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| Criterion |  Product Discovery Kano Model |  Operations Causal Factor Analysis |  UX Research Affinity Diagramming |  Operations 5 Whys |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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 single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | Medium | High | Low | Low |
Timedifferent | 1-2 Tage | 2-6 h | 45–90 min | 15-30 min |
Participantsdifferent | 10-50 | 3-10 | 3-10 | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Theme clusters, Insight statements, Opportunity areas | Root cause notes, Countermeasures |
Tagsno overlap | SatisfactionPrioritizationCustomer | CausalityIncidentRoot causeTimeline | SynthesisQualitativeRoot cause | Root causeIncidentLeanProblem solving |