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| Criterion |  Growth A/B Testing |  Operations MORT Analysis |  Product Discovery Riskiest Assumption Test |  Product Discovery Fake Door 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 safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | 1-4 Wochen | Mehrere Tage bis Wochen | 1-2 Wochen pro Iteration | 1-5 Tage |
Participantsdifferent | 1-6 | 2-6 | 2-6 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Prioritized Assumption List, Test Plan, Results Report | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeSafetySystemicIncident | ExperimentsValidationDiscoveryAssumptions | ValidationExperimentsDemandDiscovery |