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| Criterion |  Decision Making Delphi Method |  Product Discovery Product Kata |  Product Strategy DIBB |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | Product Kata helps clarify customer problems, solution ideas, and evidence through a repeatable improvement routine. It captures direction, current metric, target metric, experiment notes, and learning. | 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 | 1-4 Wochen | 1-2 Wochen je Loop | 1-2 h | 30-60 min |
Participantsdifferent | 6-30 Experten | 3-10 | 2-8 | 1-5 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Direction, Current metric, Target metric, Experiment note, Learning report | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ForecastingExpertsDecisionStrategy | OutcomesDiscoveryLearningIterationCoaching | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis |