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| Criterion |  Delivery Monte Carlo Forecasting |  Operations Bottleneck Analysis |  DevOps Incident Timeline 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 flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. | For an incident with an unclear sequence, the method makes the timeline precisely visible. It separates perception, reaction, and delay so cause and effect become more clearly readable. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 60-180 min |
Participantsdifferent | 1-8 | 3-8 | 3-10 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Incident Timeline, Evidence Log, Delay Analysis, Improvement Actions |
Tagsno overlap | ForecastingFlowDelivery | FlowMeasurementConstraints | IncidentTimelineSite Reliability Engineering |
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