Who is missing from the evidence?
Visible examples may be only the cases that survived a selection process. Interviewing successful creators can reveal their experiences, but it cannot show whether their habits caused success without considering people who followed similar habits and did not succeed. Missing cases can change the story.
Go deeper
Inspect how examples entered the sample
Suppose ten successful shop owners say they opened early every morning. It is tempting to treat early opening as a recipe for success.
But what about shops that opened early and later closed? If they are absent from the sample, the evidence describes only the survivors.
Survivorship bias occurs when conclusions rely on cases that remain visible while relevant missing cases are ignored.
The correction is not to dismiss successful people's experiences. It is to ask what comparison is needed. Examining both surviving and closed shops may reveal whether early opening distinguishes the groups at all. The same question applies to published projects, completed courses and products still available on a shelf.