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| Criterion |  Growth A/B Testing |  Operations MORT Analysis |  Innovation Design Sprint |  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 safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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 | High | Low |
Timedifferent | 1-4 Wochen | Mehrere Tage bis Wochen | 4-5 Tage | 1-5 Tage |
Participantsdifferent | 1-6 | 2-6 | 5-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Prototype, Test Findings, Decision Rationale | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeSafetySystemicIncident | Design sprintPrototypeValidationInnovation | ValidationExperimentsDemandGrowth |