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| Criterion |  Product Discovery Assumption Mapping |  Product Strategy DIBB |  Knowledge Modeling Shape-First Modeling |  Product Discovery Riskiest Assumption Test |
|---|---|---|---|---|
Purposedifferent | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | 45-60 min | 1-2 h | Halber Tag pro Domain Slice | 1-2 Wochen pro Iteration |
Participantsdifferent | 2-8 | 2-8 | 1-4 | 2-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Assumption map, Test backlog, Risk ranking | DIBB document, Belief list, Bet list, Learning report | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized Assumption List, Test Plan, Results Report |
Tagsno overlap | AssumptionsRiskExperimentsValidation | StrategyDecisionAssumptionsHypothesis | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryAssumptions |