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| Criterion | ![]() Decision Making Delphi Method | ![]() Decision Making PERT Estimation | ![]() Product Discovery Experiment Canvas | ![]() Product Strategy DIBB |
|---|---|---|---|---|
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. | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | 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 | High | Medium | Low | Low |
Timedifferent | 1-4 Wochen | 15-45 min | 30-60 min | 1-2 h |
Participantsdifferent | 6-30 Experten | 1-8 | 1-5 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | PERT Estimate, Expected Value, Risk Notes | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingExpertsDecisionStrategy | EstimationUncertaintyRisk | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |



