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| Criterion |  Operations Scatter Diagram |  Growth A/B Testing |  Operations Root Cause Tree Analysis |  Operations Root Cause Analysis |
|---|---|---|---|---|
Purposedifferent | When the question is whether two measures are related, the method makes patterns in the data picture visible. It separates felt correlations from relationships that actually show up in the data. | 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 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 a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. |
Complexitydifferent | Low | High | Medium | Medium |
Timedifferent | 30-90 min | 1-4 Wochen | 1-3 h | 1-4 h |
Participantsdifferent | 1-4 | 1-6 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | Scatter Plot, Korrelationsnotiz, Hypothesenliste | Experiment results, Decision log, Learning summary | Cause Tree, Evidence Notes, Countermeasures | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | Root causeQualityVisualization | ExperimentsGrowthAnalyticsValidation | Root causeTreeIncidentQuality | Root causeProblem solvingQualityIncident |