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| Criterion |  Delivery Monte Carlo Forecasting |  Systems Thinking Future Reality Tree |  Domain Modeling Context Map |  Systems Thinking Leverage Points |
|---|---|---|---|---|
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. | 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 several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries. | 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. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | 2-4 h | 1-3 h | Half day |
Participantsdifferent | 1-8 | 3-8 | 2-8 | 3-12 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Context Map, Integration Patterns, Boundary Notes | Leverage Map, Action Strategy |
Tagsno overlap | ForecastingFlowDelivery | Theory of ConstraintsSystems thinkingChange | Domain-Driven DesignBoundariesStrategy | Systems thinkingChangeStrategy |