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| Criterion |  Product Discovery Kano Model |  Operations Root Cause Analysis |  Agile Example Mapping |  Decision Making Pareto 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. | 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. | When a story carries business rules and exceptions, it brings clarity before implementation. It makes examples, open questions, and boundaries visible enough that the logic becomes jointly sound. | In many problem situations, effect is distributed unequally across many causes. A Pareto Analysis separates the few drivers with high leverage from the long remainder and focuses attention on what measurably moves the needle. |
Complexitydifferent | Medium | Medium | Low | Low |
Timedifferent | 1-2 Tage | 1-4 h | 30-60 min | 30-60 min |
Participantsdifferent | 10-50 | 3-8 | 3-7 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Example Map, Acceptance Criteria, Open Questions | Pareto Chart, Top Causes, Focus List |
Tagsno overlap | SatisfactionPrioritizationCustomer | Root causeProblem solvingQualityIncident | Behavior-Driven DevelopmentRequirementsExamplesRefinement | PrioritizationQualityFocusRoot cause |