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| Criterion |  Engineering Failure Scenario Analysis |  Product Discovery Smoke Test |  Product Discovery Experiment Canvas |  Growth A/B Testing |
|---|---|---|---|---|
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 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 | Medium | Low | Low | High |
Timedifferent | 1-3 h | 1-5 Tage | 30-60 min | 1-4 Wochen |
Participantsdifferent | 3-8 | Nutzertraffic | 1-5 | 1-6 |
Formatdifferent | Workshop | Async | Workshop + async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Interest Metrics, Conversion Signal, Learning Note | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | ValidationExperimentsDemandGrowth | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |