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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Discovery Riskiest Assumption Test |  Product Strategy Lean Canvas |  Innovation Lean Startup |
|---|---|---|---|---|
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. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-2 Wochen pro Iteration | 45-90 min | Wochen bis Monate je Lernzyklus |
Participantsdifferent | 1-4 | 2-6 | 1-6 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized Assumption List, Test Plan, Results Report | Lean Canvas, Core Assumptions, Experiment Backlog | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision |
Tagsno overlap | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryAssumptions | StartupLeanAssumptionsBusiness model | LeanStartupValidationMVP |