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| Criterion |  Product Discovery Dual-Track Agile |  Product Discovery Hypothesis Prioritization Canvas |  Product Strategy DIBB |  Product Discovery Riskiest Assumption Test |
|---|---|---|---|---|
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 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | Laufend, Wochen bis Monate | 60-90 min | 1-2 h | 1-2 Wochen pro Iteration |
Participantsdifferent | 4-10 | 3-8 | 2-8 | 2-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Prioritization Canvas, Hypothesis Backlog | DIBB document, Belief list, Bet list, Learning report | Prioritized Assumption List, Test Plan, Results Report |
Tagsno overlap | AgileDiscoveryDelivery | ExperimentsPrioritizationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryAssumptions |