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| Criterion |  Operations After-Action Review |  Operations PDCA Cycle |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | After missions or project phases with unclear outcomes, the method makes visible what actually happened and what can be learned from it. It separates course, effect, and causes so experience turns into solid improvement. | 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. | 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 | Low | Low | High | Low |
Timedifferent | 20-45 min | 1 h bis mehrere Wochen | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-12 | 1-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Lessons learned, Action items, Event summary | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | LearningOperationsImprovement | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |