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| Criterion |  Delivery Monte Carlo Forecasting |  Product Discovery Dual-Track Agile |  Delivery Value Stream Mapping |  Engineering Kanban |
|---|---|---|---|---|
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 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. | 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. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | Laufend, Wochen bis Monate | 1-3 h | Ongoing |
Participantsdifferent | 1-8 | 4-10 | 4-10 | 2-12 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Current-state map, Future-state map, Bottleneck list | Kanban board, WIP policies, Flow metrics |
Tags1 shared | ForecastingFlowDelivery | AgileDiscoveryDelivery | LeanFlowWasteDelivery | FlowVisual managementDelivery |