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| Criterion |  Operations PDCA Cycle |  Growth Flywheel |  Growth Funnel Analysis |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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 | Medium | High |
Timedifferent | 1 h bis mehrere Wochen | 60-120 min | 1-3 h | 1-4 Wochen |
Participantsdifferent | 1-8 | 3-8 | 1-5 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementLeanExperiments | GrowthRetentionConversion | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation |