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| Criterion |  Knowledge Modeling Shape-First Modeling |  Delivery RAID Log |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
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. | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as a RAID Log and a source for status reporting. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Medium | Low | Low | High |
Timedifferent | Halber Tag pro Domain Slice | 30 min Setup, dann laufend | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 1-4 | 1-3 maintaining, briefing for everyone | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | RAID Log, Status Report Source | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | Knowledge graphValidationSemantic | RiskTrackingStakeholdersGovernance | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |