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| Criterion |  Decision Making Delphi Method |  Delivery Monte Carlo Forecasting |  Decision Making Decision Tree |  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. | 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. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 | High | Medium | Low |
Timedifferent | 1-4 Wochen | 30-90 min Setup, danach laufend | 30-90 min | 1-2 h |
Participantsdifferent | 6-30 Experten | 1-8 | 1-6 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Decision Tree, Option Map, Assumption List | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ForecastingFlowDelivery | DecisionTreeOptions | StrategyDecisionAssumptionsHypothesis |