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| Criterion |  Operations PDCA Cycle |  Knowledge Modeling Teach-back |  Growth A/B Testing |  Growth Growth Experiment |
|---|---|---|---|---|
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. | Teach-back checks whether an explanation actually got through to the other person. The method makes misunderstandings visible early and strengthens shared understanding in advisory and learning situations. | 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 | 1 h bis mehrere Wochen | 5-20 min | 1-4 Wochen | 1-2 Wochen |
Participantsdifferent | 1-8 | 2-8 | 1-6 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Understanding Check, Clarification Notes, Learning Gaps | Experiment results, Decision log, Learning summary | Experiment card, Result summary, Next bet |
Tagsno overlap | Continuous improvementLeanExperiments | LearningUnderstandingCommunication | ExperimentsGrowthAnalyticsValidation | MarketingGrowthExperimentsLearning |