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| Criterion |  Decision Making Decision Tree |  Operations Root Cause Analysis |  UX Research Affinity Diagramming |  Operations Kepner-Tregoe |
|---|---|---|---|---|
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 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 disturbance that's hard to pin down, the method cleanly separates problem, cause, and decision. It reduces mixing when symptoms allow several interpretations. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 30-90 min | 1-4 h | 45–90 min | 2-8 h |
Participantsdifferent | 1-6 | 3-8 | 3-10 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Theme clusters, Insight statements, Opportunity areas | Problem Analysis, Decision Analysis, Risk Plan |
Tagsno overlap | DecisionTreeOptions | Root causeProblem solvingQualityIncident | SynthesisQualitativeRoot cause | Problem solvingRoot causeDecisionOperations |