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| Criterion |  Facilitation Dot Estimation |  Delivery Monte Carlo Forecasting |  Growth Funnel Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | 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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Low | High | Medium | High |
Timedifferent | 5-20 min | 30-90 min Setup, danach laufend | 1-3 h | 1-4 Wochen |
Participantsdifferent | 3-20 | 1-8 | 1-5 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Effort Heatmap, Risk Signals, Discussion Targets | Forecast Percentiles, Throughput Dataset, Risk Communication | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary |
Tagsno overlap | EstimationEffortRisk | ForecastingFlowDelivery | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation |