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| Criterion | ![]() Decision Making PERT Estimation | ![]() Product Discovery Opportunity Solution Tree | ![]() Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | 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 discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | 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 | Medium | Medium | Low |
Timedifferent | 15-45 min | 1-2 h Setup, laufend | 1-2 h |
Participantsdifferent | 1-8 | 2-6 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | PERT Estimate, Expected Value, Risk Notes | Opportunity Solution Tree, Experiment Backlog, Learning Log | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | EstimationUncertaintyRisk | DiscoveryOutcomesExperimentsOpportunity | StrategyDecisionAssumptionsHypothesis |
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