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| Criterion |  DevOps Blameless Postmortem |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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. | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. |
Complexitydifferent | Medium | Medium | High |
Timedifferent | 30-90 min | laufend | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-12 | 2-12 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Postmortem Doc, Action Items, Timeline | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | Site Reliability EngineeringIncidentLearningReliability | EstimationForecastingFlow | ForecastingFlowDelivery |
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