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| Criterion |  Product Discovery Kano Model |  UX Research HEART Framework |  Operations MORT Analysis |  Operations Causal Factor Analysis |
|---|---|---|---|---|
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. | Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | 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 | Medium | Medium | High | High |
Timedifferent | 1-2 Tage | 120 min initial, dann laufend | Mehrere Tage bis Wochen | 2-6 h |
Participantsdifferent | 10-50 | 3-6 | 2-6 | 3-10 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | HEART-GSM Table, Dashboard | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | SatisfactionPrioritizationCustomer | MetricsUX researchMeasurementSatisfaction | Root causeSafetySystemicIncident | CausalityIncidentRoot causeTimeline |