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| Criterion |  Delivery Monte Carlo Forecasting |  Operations After-Action Review |  Operations Theory of Constraints |  Agile NoEstimates |
|---|---|---|---|---|
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. | After missions or project phases with unclear outcomes, the method makes visible what actually happened and what can be learned from it. It separates course, effect, and causes so experience turns into solid improvement. | For a system that does not get faster despite effort, the method directs attention to the bottleneck. It concentrates improvement on the point that actually limits throughput. | 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. |
Complexitydifferent | High | Low | High | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 20-45 min | 2-4 h Analyse, laufend | laufend |
Participantsdifferent | 1-8 | 3-12 | 3-12 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Lessons learned, Action items, Event summary | Constraint Map, Improvement Plan, Flow Metrics | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | ForecastingFlowDelivery | LearningOperationsImprovement | OperationsConstraintsFlowImprovement | EstimationForecastingFlow |