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| Criterion |  Operations ABC Analysis |  Product Strategy ICE Scoring |  Growth Growth Experiment |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | With many similar objects of differing economic significance, the method prioritizes effort by effect. It separates what needs regular steering from what rarely needs attention. | 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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 | Medium | High |
Timedifferent | 30-60 min | 30-60 min | 1-2 Wochen | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-8 | 1-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | ABC Classification, Focus Rules, Control List | ICE Table, Top Idea List | Experiment card, Result summary, Next bet | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationOperationsPortfolio | PrioritizationScoringGrowthDecision | MarketingGrowthExperimentsLearning | ExperimentsGrowthAnalyticsValidation |