Silent Evidence

The systematic invisibility of failed outcomes that distorts our understanding of success. We study successful companies to learn 'what works' but never study the thousands of failed companies that did the same things—because they're silent (dead, dissolved, forgotten). Survivorship bias is the statistical version; silent evidence is the broader epistemic concept. Every business book about 'what great companies do' suffers from silent evidence: the same traits may be equally common among failed companies, but we can't see the failures to check.

When to use it

When studying success stories to extract lessons; when someone claims 'successful companies all do X'; when evaluating survival advice from survivors (who may have survived despite their approach, not because of it); when designing research or analysis that needs to avoid survivorship bias.

How it can help

Whenever analyzing success, deliberately ask: what about the failures? If you study 10 successful startups that all 'moved fast and broke things,' you need to ask: how many startups that moved fast and broke things failed? If the failure rate is 99%, then 'move fast' isn't a success factor—it's a survivor trait. The same logic applies to career advice, investment strategies, and management practices. Without the denominator (total attempts, not just successes), any pattern observed in survivors is meaningless.