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| Criterion |  Delivery Monte Carlo Forecasting |  Engineering Kanban |  Operations Fault Tree Analysis |  Operations MORT 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. | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | For a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | 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. |
Complexitydifferent | High | Medium | High | High |
Timedifferent | 30-90 min Setup, danach laufend | Ongoing | 2-6 h | Mehrere Tage bis Wochen |
Participantsdifferent | 1-8 | 2-12 | 3-8 | 2-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations |
Tagsno overlap | ForecastingFlowDelivery | FlowVisual managementDelivery | RiskRoot causeSafety | Root causeSafetySystemicIncident |