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| Criterion |  Delivery Monte Carlo Forecasting |  Operations Learning Review |  DevOps Game Day |  DevOps Blameless Postmortem |
|---|---|---|---|---|
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. | After a project phase with mixed results, the method makes learning from the individual case reusable. It connects events, decisions, and systemic conditions into robust insights. | In preparing for rare incidents, the method tests response capability under controlled conditions. It shows where assumptions about stability, roles, and recovery are too optimistic. | After an incident with damage or a near miss, the method creates a sober field for learning without assigning blame. It directs attention to the course of events, conditions, and effective countermeasures. |
Complexitydifferent | High | Medium | High | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | Halber Tag | 30-90 min |
Participantsdifferent | 1-8 | 3-10 | 5-20 | 3-12 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Learning Review Notes, System Factors, Improvement Actions | Simulation Notes, Gaps List, Updated Runbooks | Postmortem Doc, Action Items, Timeline |
Tagsno overlap | ForecastingFlowDelivery | LearningRetrospectiveIncidentOperations | ResilienceOperationsIncident | Site Reliability EngineeringIncidentLearningReliability |