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| Criterion |  Delivery Monte Carlo Forecasting |  Innovation Lean Startup |  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. | 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. | 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 |
Timedifferent | 30-90 min Setup, danach laufend | Wochen bis Monate je Lernzyklus | Ongoing |
Participantsdifferent | 1-8 | 2-8 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | LeanStartupValidationMVP | FlowVisual managementDelivery |
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