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| Criterion |  Growth A/B Testing |  Operations Fault Tree Analysis |  Operations Barrier Analysis |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | For a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | For a risk that can only be managed through multiple layers of protection, the method examines the effectiveness of each barrier. It shows where safeguards are missing, too weak, or fail under real conditions. | 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 | High | High | Medium | Low |
Timedifferent | 1-4 Wochen | 2-6 h | 2-4 h | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 2-6 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Barrier Inventory, Failure Analysis per Barrier, Action Backlog | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | RiskRoot causeSafety | Root causeSafetyIncident | ValidationExperimentsDemandGrowth |