Outcome bias

Judging the quality of a decision by how it turned out, when the result was produced by the reasoning and by chance in proportions you cannot observe.

Example

A decision carrying a 30% chance of total loss will lose everything roughly three times in ten. Filing each of those as a mistake revises a process that was working.

Important

The idea is nearly always invoked to defend a loss and nearly never to interrogate a gain, which leaves the dangerous half untouched - a poorly reasoned decision that paid produces no discomfort, no examination, and a method repeated at larger size.

Related terms

• Process versus outcome — The distinction between how a decision was made and what it happened to produce. The first belongs to you; the second belongs partly to the world.
• Variance — How widely actual outcomes spread around their average. High variance means individual results routinely land far from the expected value, in both directions.
• Survivorship bias — Drawing conclusions from the examples that lasted long enough to be visible, while the ones that failed have quietly left the sample.

Lessons that explain it

• Write the decision down before you know how it turns out — A decision record captures what you decided, why, the conditions, the main risks and what would change your mind. It turns each decision into something you can learn from later. (9 min)
• The memo is worth more at the two-year review than on the day you wrote it — A memo's real value is not in getting a deal approved. It is in being specific enough, on the day it was written, that reading it again later tells you something you could not otherwise have known. (10 min)
• A good decision can lose, and a bad one can win — Outcomes are made of judgement and luck in unknown proportions. Judging the decision by the result means learning from the luck, which teaches the wrong thing in both directions. (13 min)

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