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| Criterion |  Growth A/B Testing |  Operations PDCA Cycle |  Operations DMAIC |  Product Discovery Smoke Test |
|---|---|---|---|---|
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. | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together. | 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 | High | Low | High | Low |
Timedifferent | 1-4 Wochen | 1 h bis mehrere Wochen | 2-12 Wochen | 1-5 Tage |
Participantsdifferent | 1-6 | 1-8 | 3-10 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Project Charter, Measurement Plan, Cause Analysis, Control Plan | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Continuous improvementLeanExperiments | Continuous improvementQualityProcess improvement | ValidationExperimentsDemandGrowth |