Survivorship bias

Self Assessment

Survivorship bias is a cognitive bias that occurs when an analysis only considers the 'survivors' or successful entities of a group while overlooking the failures, thereby skewing the results and leading to erroneous conclusions. This bias stems from the human tendency to draw inferences based on incomplete data, largely due to the absence of information about non-survivors.

How it works

Survivorship bias works by filtering out non-survivors or failures and focusing only on successful cases, often leading to misleading conclusions. This results in a distorted view because the data analyzed represents only those who 'survived' or succeeded, rather than a complete picture that includes both successes and failures.

Examples

  • During World War II, damage assessment of returning aircraft led to recommendations for reinforcing areas that survived attacks. Statistician Abraham Wald suggested reinforcing areas with no bullet holes, realizing that aircraft hit in those areas didn’t return at all.
  • In finance, evaluating mutual funds based only on the current winners ignores funds that have performed poorly and closed, leading to an overestimation of industry-wide success rates.
  • In entrepreneurship, focusing on stories of successful entrepreneurs but ignoring those who failed can create a misleadingly positive picture of success probabilities.

Consequences

Survivorship bias can lead to overly optimistic expectations and underestimation of risks. By focusing only on successful outcomes or surviving entities, important lessons from failures are often disregarded, which can result in flawed strategies or the misallocation of resources.

Counteracting

To counteract survivorship bias, it is essential to seek out data on both success and failure cases, ensuring a comprehensive analysis. Including diverse perspectives and fostering an awareness of omitted data can help mitigate the effects of this bias.

Critiques

One critique of survivorship bias is that it oversimplifies complex systems by ignoring a multitude of factors leading to success or failure. Critics argue that while acknowledging survivorship bias is beneficial, real-world scenarios often involve variables that are not easily accounted for.

Fields of Impact

AI
History & Historiography
Psychology & Social Science
Economics & Finance
Business & Entrepreneurship
UX
Political Science & Public Policy

Also known as

Survivor bias
Survivors’ bias
Success bias

Relevant Research

  • Historical patterns of aircraft survivorship: An application of survivorship bias

    Piatkowski, T. M., & Krug, E. J. (2019)

    Journal of Historical Economics and Econometric History

  • Does the stock market overreact? The Journal of Finance, 40(3), 793-805

    Bondt, W. F. M., & Thaler, R. (1985)

  • Performance persistence

    Brown, S. J., & Goetzmann, W. N. (1995)

    The Journal of Finance, 50(2), 679-698

Test your knowledge

Check your understanding of Survivorship bias with a short quiz

Apply what you've learned and reinforce your understanding of this cognitive bias.