The Survivorship Bias is a type of cognitive bias that occurs when we focus on people or things that have “survived” some kind of selection process, while ignoring those who did not survive. This can lead to misleading conclusions and inaccurate assessments of performance.

Here are a few examples:

Example 1: Stock Market
Imagine an investor looking at the performance of companies in the stock market over a period of time. They might look at the top-performing stocks and conclude that investing in those specific industries or sectors is a good strategy. However, they might be ignoring all the companies that went bankrupt or failed to perform well during that same period.

Example 2: Aviation
In the early days of aviation, planes were made with a lot of metal plating on them. Military aircraft were often hit by anti-aircraft fire and returned safely because of their metal reinforcement. A study might show
that planes with more metal plating tended to survive battles better. However, this would lead to an incorrect conclusion: the metal plating didn’t actually make the plane safer – it was just that planes without enough
metal plating were more likely to be destroyed or shot down.

Example 3: Business
A business consultant might look at successful companies and identify common traits or strategies among them. They might conclude that these are key factors in success, but they would be ignoring all the companies that
had similar characteristics yet failed.

In each of these examples, the Survivorship Bias leads to an incorrect conclusion because it focuses only on those who have “survived” (in this case, successful stocks, planes with metal plating, and thriving
businesses). The bias occurs when we ignore the people or things that did not survive – which might be equally important for understanding what happened.

Why does the Survivorship Bias occur?

1. Availability Heuristic: We tend to focus on information that is readily available and easily accessible.
2. Confirmation Bias: We look for data that confirms our pre-existing assumptions and ignore contradictory evidence.
3. Anchoring Effect: We rely too heavily on initial impressions or observations, which can influence our subsequent judgments.

How can we avoid the Survivorship Bias?

1. Consider all possible outcomes: Make sure to account for both successes and failures in your analysis.
2. Gather comprehensive data: Include information about those who did not survive (e.g., failed businesses, unsuccessful investments).
3. Use multiple perspectives: Seek diverse viewpoints to avoid being anchored by a single perspective.

By recognizing the Survivorship Bias, we can become more aware of our own biases and strive for more accurate assessments in various domains.

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Filed under: Uncategorized - @ September 29, 2024 9:21 pm