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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Argument Mapping |  Innovation Lean Startup |  Decision Making Cynefin Workshop |
|---|---|---|---|---|
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 statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on. | 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 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-3 h | Wochen bis Monate je Lernzyklus | 60-180 min |
Participantsdifferent | 1-4 | 1-8 | 2-8 | 4-20 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Argument Map, Evidence Gaps, Decision Rationale | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Cynefin Map, Domain-specific Actions, Sensemaking Notes |
Tagsno overlap | Knowledge graphValidationSemantic | SensemakingDecisionRationale | LeanStartupValidationMVP | ComplexitySensemakingDecision |