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| Criterion |  Operations PDCA Cycle |  Decision Making Trade-off Analysis |  Product Strategy ICE Scoring |  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. | With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects. | 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. |
Complexitydifferent | Low | Medium | Low | High |
Timedifferent | 1 h bis mehrere Wochen | 45-120 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 1-8 | 2-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Trade-off Matrix, Criteria List, Decision Rationale, Accepted Downsides | ICE Table, Top Idea List | Experiment results, Decision log, Learning summary |
Tagsno overlap | Continuous improvementLeanExperiments | TradeoffsDecisionCriteriaOptions | PrioritizationScoringGrowthDecision | ExperimentsGrowthAnalyticsValidation |