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| Criterion |  Growth A/B Testing |  Operations Fault Tree Analysis |  Operations Family Tree 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 series of incidents with a similar pattern, the method arranges individual events as branches of a common origin. It makes visible which conditions keep recurring. | 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 | Family Tree Diagram, Pattern Notes, Systemic Measures | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | RiskRoot causeSafety | Root causePatternsIncidentSystemic | ValidationExperimentsDemandGrowth |