community assets and treasury funds.
## **Addressing ecosystem priorities**
Ecosystems can choose between a range of different priorities when deciding what potential initiatives could create the most impact for the ecosystem. Good prioritisation will result in addressing the most important problems and opportunities that exist in an ecosystem.
**Example priorities**
* **Community governance** - Support initiatives that help to remove middlemen and increase the transition of decision-making power from a centralised entity to a decentralised community.
* **Interoperability** - Support interoperability efforts that integrate and use various blockchain ecosystems and platforms to enrich the ecosystems overall utility.
* **Financial inclusion** - Support for initiatives that help decentralised financial services reach more underserved and unbanked communities around the world.
* **Regulatory compliance** - Efforts that help an ecosystem with regulatory compliance and any associated challenges or relevant policy advocacy.
* **Infrastructure scalability**: Ensuring that the network is capable of handling increasing load by allocating resources to scalability solutions.
* **Technical leadership** - Identifying initiatives that help with technical innovation so that the ecosystem can stay ahead with further technological advancements.
* **Applications & services** - Support the introduction and improvement of applications and services that help to cater for important use cases that are valued by community members.
* **Immutable auditability** - Support of any system improvements that help with improving auditability so that community trust can be further increased over time.
* **Global adoption** - Efforts that help to extend an ecosystem's presence in multiple countries and languages to attract a more diverse user base.
* **User onboarding** - Investing in intuitive user interfaces, tutorials, educational content and resources to foster and encourage more user adoption.
* **Security** - Conducting audits and updates to secure the network against vulnerabilities and attacks.
* **Community engagement** - Initiatives that help to actively involve the community in decision-making processes, development, and promotional activities.
* **Incentive design** - Design incentive mechanisms that engage community members and that function well to create impactful long term outcomes.
* **Developer experience** - Support the creation and maintenance of APIs and software development kits that developers can use to more easily create their own solutions.
## **Creating positive impact**
Outcomes generated from funded initiatives could also help with creating impact across a number of other areas in society. Generating outcomes that are more widely beneficial to society can make a tremendous difference.
**Example areas of impact**
* **Open source software** - Public and freely available software that can be used or modified by any person for their own use cases and development efforts.
* **Decentralised infrastructure** - Creating resources and infrastructure that advances the current state of the art for the development of distributed networks.
* **Legal systems** - Improving legal and court based systems and services that can then help to better maintain societal order and justice.
* **Voting systems** - Improve people's access to and participation in important problems and issues that benefit from more inclusive and diverse decision making systems.
* **Charitable causes** - Initiatives that help people in need regardless of their background.
* **Environmental causes** - Generating outcomes that help with the sustainability of the different areas that make up our planet such as clean air, marine life, natural parks and wildlife reserves, oceans and waterways amongst many other areas.
* **Public infrastructure** - Support any improvements made to public infrastructure such as bus services, subway systems, roads, bridges, public squares and parks, airports or any other public infrastructure.
* **Education** - Support the creation of educational resources that help with improving society's understanding and access to knowledge covering any variety of areas that are valued by society.
* **Publicly funded research** - Scientific research and development that help advance the state of the art in different fields that benefit society at large.
**Sustainable development goals**
The [sustainable development goals (SDG’s)](https://sdgs.un.org/goals) were created “as a shared blueprint for peace and prosperity for people and the planet, now and into the future”. These goals also provide similar examples of the types of areas that could help with creating positive impactful outcomes:
* **No poverty** - Eliminate poverty in all its forms everywhere.
* **Zero hunger** - End hunger and ensure access to food for all.
* **Good health and well-being** - Ensure healthy lives and promote well-being for everyone at all ages.
* **Quality education** - Provide inclusive and equitable quality education for all.
* **Gender equality** - Achieve gender equality and empower all women and girls.
* **Clean water and sanitation** - Ensure availability and sustainable management of water and sanitation for all.
* **Affordable and clean energy** - Provide access to affordable, reliable, and clean energy for everyone.
* **Decent work and economic growth** - Promote sustainable economic growth and decent work for all.
* **Industry, innovation and infrastructure** - Build resilient infrastructure and foster innovation.
* **Reduced inequality** - Reduce inequality within and among countries.
* **Sustainable cities and communities** - Make cities and human settlements inclusive, safe, and sustainable.
* **Responsible consumption and production** - Ensure sustainable consumption and production patterns.
* **Climate action** - Take urgent action to combat climate change and its impacts.
* **Life below water** - Conserve and sustainably manage aquatic ecosystems, including oceans, seas, and marine resources.
* **Life on land** - Protect and restore terrestrial ecosystems and halt biodiversity loss.
* **Peace and justice strong institutions** - Promote peace and justice, and build effective, accountable institutions.
* **Partnerships for the goals** - Strengthen global partnerships to support and achieve the SDGs.