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| Criterion |  Operations PDCA Cycle |  Business Strategy Ansoff Matrix |  Product Discovery Experiment Canvas |  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. | The Ansoff Matrix organizes growth options by market and product relation. It helps weigh expansion, diversification, and adaptation cleanly against each other. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Low | Low | High |
Timedifferent | 1 h bis mehrere Wochen | 45-90 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 1-8 | 2-8 | 1-5 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Ansoff Matrix, Growth Options, Risk Notes | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementLeanExperiments | GrowthStrategyMarketPortfolio | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |