Survivorship bias is the logical error of focusing on entities that passed a selection process while overlooking those that did not — skewing our understanding of success.
The WWII Bullet Holes Story
During WWII, analysts proposed reinforcing the parts of returning planes that showed the most bullet damage. Statistician Abraham Wald pointed out the fatal flaw: they were only looking at planes that came back. The planes that got hit where the returnees showed no damage were the ones that didn't make it home. Reinforce the undamaged areas — that's where the fatal shots were landing.
Modern Examples
- Startups: We hear success stories. We don't hear about the thousands that failed the same way
- Investing: Mutual fund performance data excludes funds that closed due to poor returns
- Self-help: Advice from successful people reflects what worked for survivors, not for the majority who tried and failed
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