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| Criterion |  Engineering Hypothesis-Driven Troubleshooting |  Product Discovery Kano Model |  Operations Root Cause Analysis |  Decision Making Pareto Analysis |
|---|---|---|---|---|
Purposedifferent | When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable. | 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. | 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 | Medium | Low |
Timedifferent | 30-240 min | 1-2 Tage | 1-4 h | 30-60 min |
Participantsdifferent | 1-6 | 10-50 | 3-8 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary | Kano Matrix, Feature Classes, Priority Themes | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Pareto Chart, Top Causes, Focus List |
Tagsno overlap | TroubleshootingProblem solvingDiagnosis | SatisfactionPrioritizationCustomer | Root causeProblem solvingQualityIncident | PrioritizationQualityFocusRoot cause |