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| Criterion |  Product Discovery Opportunity Scoring |  Decision Making Delphi Method |  Product Strategy DIBB |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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 | High | Low | Medium |
Timedifferent | 60-120 min | 1-4 Wochen | 1-2 h | 60-90 min |
Participantsdifferent | 3-6 | 6-30 Experten | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop |
Outputdifferent | Opportunity Score Table, Top Outcomes | Expert Forecast, Consensus Range, Assumption Notes | DIBB document, Belief list, Bet list, Learning report | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | ForecastingExpertsDecisionStrategy | StrategyDecisionAssumptionsHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |