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| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making Decision Tree |  Decision Making OODA Loop |  Decision Making Delphi Method |
|---|---|---|---|---|
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. | 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. | In dynamic situations, decisions become outdated faster than they can be prepared. The OODA Loop holds observing, orienting, deciding, and acting together as a recurring rhythm so reaction does not slide into inertia. | 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 | High | Medium | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | 30-90 min | 15-60 min je Zyklus | 1-4 Wochen |
Participantsdifferent | 1-8 | 1-6 | 1-8 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Decision Tree, Option Map, Assumption List | Situation Assessment, Decision Loop, Action Updates | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | ForecastingFlowDelivery | DecisionTreeOptions | DecisionChangeLearningStrategy | ForecastingExpertsDecisionStrategy |