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| Criterion |  Product Strategy DIBB |  Product Strategy RICE Scoring |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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 many initiatives compete for the same resources, it brings reach, impact, confidence, and effort into one shared ranking. It makes prioritization economically connectable. | 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. | 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. |
Complexitydifferent | Low | Medium | Low | Medium |
Timedifferent | 1-2 h | 60-90 min | 30-60 min | 60-90 min |
Participantsdifferent | 2-8 | 2-10 | 1-5 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | RICE Scores, Ranked List, Assumption Log | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | PrioritizationScoringRoadmapTradeoffs | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |