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| Criterion |  Product Strategy DIBB |  Knowledge Modeling Shape-First Modeling |  Product Discovery Assumption Mapping |  Product Discovery Test Card |
|---|---|---|---|---|
Purposedifferent | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success. |
Complexitydifferent | Low | Medium | Medium | Low |
Timedifferent | 1-2 h | Halber Tag pro Domain Slice | 45-60 min | 20-35 min |
Participantsdifferent | 2-8 | 1-4 | 2-8 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Assumption map, Test backlog, Risk ranking | Test Card with a pre-set threshold |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | Knowledge graphValidationSemantic | AssumptionsRiskExperimentsValidation | ExperimentsValidationDiscoveryHypothesis |