Survivorship bias

Hypothesis assessment biases biases

Survivorship bias is when we focus on the people or things that "survived" a process—success stories, companies that didn't fail, people who made it—and overlook those that dropped out. The full picture is distorted because the failures are invisible or forgotten, so we overestimate the chances of success or the value of a path. Related: Exception fallacy, Anecdotal.

Examples

  • "All these famous people dropped out of school" ignores the many more dropouts who did not become famous—so we overestimate the link between dropping out and success.

  • We study successful companies to learn what made them succeed, but we rarely study the many similar companies that did the same things and failed.

  • Old buildings seem to have stood the test of time, so we assume building methods of the past were better; we forget the many old buildings that collapsed or were demolished.

  • People who succeeded after taking big risks are celebrated; we hear less about those who took the same risks and lost, so we overestimate the wisdom of risk-taking.

  • A diet or fitness programme is promoted using before-and-after stories of people who got results; we don't see the many who tried it and saw no change or dropped out.

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