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| Criterion |  Engineering Failure Scenario Analysis |  Growth A/B Testing |  UX Research Surveys |  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 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 a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | 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 | High | Medium | Low |
Timedifferent | 1-3 h | 1-4 Wochen | 3-14 Tage | 30-60 min |
Participantsdifferent | 3-8 | 1-6 | 50+ | 1-5 |
Formatdifferent | Workshop | Async | Async | Workshop + async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Experiment results, Decision log, Learning summary | Survey Results, Charts, Segment Insights | Completed Experiment Canvas, Success Metric |
Tagsno overlap | FailureResilienceRisk | ExperimentsGrowthAnalyticsValidation | QuantitativeResearchValidation | ExperimentsValidationDiscoveryHypothesis |