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| Criterion |  Operations After-Action Review |  Operations PDCA Cycle |  Growth A/B Testing |  Growth Growth Experiment |
|---|---|---|---|---|
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 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. |
Complexitydifferent | Low | Low | High | Medium |
Timedifferent | 20-45 min | 1 h bis mehrere Wochen | 1-4 Wochen | 1-2 Wochen |
Participantsdifferent | 3-12 | 1-8 | 1-6 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Lessons learned, Action items, Event summary | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary | Experiment card, Result summary, Next bet |
Tagsno overlap | LearningOperationsImprovement | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation | MarketingGrowthExperimentsLearning |