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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Cynefin Workshop |  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. | When problems are unclear, chaotic, or only seemingly familiar, standard recipes fall short. A Cynefin Workshop sorts situations by the nature of their problem and connects them with matching action logic. | 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 | 60-180 min | 1-4 h | 45-60 min |
Participantsdifferent | 1-4 | 4-20 | 3-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Cynefin Map, Domain-specific Actions, Sensemaking Notes | Challenge Findings, Risk Register, Mitigation Plan | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | ComplexitySensemakingDecision | RiskDecisionSensemaking | AssumptionsRiskExperimentsValidation |