Survivorship bias

Survivorship bias refers to the tendency to focus on the individuals or entities that have succeeded while overlooking those that have failed. This bias can lead to an overestimation of the likelihood of success, as the failures are not taken into account. It can also lead to an underestimation of the challenges and risks that are associated with achieving success.

For example, if you were to study the biographies of successful entrepreneurs, you might conclude that the key to their success was taking big risks. However, if you looked at the biographies of all entrepreneurs, including those who failed, you would see that many of them also took big risks, and that success is not solely determined by taking big risks. This would give you a more accurate and complete picture of the path to success.

Another example of survivorship bias is in the stock market, where investors may only focus on the stocks that have performed well in the past. By ignoring the stocks that have performed poorly, they may overestimate the likelihood of continued success and make poor investment decisions.

Survivorship bias can also be found in the medical field, where studies that focus on the survivors of a disease or treatment may lead to a false understanding of the effectiveness of that treatment. For example, a study that only looks at patients who have survived a certain cancer treatment may lead to an overestimation of the treatment’s effectiveness, because it does not take into account the patients who did not survive the treatment.

Survivorship bias can be seen in many fields, including business, finance, engineering, and healthcare. It can be difficult to avoid, as it can be hard to identify the individuals or entities that have failed. However, it is important to be aware of it and to try to take into account the failures as well as the successes when making decisions or drawing conclusions.

One way to avoid survivorship bias is by looking at the data from a different perspective. Instead of focusing on the survivors, focus on the non-survivors, and try to understand why they failed. Additionally, it is important to make sure that the data is representative, which means that it includes a wide range of individuals and entities and not just a select few.

Another way to avoid survivorship bias is by using multiple sources of data. For example, if you were studying the biographies of successful entrepreneurs, you might want to read books, articles, and interviews, as well as conduct your own research. This would give you a more complete and accurate picture of the path to success.

In summary, survivorship bias refers to the tendency to focus on the individuals or entities that have succeeded, while overlooking those that have failed. This can lead to an overestimation of the likelihood of success, as the failures are not taken into account and an underestimation of the challenges and risks that are associated with achieving success. To avoid survivorship bias, it is important to be aware of it and to try to take into account the failures as well as the successes when making decisions or drawing conclusions. Additionally, it is important to make sure that the data is representative and to use multiple sources of data.