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| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making Decision Matrix |  Decision Making Decision Tree |
|---|---|---|---|
Purposedifferent | 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 several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. | 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. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 45-90 min | 30-90 min |
Participantsdifferent | 1-8 | 2-8 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Decision Matrix, Scoring Rationale, Selected Option | Decision Tree, Option Map, Assumption List |
Tagsno overlap | ForecastingFlowDelivery | DecisionCriteriaScoringTradeoffs | DecisionTreeOptions |
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