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| Criterion |  Decision Making Pareto Analysis |  Operations Root Cause Analysis |  Growth A/B Testing |  Operations Root Cause Tree Analysis |
|---|---|---|---|---|
Purposedifferent | In many problem situations, effect is distributed unequally across many causes. A Pareto Analysis separates the few drivers with high leverage from the long remainder and focuses attention on what measurably moves the needle. | 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. | 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. |
Complexitydifferent | Low | Medium | High | Medium |
Timedifferent | 30-60 min | 1-4 h | 1-4 Wochen | 1-3 h |
Participantsdifferent | 1-6 | 3-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Pareto Chart, Top Causes, Focus List | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Experiment results, Decision log, Learning summary | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | PrioritizationQualityFocusRoot cause | Root causeProblem solvingQualityIncident | ExperimentsGrowthAnalyticsValidation | Root causeTreeIncidentQuality |