One of the main assertions of this blog post is that, "Startup employee effectiveness follows a power law" rather than a normal distribution.
Much like startup performance follows a power law, so do startup employees. The most effective employees create 20x more leverage than an average employee. This is not true in an efficiency company — the best employees might work 2x faster than their peers. But in a high-leverage startup like ours, the effectiveness gap between employees can be multiple orders of magnitude.
Our minds find it easier to think in terms of efficiency and normal distributions than leverage and power law distributions. So we mentally squash the employee power law curve into a normal distribution curve. We underestimate the most effective employees and overestimate the ineffective ones.
Aside from the fact that this is a gross over-simplification of productivity within the context of development, I think the reason why we assume a normal distribution is because thats how any random variable with a population works (I'm assuming within the population of professional developers programmers).
I've also similar claims to this, in the form of the, "10x engineer".
Can anyone provide any research to back up these assertions? Or perhaps someone with a better understanding of stats help?