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| Criterion |  Product Discovery Assumption Mapping |  Growth A/B Testing |  Knowledge Modeling Competency Questions |  Knowledge Modeling Shape-First Modeling |
|---|---|---|---|---|
Purposedifferent | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. | 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. |
Complexitydifferent | Medium | High | Medium | Medium |
Timedifferent | 45-60 min | 1-4 Wochen | 2-4 h | Halber Tag pro Domain Slice |
Participantsdifferent | 2-8 | 1-6 | 2-8 | 1-4 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation |
Tagsno overlap | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation | OntologyKnowledge graphScopeRequirementsSemantic | Knowledge graphValidationSemantic |