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| Criterion |  Engineering Kanban |  Knowledge Modeling Teach-back |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |
|---|---|---|---|---|
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. | Teach-back checks whether an explanation actually got through to the other person. The method makes misunderstandings visible early and strengthens shared understanding in advisory and learning situations. | 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 delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible. |
Complexitydifferent | Medium | Low | High | Medium |
Timedifferent | Ongoing | 5-20 min | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 2-12 | 2-8 | 1-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Understanding Check, Clarification Notes, Learning Gaps | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list |
Tagsno overlap | FlowVisual managementDelivery | LearningUnderstandingCommunication | ForecastingFlowDelivery | LeanFlowWasteDelivery |