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| Criterion | ![]() Engineering Failure Scenario Analysis | ![]() Agile WSJF | ![]() Growth A/B Testing | ![]() Product Discovery Smoke Test |
|---|---|---|---|---|
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 many tasks compete for the same capacity, it orders work by economic impact. It makes time lost, benefit, and effort comparable together. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | High | High | Low |
Timedifferent | 1-3 h | 45-90 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-8 | 3-10 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Ranked Backlog, Cost-of-Delay Assumptions | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | FailureResilienceRisk | LeanEconomicsSequencePrioritization | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |



