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| Criterion |  Product Discovery Kano Model |  Operations PDCA Cycle |  Operations Root Cause Analysis |  Operations Root Cause Tree 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. | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | 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 | Medium | Low | Medium | Medium |
Timedifferent | 1-2 Tage | 1 h bis mehrere Wochen | 1-4 h | 1-3 h |
Participantsdifferent | 10-50 | 1-8 | 3-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | SatisfactionPrioritizationCustomer | Continuous improvementLeanExperiments | Root causeProblem solvingQualityIncident | Root causeTreeIncidentQuality |