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| Criterion |  Operations PDCA Cycle |  Growth A/B Testing |  Product Strategy Counter Metrics |  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 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 a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | 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 | High | Low | Low |
Timedifferent | 1 h bis mehrere Wochen | 1-4 Wochen | 30-60 min | 1-5 Tage |
Participantsdifferent | 1-8 | 1-6 | 2-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary | Counter Metric List, Guardrail Definitions | Interest Metrics, Conversion Signal, Learning Note |
Tags1 shared | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation | MetricsMeasurementStrategyExperiments | ValidationExperimentsDemandGrowth |