View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Operations PDCA Cycle |  Growth Growth Experiment |  Operations After-Action Review |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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. | 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 | Low | High |
Timedifferent | 1 h bis mehrere Wochen | 1-2 Wochen | 20-45 min | 1-4 Wochen |
Participantsdifferent | 1-8 | 1-6 | 3-12 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment card, Result summary, Next bet | Lessons learned, Action items, Event summary | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementLeanExperiments | MarketingGrowthExperimentsLearning | LearningOperationsImprovement | ExperimentsGrowthAnalyticsValidation |