Broad vs Specific Categorisations
Comparing funding categorisation based on the specificity of the categorisation
Last updated
Comparing funding categorisation based on the specificity of the categorisation
Last updated
Categorisation can be either broad and cover a large range of focus areas or be more specific and cover more specific idea focus areas.
No categories - Funding is distributed through a single categorisation. Proposals compete with every other proposal. This is the most broad form of categorisation.
Broad categories - Funding is allocated between a small number of broad categories with a budget weighting applied to each of them. Examples categories include Products & Integrations, Governance & Identity and Development & Infrastructure.
Specific categories - Funding is allocated between a large number of specific categories that would have a smaller budget distributed between each of them. Example specific categorisations could focus on groupings such as AI & machine learning, transportation or DeFi.
Very specific categories - Funding is allocated between even larger number and more specific categorisations with small budget weightings. Example categories that would be very specific could be Japan local events, DeFi in Botswana or IoT for agriculture farming.
Budget weighting complexity - What level of complexity exists when the community needs to decide the budgets that should be applied to each of the funding categorisations?
Proposal visibility - How easy is it for proposals to be seen in the funding process?
Directing funding precision - How effective is the categorisation for directing funding to certain areas? How much can the outcome of each funding round vary in terms of what focus areas receive funding?
Proposer effort - How much effort is required by proposers who need to submit proposals into the funding categorisations being used?
Proposal assessor effort - How much effort is required by the proposal assessors who will assess the categorisations?
Category team effort - How much effort is required by the category teams who create, support and maintain the categorisations?
Voter proposal decision complexity - How complex are the decisions when voting on proposals due to the categorisation approach?
Level of competition - What is the impact of the categorisation approach on competition? High competition can be good for selecting the best proposed ideas from a wider range of proposals but this comes at the cost of making it more challenging for smaller teams. Lower competition for categorisation has the benefit of helping spread the competition difficulty that will help smaller teams but comes at the cost of an increased chance of funding innovation that is lower quality due to less competition.
Challenging funding situations - How does the categorisation approach handle situations where only a few proposals turn up for the categorisation or the proposals that turn up are of low quality? What happens when proposals for areas that are lower priority are a higher quality than the proposals that are focussing on areas the community considers higher priority?
Advantages
No budget weighting complexity - All funding is available in one categorisation meaning no budget weightings need to be determined in each funding round. No decisions need to be made about budget weightings meaning there is no governance effort needed.
No proposer effort - Proposers would not need to consider multiple categorisations and would just submit their proposals in a single categorisation.
No proposal assessor effort - No assessments would be needed on categorisations.
No category team effort - No categorisations need to be created or maintained.
Very effective in challenging funding situations - A single categorisation means there is much lower risks of being able to handle challenging funding situations as every focus area can submit proposals. This means that only a small number of focus area needs to provide proposals of a sufficient quality and the voter can respond to this situation accordingly by just supporting the quality proposals. As all ideas from every focus area can be submitted there is a far lower chance of there being risks around not receiving enough proposals due to the incentive for the community to propose ideas in return for a financial incentive.
Issues
Very low proposal visibility - With just one category it becomes hard for individual proposals to stand out against all other proposal teams. This results in an increased need for proposal standards and better tagging approaches to help with sorting, comparing and filtering proposals as well as potentially community curated lists so that small proposals can more easily get better visibility.
No directing funding precision - No effort is made at the categorisation level to direct any funding towards certain focus areas in the ecosystem. Funding outcomes would see a very large variance in what focus areas receive funding. Some focus areas could more easily receive no funding repeatedly for many funding rounds. Not using categories increases the issues around the process being impacted by instances where it becomes a popularity contest. This issue would result in the most popular teams or focus areas inadvertently and repeatedly receiving more funding than is desired or needed. This could result in funding distribution that is less effective for supporting and improving the ecosystem. Voters benefit from a high level of control in determining where funding should be allocated however without tools, processes and infrastructure to make that decision more effortless there is an increased risk of causing voter paralysis. This due to the complexity of pushing every possible combination of decision to the voter at the voting stage to handle themselves. Robust and well refined voting infrastructure would be needed to facilitate the communities ability to effectively direct funding when only using a single categorisation.
Very high competition - High competition can help the best projects from different focus areas rise to the top and receive funding. However using no categorisations would also mean that less known or popular teams and focus areas would need to compete with every single larger or more popular team in the ecosystem as well as against all of the other more popular focus areas. Competition in this environment would be at its highest. The community would need to check on the impacts of this most extreme level of competition and who exactly is receiving funding and what focus areas are most dominant. This would help determine whether this categorisation approach is actually net beneficial for the ecosystem.
Very high voter proposal decision complexity - Voters would need to compare proposals that cover every other possible focus area that exists and then make decisions on which proposals should deliver the most impact. This is challenging due to the wide differences in what the proposals are about, what focus area they address and what stage they are at. Each voter would need to understand these factors and the potential impact of these proposals to make a well informed decision.
Advantages
Low budget weighting complexity - Using only a few categories means the complexity of budget weighting decisions remains low as voters only need to determine the budget to allocate between a small number of categorisations. Broader categorisations don't require the same precision in accuracy as they invite a large amount of proposals to be submitted that cover a range of different focus areas. A relatively low amount of governance effort is needed to make informed budget weighting decisions.
Low proposer effort - Proposers would only need to look at and compare a few categorisations to understand where to submit their proposal.
Low proposal assessor effort - If the broad categorisations used were recurring there would be no effort required. However if they are changing each round then even then only a small to moderate amount of time that would be needed to assess a small number of broad categorisations.
Low category team effort - Only a small number of categorisations would be created and justified. There are a limited amount of broad categorisation variations that will exist. This means that using broad categorisations generally lead to using recurring categorisations which wouldn't need to be defined every funding round. Due to this less effort is required to create and maintain broad categorisations.
Good competition - The smaller the amount of categorisations there are the more competition there is between proposals. Broad categorisations are good for promoting healthy competition but they can also help with the keeping similar groupings of focus areas separated which may be more popular than others. This reduces the implications of some focus areas receiving excessive amounts of funding due to getting more attention and voting power.
Effective in challenging funding situations - The risks around when only a few proposals turn up or when the proposals that do turn up are of low quality are reduced due to the categorisations inviting multiple focus areas to be submitted. Broad categorisations only requires one or a few of those focus areas to present impactful proposals to mitigate these risks. Due to this broad categorisations are more flexible and robust in handling these funding situations.
Issues
Low directing funding precision - Directing funding to more precise areas within the category could be difficult due to the range of focus areas competing in the same categorisation. It still remains the case that the most effective way to direct funding is through voting however the right voting infrastructure is needed to make this easy enough to do for voters. The community could effectively promote the most important focus areas with an independent goal & objective setting process. There are also many other approaches to direct funding that can be explored and integrated to mitigate this potential issue.
Lower proposal visibility - Having only a few broad categories could make it hard for some proposals to stand out against larger more established teams. There could be a need for some form of proposal tagging and community curated lists to help aid in visibility for smaller teams.
Moderate voter proposal decision complexity - Voters would need to compare proposals grouped around similar focus areas when using broad categorisations. This would have at least have some moderate complexity. If the categorisations are well grouped on the focus areas they include then at a benefit would be that the complexity of the comparisons between proposal should be limited. The potential funding outcomes when using broad categories would be somewhat predictable and create some small guarantee for how funding would be directed to a grouping of focus areas. There would not be a guarantee that a specific focus area receives funding in a given funding round as broad categorisations would invite multiple focus areas into a single categorisation. Due to this some focus areas may not receive funding in certain funding rounds.
Advantages
Good proposal visibility - Proposals should be surrounded by proposals that are fairly similar when using specific categorisations. This should make it easier to get clear proposal visibility and understanding for proposals submitted in that specific categorisation.
Higher directing funding precision - Using more specific categorisations make it easier to allocate funding to precise focus areas in the ecosystem. This also creates a guarantee that funding will be directed towards the selected focus areas.
Low voter proposal decision complexity - Voters only need to compare proposals about a similar focus area or small group of focus areas. This reduces complexity around understanding, comparing and selecting which proposals appear more promising in producing the most impact for that focus area. Voters would save effort by not have to make more complex comparisons with other proposals that address very different focus areas.
Issues
High budget weighting complexity - Every extra specific category makes it more complex to determine what budget weighting should be allocated to each categorisation being used. The voters who determines the budget weightings will need to be more well informed on the specifics of that focus area to make an informed judgement on how much funding to distribute to each categorisation.
Higher proposer effort - Proposers must compare a large amount of categorisations before they can submit a proposal.
Higher proposal assessor effort - If the specific categorisations are changing each funding round assessors would require a high amount of time to go through the larger amount of categorisations.
Higher category team effort - More category teams would be needed to create specific categorisations and justify their potential impact in contrast to the other specific categorisations that other teams define.
Higher governance complexity - The more specific categorisation becomes the more complex governance is on providing justifications towards the budgets weightings applied to each categorisation. Complexity is increased for voters in being able understand the full implications of increasing or decreasing the access to funding for certain specific focus areas.
Lower competition - Increasing the amount of categories means there is less competition between each of the proposals in a given category. This increases the chance that categorisations will need to handle a weaker group of ideas and innovation which could lead to worse outcomes.
Not effective in challenging funding situations - Specific categorisations are far riskier in challenging funding situations as the more specific categorisations you have the higher chance there is that one of those focus areas receives a low number or quality of proposals being submitted. Specific categorisations would not be flexible in this event the as they would not allow voters to then redirect funding to other focus areas as the categorisations and budgets were already decided.
Specific categorisation budget weighting complexity
It is difficult to decide how much funding should be directed to specific categories as it is hard to predict what will happen at the proposal submission stage. The more categorisations there are the harder this prediction becomes in determining what a good budget weighting should be and what will actually happen at the proposal submission stage. A process to gather a sufficient amount of data and justification to support every decision would be needed on which area requires more funding over other areas and whether there are any individuals or teams lined up to submit proposals for that focus area. The more that specificity is added to categorisations the more complex and thorough the governance process need to be to effectively decide on final budget weighting allocations. As funding categorisations are set ahead of time this problem is very complex to solve. Due to this uncertainty it would be easier to allow the community to set the priorities for the ecosystem but use categorisations that accept the fact that what the community wants to happen may not actually happen as they wanted it to. It is these risks of poor proposal turn out or quality that further increase the complexity of doing budget weighting decisions for specific categorisations.
Specificity adds significant budget weighting complexity - The more categories that get used in the funding process the more complex it becomes to determine a sensible budget to allocate to each category and the more risks there are that the funding is misallocated due to a lack of proposals or quality proposals for that specific categorisation at that precise time it is being used.
Easier to solve broad categorisation issues - Addressing the problems of low proposal visibility, voter proposal decision complexity and difficulties with directing funding can be more effectively solved by integrating a range of different approaches that help with directing funding. Better tagging, proposal standards, priority voting using an independent goal & objective setting process, curated lists and gathering community feedback are all be potentially effective ways to organise and distribute information to the community to help with improving how funding is directed. These approaches would help to resolve issues around proposal visibility and improving how funding is directed when using broad categorisations.
Broader categorisation takes less effort and governance - Less information, governance and tools are needed to use a broad categorisation approach. Less effort is needed to determine suitable budgets for each category.
