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| Criterion |  Operations Fishbone Diagram |  Engineering Kanban |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | When a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. | 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. | 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 | Low | Medium | Medium | High |
Timedifferent | 30-60 min | Ongoing | laufend | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-8 | 2-12 | 2-12 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Fishbone Diagram, Cause Categories, Investigation Backlog | Kanban board, WIP policies, Flow metrics | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | Root causeQualityOperations | FlowVisual managementDelivery | EstimationForecastingFlow | ForecastingFlowDelivery |