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| Criterion |  Delivery Monte Carlo Forecasting |  Product Strategy Lean Canvas |  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. | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | 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 | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 45-90 min | Wochen bis Monate je Lernzyklus | Ongoing |
Participantsdifferent | 1-8 | 1-6 | 2-8 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Lean Canvas, Core Assumptions, Experiment Backlog | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | StartupLeanAssumptionsBusiness model | LeanStartupValidationMVP | FlowVisual managementDelivery |