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| Criterion |  Delivery Monte Carlo Forecasting |  Engineering Kanban |  Knowledge Modeling Knowledge Mapping |  Agile NoEstimates |
|---|---|---|---|---|
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. | 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. | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | Ongoing | 1-3 h | laufend |
Participantsdifferent | 1-8 | 2-12 | 3-12 | 2-12 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | ForecastingFlowDelivery | FlowVisual managementDelivery | KnowledgeMappingRisk | EstimationForecastingFlow |