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| Criterion |  UX Research Affinity Diagramming |  Product Discovery Kano Model |  Operations MORT Analysis |  Operations Causal Factor 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. | When features need to be distinguished by their effect on satisfaction, it makes expectations and surprises comparable. It separates basic needs, performance contribution, and delight. | For a safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. |
Complexitydifferent | Low | Medium | High | High |
Timedifferent | 45–90 min | 1-2 Tage | Mehrere Tage bis Wochen | 2-6 h |
Participantsdifferent | 3-10 | 10-50 | 2-6 | 3-10 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Kano Matrix, Feature Classes, Priority Themes | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | SynthesisQualitativeRoot cause | SatisfactionPrioritizationCustomer | Root causeSafetySystemicIncident | CausalityIncidentRoot causeTimeline |