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Selected:Monte Carlo ForecastingRoot Cause AnalysisFailure Mode and Effects AnalysisFishbone Diagram
| Criterion |  Delivery Monte Carlo Forecasting |  Operations Root Cause Analysis |  Operations Failure Mode and Effects Analysis |  Operations Fishbone Diagram |
|---|---|---|---|---|
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 process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability. | When a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-4 h | 2-6 h | 30-60 min |
Participantsdifferent | 1-8 | 3-8 | 3-10 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | FMEA Table, Risk Priority, Mitigation Actions | Fishbone Diagram, Cause Categories, Investigation Backlog |
Tagsno overlap | ForecastingFlowDelivery | Root causeProblem solvingQualityIncident | RiskQualityOperationsRoot cause | Root causeQualityOperations |