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| Criterion |  Growth Growth Experiment |  Engineering Kanban |  Operations PDCA Cycle |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 1-2 Wochen | Ongoing | 1 h bis mehrere Wochen | 1-4 Wochen |
Participantsdifferent | 1-6 | 2-12 | 1-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Kanban board, WIP policies, Flow metrics | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary |
Tagsno overlap | MarketingGrowthExperimentsLearning | FlowVisual managementDelivery | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation |