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| Criterion |  Delivery Monte Carlo Forecasting |  Operations Root Cause Analysis |  Operations MORT Analysis |  Operations 5 Whys |
|---|---|---|---|---|
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 a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. | 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. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-4 h | Mehrere Tage bis Wochen | 15-30 min |
Participantsdifferent | 1-8 | 3-8 | 2-6 | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Root cause notes, Countermeasures |
Tagsno overlap | ForecastingFlowDelivery | Root causeProblem solvingQualityIncident | Root causeSafetySystemicIncident | Root causeIncidentLeanProblem solving |