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| Criterion |  UX Research Affinity Diagramming |  Product Strategy DIBB |  Operations Root Cause Analysis |  Operations Root Cause Tree Analysis |
|---|---|---|---|---|
Purposedifferent | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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. | 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 | Low | Medium | Medium |
Timedifferent | 45–90 min | 1-2 h | 1-4 h | 1-3 h |
Participantsdifferent | 3-10 | 2-8 | 3-8 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | DIBB document, Belief list, Bet list, Learning report | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | SynthesisQualitativeRoot cause | StrategyDecisionAssumptionsHypothesis | Root causeProblem solvingQualityIncident | Root causeTreeIncidentQuality |