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| Criterion |  Delivery Monte Carlo Forecasting |  Innovation Lean Startup |  Agile NoEstimates |  Product Strategy Lean Canvas |
|---|---|---|---|---|
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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | Wochen bis Monate je Lernzyklus | laufend | 45-90 min |
Participantsdifferent | 1-8 | 2-8 | 2-12 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Throughput Data, Flow Forecast, Slicing Rules | Lean Canvas, Core Assumptions, Experiment Backlog |
Tagsno overlap | ForecastingFlowDelivery | LeanStartupValidationMVP | EstimationForecastingFlow | StartupLeanAssumptionsBusiness model |