Decision Autopsy

Judge a past decision by its PROCESS, not its outcome — because good decisions lose and bad decisions win, and teams that can't tell the difference learn the wrong lessons. Use when reviewing a big call after the fact (a bet that failed, a pass that haunts, a hire, a pivot) and the room is about to conclude 'it failed so it was wrong.' Produces a process-forensics report: what was knowable then, the quality grade of the decision as-made, the luck accounting, and the ONE process change worth keeping.

Outcome bias is the strongest bias in organisational memory: the bet that failed becomes "obviously reckless," the coin-flip that landed becomes "visionary." The autopsy separates the two questions that always get merged: was it a good decision? and did it get a good outcome? — because only the first is under anyone's control next time.

Required Inputs

• The decision — what was decided, when, by whom, and what the live alternatives were.
• What was knowable at the time — the information, constraints, and time pressure as of the decision date. Be strict: things learned afterward go in a separate pile, and the autopsy will police the boundary.
• The outcome — what actually happened, so the luck accounting has something to account.

The Forensic Frames

• The information test: given only what was knowable then, what would a calibrated outsider have chosen? (The autopsy answers this before re-examining the outcome, to keep hindsight out of the grade.)
• The process test: were alternatives really generated? Was disconfirming evidence sought or only tolerated? Was the reversibility of the choice priced in? Was a kill-criterion set?
• The luck accounting: decompose the outcome into decision quality vs. variance — what portion of the result would replay differently if the world rolled again?
• The lesson filter: the only lessons worth keeping are process lessons ("we never priced reversibility") — outcome lessons ("don't bet on X") overfit to one roll of the dice.

Output Format

1. The two verdicts, separated — Decision: 🟢 sound / 🟡 flawed / 🔴 negligent as made. Outcome: good / bad / mixed. State them side by side; the whole point is that they can disagree.
2. The knowability ledger — table: fact | knowable then? | actually known? | changed the call? Hindsight contamination gets flagged explicitly ("this entered the story after the fact").
3. The luck accounting — one honest paragraph: what fraction of this outcome was variance, with the reasoning shown.
4. The one process change — a single, named, repeatable change to how decisions like this get made ("every >$100k bet gets a written kill-criterion before commitment"). One. Teams adopt one; they file lists.
5. The replay line — "facing the same information again, the right call would be ___" — the sentence that inoculates the team against both regret and false confidence.

Quality Checks

• The decision grade was assigned from the knowability ledger BEFORE outcome discussion, and the report's structure shows it
• At least one hindsight contamination is caught and named — reviews without any are usually not looking
• The luck paragraph commits to a rough proportion, with reasoning — "some luck was involved" is evasion
• The process change is executable next quarter and testable ("did we do it?"), not a value statement
• If the decision was 🟢 and the outcome bad, the report says the uncomfortable sentence plainly: "do it again"

Anti-Patterns

• Do not let the outcome leak into the grade — a bad result may not appear as evidence of a bad decision anywhere in the report
• Do not run an autopsy as a trial — no verdicts on people; the unit of analysis is the process that any competent person was embedded in
• Do not conclude "we were unlucky" without the ledger to earn it — luck is the residual after process is examined, never the headline
• Do not extract more than one lesson — the second-best lesson dilutes the best one
• Do not autopsy decisions younger than their outcome — if the result isn't actually in yet, this is a premortem's job