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| Criterion |  Delivery Monte Carlo Forecasting |  Operations Process Mapping |  Operations After-Action Review |  Operations Learning Review |
|---|---|---|---|---|
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. | With a confusing workflow that has many handoffs, the method makes the actual process visible. It shows where work is passed on, delayed, or duplicated, so improvement targets the right spots. | 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. | After a project phase with mixed results, the method makes learning from the individual case reusable. It connects events, decisions, and systemic conditions into robust insights. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 20-45 min | 1-3 h |
Participantsdifferent | 1-8 | 3-10 | 3-12 | 3-10 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Process Map, Handoff List, Improvement Backlog | Lessons learned, Action items, Event summary | Learning Review Notes, System Factors, Improvement Actions |
Tagsno overlap | ForecastingFlowDelivery | ProcessOperationsImprovement | LearningOperationsImprovement | LearningRetrospectiveIncidentOperations |