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| Criterion |  Engineering Kanban |  Knowledge Modeling Teach-back |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |
|---|---|---|---|---|
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 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 | Medium | Low | High | Medium |
Timedifferent | Ongoing | 5-20 min | 30-90 min Setup, danach laufend | laufend |
Participantsdifferent | 2-12 | 2-8 | 1-8 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Understanding Check, Clarification Notes, Learning Gaps | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | FlowVisual managementDelivery | LearningUnderstandingCommunication | ForecastingFlowDelivery | EstimationForecastingFlow |