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| Criterion |  Delivery Monte Carlo Forecasting |  Engineering Kanban |  Innovation Lean Startup |
|---|---|---|---|
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 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. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | Ongoing | Wochen bis Monate je Lernzyklus |
Participantsdifferent | 1-8 | 2-12 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision |
Tagsno overlap | ForecastingFlowDelivery | FlowVisual managementDelivery | LeanStartupValidationMVP |
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