Insight: Survivorship bias is very common in finance and areas of risk.
Insight: People often neglect "invisible" data or cases.
Insight: The stories we hear are rarely of the unsuccessful - there is often no incentive to tell uninteresting stories of failure.
Principle: Actively seek out data or stories from those that don't survive.
Insight: Survivorship bias plays a big role in investment funds. The ones that die don't show up in the numbers over time, inflating the average returns.
Reference: Abraham Wald: "Bullet hole problem" during WWII.
Insight: Data often doesn't account for dropouts - those that try and give up.
Insight: Finding evidence of dropouts is often difficult.
Insight: The possibility of survivorship bias doesn't always mean that results aren't representative or useful.
Insight: Often those that respond to surveys are those that have had positive results - you are only asking the survivors.
Reference: Mathematician Abraham Wald: During WWII he was asked by the RAF to analyse planes that had flown in battle to see where the most bullet holes were, so that these areas could be reinforced. He quickly realised that what was not being taken into account was the planes that didn't make it back (the RAF had made a survivorship bias). He then made the recommendation to reinforce areas where the planes had no bullet holes, as these were most likely to be the vulnerable areas - where the planes that didn't make it back had been shot.
Insight: Survivorship bias means that the highest performers are the most visible, because the losers are not visible.
Insight: Luck should be accounted for when analysing success.
Insight: When setting goals we concentrate on successful individuals and organisations. The problem with this is that this does not account for those that didn't succeed - we have a survivorship bias.
Insight: Goals set direction, but systems are more important for making progress.
Definition: When we look only at the data of those that succeed or survive and ignore the data that related to those that failed.
Insight: Survivorship bias plays a large part in investment funds overstating returns because those that fail are not included over time.
Key Insights & Principles
Planning and Decision Making
We often overestimate success, and look only at data or examples from those that succeed, and ignore the failures.
Luck is often overlooked when analysing success.
Survivorship bias does not mean that data or insights are irrelevant.
Actively search for data or stories of non-survivors.
