Survivor Bias

In statistics, there is a concept called “survivor bias,” which refers to researchers only focusing on the common traits of “survivors” while ignoring information from those who “failed.”

A classic example is during World War II, when mathematician Abraham Wald was tasked with studying how to reinforce the armor of British bombers. On the aircraft returning from missions, bullet holes were mainly concentrated in the wings and the tail, but Wald believed that the cockpit and fuel tanks should be reinforced, because bombers that were hit in those areas never even made it back.

The same logic also applies to books that talk about entrepreneurs’ success secrets: blindly copying the advice in those books doesn’t mean you can replicate success. What’s more valuable is analyzing the mistakes made by companies that ended up going bankrupt.

It’s the same in our circle. Everyone always keeps their eyes on the very few, the most sensational success stories. For example, someone might have made millions on SHIB or NFT projects, yet hardly anyone analyzes what exactly went wrong with the bankrupt exchanges and funds: fraud, high-leverage trading, and failures in risk control.

Learn lessons from other people’s mistakes—sometimes the cost of your own mistakes can be far too heavy!