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| Criterion |  Product Strategy DIBB |  Delivery Monte Carlo Forecasting |  Product Discovery Assumption Mapping |  Decision Making Delphi Method |
|---|---|---|---|---|
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 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. |
Complexitydifferent | Low | High | Medium | High |
Timedifferent | 1-2 h | 30-90 min Setup, danach laufend | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-8 | 2-8 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Forecast Percentiles, Throughput Dataset, Risk Communication | Assumption map, Test backlog, Risk ranking | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | ForecastingFlowDelivery | AssumptionsRiskExperimentsValidation | ForecastingExpertsDecisionStrategy |