TL;DR: A decision can be right even if the outcome is bad — and wrong even if you got lucky.
This protects you from judging decisions purely by what happened afterward.
An investor may back ten startups knowing several will fail because the payoff distribution still makes the bet rational.
Confusing confidence with edge.
A decision can be right even if the outcome is bad — and wrong even if you got lucky.
You are here because this concept becomes more useful after Decision Trees and before Prioritization.