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| Criterion | ![]() Operations Change Analysis | ![]() Operations 5 Whys | ![]() Growth A/B Testing | ![]() Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | 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. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 45-120 min | 15-30 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 2-6 | 2-6 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Root cause notes, Countermeasures | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | Root causeIncidentLeanProblem solving | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |



