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| Criterion |  UX Research Affinity Diagramming |  Innovation Lean Startup |  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. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. | 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 | Medium | Medium | Medium |
Timedifferent | 45–90 min | Wochen bis Monate je Lernzyklus | 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 | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | SynthesisQualitativeRoot cause | LeanStartupValidationMVP | Root causeProblem solvingQualityIncident | Root causeTreeIncidentQuality |