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| Criterion |  Product Strategy ICE Scoring |  Innovation Design Sprint |  Decision Making Constraint Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 | High | Low | High |
Timedifferent | 30-60 min | 4-5 Tage | 30-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 5-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | ICE Table, Top Idea List | Prototype, Test Findings, Decision Rationale | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | Design sprintPrototypeValidationInnovation | ConstraintsDecisionPlanningOptions | ExperimentsGrowthAnalyticsValidation |