Sensemaking Bias

The cognitive tendency to construct coherent narratives and causal explanations from random or loosely connected events—seeing meaningful patterns where none exist. The brain is a SENSEMAKING MACHINE that abhors randomness and actively constructs explanations, even for noise. After-the-fact narratives make random outcomes feel inevitable ('of course the startup succeeded—they had X, Y, Z advantages'). Pattern-matching in random data produces superstitions, conspiracy theories, and overconfident causal claims. As a mental model: sensemaking bias reveals that our confidence in explanations is driven by the COHERENCE of the story rather than the VALIDITY of the evidence.

When to use it

When narrative coherence is being mistaken for causal validity; when post-hoc explanations need scrutiny for sensemaking bias; when pattern-matching in random data is producing false conclusions; when accepting randomness would be more accurate than constructing causal narratives.

How it can help

When an explanation feels compelling: check whether the compellingness comes from EVIDENCE or from NARRATIVE COHERENCE. The diagnostic: 'Would I find this explanation compelling if I only had the evidence and not the story?' For business: post-hoc explanations of success or failure almost always feel more coherent than the messy reality warranted. The practice: (1) Distrust explanations that are TOO coherent—reality is messier. (2) Check whether the same 'causal factors' also appear in failure cases (if so, they're not really causal). (3) Seek DISCONFIRMING evidence for compelling narratives. (4) Accept that some outcomes are primarily random, not primarily caused.