Concept
Survivorship Bias
Survivorship bias is the error of drawing conclusions only from the people, companies or things that made it through a filter, while ignoring the far larger number that failed and so disappeared from view.
Success is loud and failure is quiet. The founders who made it give interviews. The thousands who closed their doors don't. The funds that beat the market keep advertising, while the ones that lost were quietly merged away. So the evidence we see around us has already been filtered, and we mistake the filter for a recipe. The traits the winners share often turn out to be common among the losers too. Rolf Dobelli puts it bluntly in The Art of Thinking Clearly: we systematically overestimate our chances of success because the graveyard of failed attempts is invisible. A classic illustration comes from the Second World War. Statistician Abraham Wald was asked where to add armour to bombers. The returning planes had bullet holes on the wings, so Wald pointed to the engines, where there were no holes. The planes hit there never came back. The useful question is always: what am I not seeing?
A real-life example
Maya, a nurse in Leeds, binges podcasts about novelists who quit their jobs and hit the bestseller list. She drafts a resignation letter. Before sending it, she looks for the other side. She finds an author-income survey showing most published novelists earn far below a living wage from books. She also learns that countless finished manuscripts never find a publisher. She keeps her job, writes in the mornings and gives herself a two-year test instead.
How to use it
- 1Before copying a success story, ask how many people tried the same thing and where they are now. Then go looking for them, not just the winners.
- 2Find the base rate: what share of similar attempts actually succeed? Start from survival data for the field, not from interviews.
- 3Study failures as seriously as wins. Talking to five people who gave up often teaches more than the biography of one who made it.