Score decision quality separately from outcome quality

Judge the process you used — not whether it worked — when you review a past decision.

Why it works

"Resulting" — Annie Duke’s term for judging decisions by outcomes — is the most common way people learn the wrong lesson. In uncertain domains, a bad process can produce a good outcome by luck, and a good process can produce a bad outcome by bad luck. Scoring the process separately ("was the reasoning sound given what I knew?") breaks this conflation and protects the actual signal from noise.

How to do it

1. When reviewing a past decision, fill in two separate scores: (1) how good was the process at decision time, (2) how good was the outcome?
2. Write the gap between them explicitly — a high-process, low-outcome entry is a useful lesson about luck; a low-process, high-outcome entry is a warning about lucky habits.
3. Identify one thing in the process you’d change, regardless of the outcome.
4. Track the process score trend over time — that is what improves with practice.

Evidence

Outcome bias — rating identical decision processes differently based on outcomes — is well established in the judgment literature. Explicit separate scoring of process and outcome is the practitioner remedy advocated by Duke and others; it aligns with research showing that separating the two improves feedback quality. (observational)

The benefit of separate scoring is principled; empirical evidence that the practice produces better future decisions in real-world settings specifically is limited — most support comes from the judgment research on outcome bias.

Sources

• Baron & Hershey (1988), outcome bias in decision evaluation, Journal of Personality and Social Psychology
• Duke (2018), Thinking in Bets

Common mistake

Telling yourself you’re scoring the process but secretly anchoring on the outcome. If you find yourself giving high process scores to decisions that worked and low ones to decisions that didn’t, the outcome is still driving the rating.