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| Criterion |  Operations PDCA Cycle |  Growth Flywheel |  Growth Hooked Model |  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. | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | 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 | Multiple workshops over several weeks | 1-4 Wochen |
Participantsdifferent | 1-8 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementLeanExperiments | GrowthRetentionConversion | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation |