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| Criterion |  Product Discovery Context Canvas |  Knowledge Modeling Shape-First Modeling |  Product Discovery Concierge MVP |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
Purposedifferent | When an environment of users, systems, and constraints is hard to grasp, it puts the context compactly on the table. It creates a clear reading of influence, boundary, and dependency. | 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 can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. |
Complexitydifferent | Low | Medium | Medium | Medium |
Timedifferent | 45-90 min | Halber Tag pro Domain Slice | 1-4 Wochen | 2-4 h |
Participantsdifferent | 3-10 | 1-4 | 3-10 Kunden | 2-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Context canvas, Open questions, Shared context notes | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Concierge Learnings, Service Blueprint, MVP Risks | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | ContextFramingRequirementsCanvas | Knowledge graphValidationSemantic | MVPValidationServiceDiscovery | OntologyKnowledge graphScopeRequirementsSemantic |