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| Criterion |  Knowledge Modeling Shape-First Modeling |  Systems Thinking Leverage Points |  Product Discovery Assumption Mapping |  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. | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | High | Medium | High |
Timedifferent | Halber Tag pro Domain Slice | Half day | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-4 | 3-12 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Leverage Map, Action Strategy | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | Knowledge graphValidationSemantic | Systems thinkingChangeStrategy | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |