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| Criterion |  Knowledge Modeling Shape-First Modeling |  Operations 8D Problem Solving |  Knowledge Modeling Competency Questions |  Operations Root Cause Analysis |
|---|---|---|---|---|
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. | For an acute quality or delivery problem, the method structures immediate protection and root cause work together. It keeps the situation stable while the actual cause is investigated cleanly. | 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. | When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. |
Complexitydifferent | Medium | High | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-6 Wochen | 2-4 h | 1-4 h |
Participantsdifferent | 1-4 | 4-10 | 2-8 | 3-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | 8D Report, Containment Plan, Root Cause Evidence, Corrective Action Plan | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | Knowledge graphValidationSemantic | QualityProblem solvingRoot cause | OntologyKnowledge graphScopeRequirementsSemantic | Root causeProblem solvingQualityIncident |