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| Criterion |  Agile NoEstimates |  Systems Thinking Future Reality Tree |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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. | 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. |
Complexitydifferent | Medium | High | High |
Timedifferent | laufend | 2-4 h | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-8 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | Theory of ConstraintsSystems thinkingChange | ForecastingFlowDelivery |
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