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| Criterion |  Operations 5 Whys |  Growth Growth Experiment |  Operations Root Cause Tree Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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. | 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 | Low | Medium | Medium | High |
Timedifferent | 15-30 min | 1-2 Wochen | 1-3 h | 1-4 Wochen |
Participantsdifferent | 2-6 | 1-6 | 2-8 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Workshop | Async |
Outputdifferent | Root cause notes, Countermeasures | Experiment card, Result summary, Next bet | Cause Tree, Evidence Notes, Countermeasures | Experiment results, Decision log, Learning summary |
Tagsno overlap | Root causeIncidentLeanProblem solving | MarketingGrowthExperimentsLearning | Root causeTreeIncidentQuality | ExperimentsGrowthAnalyticsValidation |