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| Criterion |  Product Discovery Dual-Track Agile |  Product Discovery Opportunity Scoring |  Product Strategy DIBB |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | 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 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 | Medium | Medium | Low | Medium |
Timedifferent | Laufend, Wochen bis Monate | 60-120 min | 1-2 h | 60-90 min |
Participantsdifferent | 4-10 | 3-6 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Opportunity Score Table, Top Outcomes | DIBB document, Belief list, Bet list, Learning report | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | AgileDiscoveryDelivery | PrioritizationDiscoveryOutcomesNeeds | StrategyDecisionAssumptionsHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |