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 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.

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