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| Criterion |  Growth A/B Testing |  Operations Fishbone Diagram |  Growth Funnel Analysis |  Operations Failure Mode and Effects 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. | When a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. | 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 process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability. |
Complexitydifferent | High | Low | Medium | High |
Timedifferent | 1-4 Wochen | 30-60 min | 1-3 h | 2-6 h |
Participantsdifferent | 1-6 | 2-8 | 1-5 | 3-10 |
Formatdifferent | Async | Workshop | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Fishbone Diagram, Cause Categories, Investigation Backlog | Funnel report, Drop-off analysis, Optimization hypotheses | FMEA Table, Risk Priority, Mitigation Actions |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeQualityOperations | AnalyticsConversionGrowth | RiskQualityOperationsRoot cause |