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| Criterion |  Product Discovery Pretotyping |  Agile NoEstimates |  Innovation Lean Startup |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | 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. | 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. | 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. |
Complexitydifferent | Low | Medium | Medium | High |
Timedifferent | Stunden bis wenige Tage | laufend | Wochen bis Monate je Lernzyklus | 30-90 min Setup, danach laufend |
Participantsdifferent | 1-4 | 2-12 | 2-8 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Throughput Data, Flow Forecast, Slicing Rules | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | ValidationDemandMVP | EstimationForecastingFlow | LeanStartupValidationMVP | ForecastingFlowDelivery |