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| Criterion |  Growth A/B Testing |  Innovation Design Sprint |  Operations Root Cause Tree Analysis |  Operations 5 Whys |
|---|---|---|---|---|
Purposedifferent | 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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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. | 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. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | 1-4 Wochen | 4-5 Tage | 1-3 h | 15-30 min |
Participantsdifferent | 1-6 | 5-8 | 2-8 | 2-6 |
Formatdifferent | Async | Workshop | Workshop | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Prototype, Test Findings, Decision Rationale | Cause Tree, Evidence Notes, Countermeasures | Root cause notes, Countermeasures |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Design sprintPrototypeValidationInnovation | Root causeTreeIncidentQuality | Root causeIncidentLeanProblem solving |