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| Criterion |  Delivery Monte Carlo Forecasting |  Systems Thinking Leverage Points |  Systems Thinking Future Reality Tree |  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. | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation. | 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. |
Complexitysame | High | High | High | High |
Timedifferent | 30-90 min Setup, danach laufend | Half day | 2-4 h | 1-4 Wochen |
Participantsdifferent | 1-8 | 3-12 | 3-8 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop | Workshop | Async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Leverage Map, Action Strategy | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | ForecastingFlowDelivery | Systems thinkingChangeStrategy | Theory of ConstraintsSystems thinkingChange | ForecastingExpertsDecisionStrategy |