Hello everyone,
We’re here to report back on our first prototype test with Collabberry and RnDAO.
Collabberry was born from the RnDAO’s fellowship program, and they’ve been our first supporters, partners, and mentors. Compensation is a very relevant problem to RnDAO as well, as they struggle with it and have done a lot of research, and designed their own system, which Collabberry learned a lot from.
It was a great milestone for us, to have our first prototype tested and potentially in future implemented by the RnDAO team.
The way it all started was that in Collabberry we were working on a prototype and wireframes for the model, when a team member of RnDAO reached out, looking for some input as he was trying to solve some of the problems with their compensation model.
We quickly pinpointed some of the problems that Collabberry solves by design and decided to put the effort into building a fully functioning compensation tool, instead of a clickable prototype. We use very much centralized but out-of-the-box tools, such as Google Sheets, Google Forms, and Discord, but with that we managed to develop a fully functioning prototype.
The nature of Startups and early-stage projects is inevitably dynamic and flexible, and there’s a need for a compensation model that is as well. Negotiation and lack of transparency lead to unfairness in the team and inevitably bring tension to the team. Founders spend a tremendous amount of time doing admin related to salaries and equity packages, trying to measure value and managing the team, to make sure that everyone delivers on their promises, and dealing with legal entities for all of this to work.
Collabberry aims to bring decentralization and trust in this process, by allowing the team to measure the value brought, through peer-to-peer assessment, and introduce dynamic ownership, so that a contributor can be dynamically and on-the-go compensated with team points, rewarded for the value they brought month by month.
We aim to create a collaborative environment with aligned incentives and fair compensation.
Collabberry’s compensation is based on an agreement between the organization and the contributor, a peer-to-peer assessment process for measuring value, and an algorithm with an outcome of a compensation package with monetary and ownership components, to reward everyone, ensuring all their essential needs are covered.
The first input of Collabberry’s algorithms is the agreement that the contributor has with the organization. This agreement can be reached by putting up a proposal, in the DAO world, or through a standard process of communication between the contributor and founder.
The parameters of this agreement are the following: