A Startup Quest towards a decent Reward System (part 2)

In this post, we’ll tell you about a first set of lightweight experiments we did, using only a handful of ironing beads and an enthusiastic group of Kunlaborants.


This is the second post in a series about installing a transparent, honest and efficient reward system at Kunlabora. In the first post we talked about how you quickly end up with a bloated system and how we would like to avoid this. We’re wondering whether we can leverage our open culture to help us achieve this. We need to do some experiments and learn from their results and feedback.

We understand that a reward system consists of more than only a number on your paycheck. Non-billable time (experiments, training, …) is very important to us, and the total remuneration at Kunlabora can also contain things like a company car or a hospitalization insurance. But for our experiments, the question at hand is “how does an employee’s gross salary evolve?”.

The Lightweight approach

Alright, time for our first experiment. Suppose you have a yearly budget you can spend to grow the gross salary of your employees. We were curious whether we could get an honest result by doing an exercise that has the following requirements:

  • no heavy tooling
  • time spent per person is about 30 minutes
  • involves everyone
  • builds upon our transparency (all employees can lookup what another employee earns)


We had 14 employees to conduct our experiment with. We formed a big circle and everyone was given 2 sheets of paper. One sheet contained the names and gross salary for each employee. The other sheet was to fill in the results for the experiments. I “borrowed” my daughter’s bucket of ironing beads and we handed out an equal amount of beads to each employee. We gave everyone a “simple” task: you must divide your beads amongst your colleagues, knowing that the amount of beads they receive, will have an impact on their gross salary. After everyone was done handing out their beads, we counted our beads and we formed a single file line, ordered by the amount of beads received.

We did 6 experiments like this, but each time with small variations on certain aspects. One such aspect was about the effect on the gross salary. In one variation, only the top 30% of the employees would receive a raise. In another variation, everyone would receive a raise, proportional to the amount of beads received. Another aspect we varied on, was the amount of beads to divide. For each experiment, we asked our contenders to write down some feedback.



Some feedback we gathered about the variations in the experiments:

  • About the impact on the salary
    • Everyone receives a raise: a more social system where everyone is rewarded for their hard work
    • Only top 30% receives a raise: less social, but maybe more honest towards those that really deserve a decent raise
    • The cut-off at 30% is brutal and arbitrary
  • About the amount of beads to divide
    • Too little beads –> very hard to divide and to reward everyone who deserves it
    • Too many beads –> results in a more social, but maybe less honest, division where everyone gets something
    • In general, having the amount of beads equal to the number of employees seems like a nice fit


After all experiments were done, we did an open feedback round. These were the main reactions:

  • Things we liked:
    • Everyone is involved
    • Simple and quick
  • Things that need improvement:
    • There is a possibility that people with high exposure have an advantage
    • There is a possibility that people mostly hand out beads to team members, because they don’t know the other people all that well
    • There is no written/verbal feedback as to why person X gave (no) beads to person Y
    • The differences in gross salary are not very visual (this was presented as tabular data on a sheet of paper)

Up next

Are we done?

No, not quite…

An early conclusion could be that, in general, it felt as if the end result of how accurate people are estimated, is the same of what you can expect from a “classic” system, as are the risks of misevaluating someone. However, the cost for attaining that result is much smaller and we’ve gained that beloved thing called transparency!

We feel that we want to continue experimenting, our system is surely not yet “mature”. So the next step for us is to come up with a new experiment. One that embraces the things we liked, but addresses the shortcomings we identified.

We asked our employees to write down ideas. What would your advice be?

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