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| Criterion |  Engineering Kanban |  DevOps Blameless Postmortem |  Decision Making Decision Framing Workshop |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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 a decision is poorly framed, even good answers deliver little value. A Decision Framing Workshop sharpens the problem, goal, and boundaries before the actual weighing begins. | 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 | Medium | High |
Timedifferent | Ongoing | 30-90 min | 60-120 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-12 | 4-10 | 1-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Postmortem Doc, Action Items, Timeline | Decision Frame, Decision Question, Criteria List, Evidence Plan | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FlowVisual managementDelivery | Site Reliability EngineeringIncidentLearningReliability | Decision framingAlignmentCriteriaOptions | ForecastingFlowDelivery |