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| Criterion |  Delivery Monte Carlo Forecasting |  Facilitation Dot Estimation |  Product Discovery Experiment Canvas |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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 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. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | High | Low | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 5-20 min | 30-60 min | 45-60 min |
Participantsdifferent | 1-8 | 3-20 | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Effort Heatmap, Risk Signals, Discussion Targets | Completed Experiment Canvas, Success Metric | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | ForecastingFlowDelivery | EstimationEffortRisk | ExperimentsValidationDiscoveryHypothesis | AssumptionsRiskExperimentsValidation |