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| Criterion |  Engineering Kanban |  Product Discovery Dual-Track Agile |  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. | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | 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 | Medium | High | Medium |
Timedifferent | Ongoing | Laufend, Wochen bis Monate | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 2-12 | 4-10 | 1-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list |
Tags1 shared | FlowVisual managementDelivery | AgileDiscoveryDelivery | ForecastingFlowDelivery | LeanFlowWasteDelivery |