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 DMAIC |  Growth Growth Experiment |  Operations PDCA Cycle |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together. | 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. | 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 | High | Medium | Low | High |
Timedifferent | 2-12 Wochen | 1-2 Wochen | 1 h bis mehrere Wochen | 1-4 Wochen |
Participantsdifferent | 3-10 | 1-6 | 1-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Project Charter, Measurement Plan, Cause Analysis, Control Plan | Experiment card, Result summary, Next bet | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementQualityProcess improvement | MarketingGrowthExperimentsLearning | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation |