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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Knowledge Mapping |  Decision Making Red Teaming |  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 strategic decisions with high reach, agreement and gut feeling are often not enough. Red teaming brings deliberate opposition into the situation and tests where a plan breaks under real counterarguments. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-3 h | 1-4 h | 45-60 min |
Participantsdifferent | 1-4 | 3-12 | 3-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Challenge Findings, Risk Register, Mitigation Plan | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | KnowledgeMappingRisk | RiskDecisionSensemaking | AssumptionsRiskExperimentsValidation |