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| Criterion |  Growth A/B Testing |  Operations MORT Analysis |  Growth Funnel Analysis |  Operations 5 Whys |
|---|---|---|---|---|
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | 1-4 Wochen | Mehrere Tage bis Wochen | 1-3 h | 15-30 min |
Participantsdifferent | 1-6 | 2-6 | 1-5 | 2-6 |
Formatdifferent | Async | Workshop + async | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Funnel report, Drop-off analysis, Optimization hypotheses | Root cause notes, Countermeasures |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeSafetySystemicIncident | AnalyticsConversionGrowth | Root causeIncidentLeanProblem solving |