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| Criterion |  Delivery Monte Carlo Forecasting |  DevOps Blameless Postmortem |  Decision Making Force Field Analysis |  Product Strategy DIBB |
|---|---|---|---|---|
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 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. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | High | Medium | Low | Low |
Timedifferent | 30-90 min Setup, danach laufend | 30-90 min | 45-90 min | 1-2 h |
Participantsdifferent | 1-8 | 3-12 | 3-12 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Postmortem Doc, Action Items, Timeline | Force Field Map, Change Levers, Risk Notes | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingFlowDelivery | Site Reliability EngineeringIncidentLearningReliability | ChangeDecisionStrategy | StrategyDecisionAssumptionsHypothesis |