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| Criterion |  Growth A/B Testing |  Operations MORT Analysis |  Product Discovery Assumption Mapping |  Operations Fault Tree Analysis |
|---|---|---|---|---|
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 safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | 1-4 Wochen | Mehrere Tage bis Wochen | 45-60 min | 2-6 h |
Participantsdifferent | 1-6 | 2-6 | 2-8 | 3-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Assumption map, Test backlog, Risk ranking | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeSafetySystemicIncident | AssumptionsRiskExperimentsValidation | RiskRoot causeSafety |