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| Criterion |  Delivery Monte Carlo Forecasting |  Operations MORT Analysis |  Delivery Value Stream Mapping |  Operations Causal Factor Analysis |
|---|---|---|---|---|
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. | For a safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | When delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | Mehrere Tage bis Wochen | 1-3 h | 2-6 h |
Participantsdifferent | 1-8 | 2-6 | 4-10 | 3-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Current-state map, Future-state map, Bottleneck list | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | ForecastingFlowDelivery | Root causeSafetySystemicIncident | LeanFlowWasteDelivery | CausalityIncidentRoot causeTimeline |