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| Criterion |  Knowledge Modeling Shape-First Modeling |  Operations 5 Whys |  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 a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. | 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 | Low | Medium |
Timedifferent | Halber Tag pro Domain Slice | 15-30 min | 1-4 h |
Participantsdifferent | 1-4 | 2-6 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Root cause notes, Countermeasures | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | Knowledge graphValidationSemantic | Root causeIncidentLeanProblem solving | Root causeProblem solvingQualityIncident |
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