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| Criterion |  Decision Making Decision Tree |  UX Research Affinity Diagramming |  Operations Root Cause Tree Analysis |  Operations Root Cause Analysis |
|---|---|---|---|---|
Purposedifferent | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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. | 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 | Medium | Low | Medium | Medium |
Timedifferent | 30-90 min | 45–90 min | 1-3 h | 1-4 h |
Participantsdifferent | 1-6 | 3-10 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Theme clusters, Insight statements, Opportunity areas | Cause Tree, Evidence Notes, Countermeasures | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | DecisionTreeOptions | SynthesisQualitativeRoot cause | Root causeTreeIncidentQuality | Root causeProblem solvingQualityIncident |