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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Decision Making Delphi Method |  Product Discovery Experiment Canvas |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | 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. | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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. | 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. |
Complexitydifferent | Medium | High | Low | Low |
Timedifferent | 60-90 min | 1-4 Wochen | 30-60 min | 1-2 h |
Participantsdifferent | 3-8 | 6-30 Experten | 1-5 | 2-8 |
Formatdifferent | Workshop | Async | Workshop + async | Workshop + async |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Expert Forecast, Consensus Range, Assumption Notes | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | ForecastingExpertsDecisionStrategy | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |