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| Criterion |  Growth Growth Experiment |  Engineering Fault Isolation |  Engineering Hypothesis-Driven Troubleshooting |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | In technical failures, the visible symptom often gets mixed up with the actual cause. Fault Isolation narrows the fault space and progressively reduces which part of the system is truly affected. | 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 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | 1-2 Wochen | 30-180 min | 30-240 min | 1-4 Wochen |
Participantssame | 1-6 | 1-6 | 1-6 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Fault Isolation Map, Test Log, Excluded Hypotheses, Narrowed Fault Area | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary | Experiment results, Decision log, Learning summary |
Tagsno overlap | MarketingGrowthExperimentsLearning | TroubleshootingDiagnosisEngineering | TroubleshootingProblem solvingDiagnosis | ExperimentsGrowthAnalyticsValidation |