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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Strategy ICE Scoring |  Growth A/B Testing |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | Low | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | 30-60 min | 1-4 Wochen | 45-60 min |
Participantsdifferent | 1-4 | 2-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | ICE Table, Top Idea List | Experiment results, Decision log, Learning summary | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | PrioritizationScoringGrowthDecision | ExperimentsGrowthAnalyticsValidation | AssumptionsRiskExperimentsValidation |