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| Criterion |  Engineering Failure Scenario Analysis |  Facilitation Dot Estimation |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | 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 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. | 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 1-3 h | 5-20 min | 1-4 Wochen | 30-60 min |
Participantsdifferent | 3-8 | 3-20 | 1-6 | 1-5 |
Formatdifferent | Workshop | Workshop | Async | Workshop + async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Effort Heatmap, Risk Signals, Discussion Targets | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | FailureResilienceRisk | EstimationEffortRisk | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |