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| Criterion |  Decision Making Pareto Analysis |  Operations Root Cause Analysis |  UX Research Affinity Diagramming |  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 research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | 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 | Low | Medium |
Timedifferent | 30-60 min | 1-4 h | 45–90 min | 1-3 h |
Participantsdifferent | 1-6 | 3-8 | 3-10 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Pareto Chart, Top Causes, Focus List | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Theme clusters, Insight statements, Opportunity areas | Cause Tree, Evidence Notes, Countermeasures |
Tags1 shared | PrioritizationQualityFocusRoot cause | Root causeProblem solvingQualityIncident | SynthesisQualitativeRoot cause | Root causeTreeIncidentQuality |