TL;DR
A green target does not prove a good full outcome or a sound approval. Review the outcome, the route, and the first decision separately.
What the paper develops
A program can hit its benefit target while bypassing controls, exhausting a key team, shifting risk, or harming customers. One green target does not describe everything the program caused.
Reviews can also make the opposite mistake. A program can miss a target after an outside event no one could reasonably predict. A bad result does not prove the approval was poor.
Ask whether the original decision was sound based only on approval-time evidence, what was achieved when the full consequence is counted, and how it was achieved compared with the approved route.
Use two grades and one attribution record. Grade the approval from its original evidence before seeing the outcome score. Then score the full outcome and compare the approved route with the route the team took.
Keep a short record at approval: the problem, alternatives, assumptions, risks, ranges, decision owner, and evidence that would reopen the choice. Keep later facts in a separate column at review.
At the next stage gate, require the record. At the next review, grade the original decision before opening the outcome score. Then score the full outcome and compare the route taken.
What to do next
At the next review, first grade the decision from its approval record. Then score the full outcome and compare the route taken with the approved route.
Inside the white paper
- Why one green target does not describe the whole outcome
- The four combinations of decision quality and outcome
- Three tests for uncertainty, delivery changes, and repeated estimating error
Sources and notes
- Jonathan Baron and John C. Hershey, Outcome bias in decision evaluation, Journal of Personality and Social Psychology 54(4), April 1988, 569–579 — Baron and Hershey showed that outcome changes how people rate the same decision.
- Sriraj Aiyer, Hoi Ching Kam, Ka Yuk Ng, Nathaniel A. Young, Jiaxin Shi, and Gilad Feldman, Outcomes Affect Evaluations of Decision Quality, International Review of Social Psychology 36(1), article 12, July 28, 2023 — Aiyer and colleagues replicated outcome bias with 692 participants.
- Jan C. van Ours, Outcome bias in managerial decisions, Journal of Economic Psychology 112, January 2026, article 102872 — van Ours studied outcome bias in manager replacement decisions.
- Michael J. Mauboussin and Dan Callahan, Outcome Bias and the Interpreter: How Our Minds Confuse Skill and Luck, Credit Suisse Global Financial Strategies, October 15, 2013 — Mauboussin and Callahan explain how luck can obscure process quality.
- Bent Flyvbjerg and Alexander Budzier, Why Your IT Project Might Be Riskier Than You Think, Harvard Business Review 89(9), September 2011; open-access version arXiv:1304.0265 — Flyvbjerg and Budzier show why IT-project averages hide tail risk.
- Society of Decision Professionals, "Decision Quality." — The Society of Decision Professionals lists six parts of a decision.
- Bent Flyvbjerg, Quality Control and Due Diligence in Project Management: Getting Decisions Right by Taking the Outside View, arXiv:1302.2544, 2013 — Flyvbjerg explains the outside view and reference-class discipline.