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| Criterion |  Knowledge Modeling Teach-back |  Engineering Kanban |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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 | Low | Medium | High | Medium |
Timedifferent | 5-20 min | Ongoing | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 2-8 | 2-12 | 1-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Understanding Check, Clarification Notes, Learning Gaps | Kanban board, WIP policies, Flow metrics | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list |
Tagsno overlap | LearningUnderstandingCommunication | FlowVisual managementDelivery | ForecastingFlowDelivery | LeanFlowWasteDelivery |