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| Criterion |  Decision Making Constraint Analysis |  Product Discovery Hypothesis Prioritization Canvas |  Product Strategy DIBB |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Low | Medium | Low | Low |
Timedifferent | 30-90 min | 60-90 min | 1-2 h | 30-60 min |
Participantsdifferent | 2-8 | 3-8 | 2-8 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Prioritization Canvas, Hypothesis Backlog | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ConstraintsDecisionPlanningOptions | ExperimentsPrioritizationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis |