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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Knowledge Mapping |  Innovation Lean Startup |  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. | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-3 h | Wochen bis Monate je Lernzyklus | 45-60 min |
Participantsdifferent | 1-4 | 3-12 | 2-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | KnowledgeMappingRisk | LeanStartupValidationMVP | AssumptionsRiskExperimentsValidation |