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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Hypothesis Prioritization Canvas |  Product Strategy DIBB |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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 | High | Medium | Low | Low |
Timedifferent | Mehrere Wochen | 60-90 min | 1-2 h | 30-60 min |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 2-8 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Prioritization Canvas, Hypothesis Backlog | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric |
Tagsno overlap | OutcomesInnovationResearchQuantitative | ExperimentsPrioritizationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis |