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| Criterion |  Decision Making Pareto Analysis |  Operations Root Cause Tree Analysis |  UX Research Affinity Diagramming |  Operations Root Cause 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. | 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 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. | 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 | Medium | Low | Medium |
Timedifferent | 30-60 min | 1-3 h | 45–90 min | 1-4 h |
Participantsdifferent | 1-6 | 2-8 | 3-10 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Pareto Chart, Top Causes, Focus List | Cause Tree, Evidence Notes, Countermeasures | Theme clusters, Insight statements, Opportunity areas | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tags1 shared | PrioritizationQualityFocusRoot cause | Root causeTreeIncidentQuality | SynthesisQualitativeRoot cause | Root causeProblem solvingQualityIncident |