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| Criterion | ![]() Delivery Monte Carlo Forecasting | ![]() Decision Making Trade-off Analysis | ![]() 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. | With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects. | 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 | 45-120 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 | Trade-off Matrix, Criteria List, Decision Rationale, Accepted Downsides | Decision Tree, Option Map, Assumption List |
Tagsno overlap | ForecastingFlowDelivery | TradeoffsDecisionCriteriaOptions | DecisionTreeOptions |
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