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| Criterion |  Delivery Monte Carlo Forecasting |  Growth Growth Experiment |  Agile NoEstimates |  Product Discovery Learning Card |
|---|---|---|---|---|
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-2 Wochen | laufend | 25-40 min |
Participantsdifferent | 1-8 | 1-6 | 2-12 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Experiment card, Result summary, Next bet | Throughput Data, Flow Forecast, Slicing Rules | Learning Card with evidence and next action |
Tagsno overlap | ForecastingFlowDelivery | MarketingGrowthExperimentsLearning | EstimationForecastingFlow | ExperimentsValidationDiscoveryLearning |