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| Criterion |  Product Strategy DIBB |  Delivery Monte Carlo Forecasting |  Product Discovery Assumption Mapping |  Product Discovery Riskiest Assumption Test |
|---|---|---|---|---|
Purposedifferent | 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. | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Low | High | Medium | Medium |
Timedifferent | 1-2 h | 30-90 min Setup, danach laufend | 45-60 min | 1-2 Wochen pro Iteration |
Participantsdifferent | 2-8 | 1-8 | 2-8 | 2-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Forecast Percentiles, Throughput Dataset, Risk Communication | Assumption map, Test backlog, Risk ranking | Prioritized Assumption List, Test Plan, Results Report |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | ForecastingFlowDelivery | AssumptionsRiskExperimentsValidation | ExperimentsValidationDiscoveryAssumptions |