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| Criterion | ![]() Operations PDCA Cycle | ![]() Product Strategy ICE Scoring | ![]() Growth A/B Testing | ![]() Product Discovery Smoke Test |
|---|---|---|---|---|
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. | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Low | Low | High | Low |
Timedifferent | 1 h bis mehrere Wochen | 30-60 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-8 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | ICE Table, Top Idea List | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | Continuous improvementLeanExperiments | PrioritizationScoringGrowthDecision | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |



