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| Criterion |  Delivery Monte Carlo Forecasting |  Systems Thinking Leverage Points |  Agile NoEstimates |  Systems Thinking Future Reality 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. | 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. | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | Half day | laufend | 2-4 h |
Participantsdifferent | 1-8 | 3-12 | 2-12 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Leverage Map, Action Strategy | Throughput Data, Flow Forecast, Slicing Rules | Future Reality Tree, Negative Branches, Assumption List, Improved Injections |
Tagsno overlap | ForecastingFlowDelivery | Systems thinkingChangeStrategy | EstimationForecastingFlow | Theory of ConstraintsSystems thinkingChange |