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| Criterion |  Operations Root Cause Tree Analysis |  Product Discovery Smoke Test |  Operations Fishbone Diagram |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie. | 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. | 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 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. |
Complexitydifferent | Medium | Low | Low | High |
Timedifferent | 1-3 h | 1-5 Tage | 30-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 2-8 | 1-6 |
Formatdifferent | Workshop | Async | Workshop | Async |
Outputdifferent | Cause Tree, Evidence Notes, Countermeasures | Interest Metrics, Conversion Signal, Learning Note | Fishbone Diagram, Cause Categories, Investigation Backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | Root causeTreeIncidentQuality | ValidationExperimentsDemandGrowth | Root causeQualityOperations | ExperimentsGrowthAnalyticsValidation |