I was able to run some stats at scale on this and people who make mistakes are more likely to make more mistakes, not less. Essentially sampling from a distribution of a propensity for mistakes and this dominated any sign of learning from mistakes. Someone who repeatedly makes mistakes is not repeatedly learning, they are accident prone.
Can you elaborate? What scale? What kind of mistakes? This sounds quite interesting.
What if you define a hard rule from this statistics that « you must fire anyone on error one »? Won’t your company be empty in a rather short timeframe? [or will be composed only of doingNothing people?]
Why would you do that? You’re sampling from a distribution, a single sample only carries a small amount of information, repeat samples compound though.