Decision context
Forecasting & future choices
Use these evidence-reviewed lenses when estimating uncertainty, imagining future feelings or preferences, or reviewing forecasts after the outcome is known.
Decision skill
Decision making under uncertainty
Make useful choices when outcomes are not known and one number, story or recent event can pull judgment too strongly.
Learning outcome: You can make a decision without pretending uncertainty has disappeared.
When it matters
Notice the situation before naming the bias.
- A deadline, probability or budget is being discussed as one precise number.
- An early estimate is shaping every later estimate.
- The latest success or failure is dominating the next decision.
- The team is continuing mainly because it has already invested a lot.
Practice the skill
Use a better reasoning move.
- Start with a range or reference class before negotiating a precise number.
- Create an independent estimate before looking at a strong anchor when possible.
- Separate already-spent resources from the future cost and value of the next step.
- Record assumptions that would make you reopen the decision.
Decision contexts
Apply the skill to real kinds of decisions.
Decision context
Project estimation & delivery
Use these evidence-reviewed lenses when setting a deadline, estimating effort, discussing delivery risk, or learning from a project that finished later than expected.
Decision context
Work & project decisions
Use these evidence-reviewed lenses when a team is choosing a direction, interpreting results, deciding whether to continue, or turning metrics into action.
Evidence-reviewed lenses
Patterns worth checking, not labels for people.
Several patterns can fit the same situation. Use these lenses to ask better questions, then inspect the evidence behind each concept.
Anchoring Effect
Anchoring is a well-supported effect in which an initial numerical value can pull a later estimate toward it. A 2026 meta-analysis covering 2,601 effect sizes found a large overall effect, but also substantial variation across studies. The effect should not be treated as a rule that every number changes every judgment: incidental anchors, anchors from a different dimension, clearly random values, incentives, and some debiasing conditions were associated with smaller or null effects.
well-supported for numerical judgments; strength depends on anchor type and context Read evidence review
Subadditivity Effect
People often give a larger total probability when an event is unpacked into separate possibilities than when the same event is judged as one packed category. The effect is not universal: how the possibilities are described and how typical they are can change or even reverse an unpacking effect.
established with boundary conditions Read evidence review
Availability Heuristic
Availability is a judgment heuristic: people can use how easily examples or scenarios come to mind when estimating frequency or probability. That shortcut is not automatically an error because memorable or accessible examples can correlate with real frequency. Bias appears when accessibility is driven by factors that are not diagnostic of the quantity being judged.
established heuristic; bias is context-dependent Read evidence review
Escalation of Commitment
Sunk-cost effects and escalation of commitment overlap but are not interchangeable. Sunk-cost research asks whether irrecoverable prior investments influence current choices. Escalation of commitment describes persistence or additional resource allocation to a failing course of action and can also be driven by personal responsibility, self-justification, project structure, and other factors.
established, but related constructs should be separated Read evidence review
Practice this skill
Apply the capability across real decisions.
One large customer describes a painful workflow problem. The roadmap discussion treats that story as proof that most users need the same feature.
Skill: Decision making under uncertaintyOpen scenario →A feature has consumed eight months of work. New research shows limited demand, but the team argues that stopping would waste the investment.
Skill: Decision making under uncertaintyOpen scenario →A supplier opens at €120 per unit. The buying team immediately discusses whether €105 would be a good deal, although no independent range was prepared.
Skill: Decision making under uncertaintyOpen scenario →A team publicly announced that it would never accept a contract longer than one year. New evidence shows a longer term could reduce total risk, but every analysis is now used to defend the public position.
Skill: Decision making under uncertaintyOpen scenario →A recruiter names a salary 20% above the current role. The career discussion now revolves around that number, while learning, stability, workload and future options remain vague.
Skill: Decision making under uncertaintyOpen scenario →A specialist dislikes the current path but says changing direction would waste twelve years of experience. The next year is evaluated mainly through the past investment.
Skill: Decision making under uncertaintyOpen scenario →A person feels exhausted today and considers leaving the field completely. The choice is framed as staying forever or resigning immediately, although smaller tests are possible.
Skill: Decision making under uncertaintyOpen scenario →