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| Criterion |  Operations After-Action Review |  Delivery Monte Carlo Forecasting |  Operations Theory of Constraints |
|---|---|---|---|
Purposedifferent | 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. | 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. | 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. |
Complexitydifferent | Low | High | High |
Timedifferent | 20-45 min | 30-90 min Setup, danach laufend | 2-4 h Analyse, laufend |
Participantsdifferent | 3-12 | 1-8 | 3-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Lessons learned, Action items, Event summary | Forecast Percentiles, Throughput Dataset, Risk Communication | Constraint Map, Improvement Plan, Flow Metrics |
Tagsno overlap | LearningOperationsImprovement | ForecastingFlowDelivery | OperationsConstraintsFlowImprovement |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
