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| Criterion |  Decision Making Delphi Method |  Knowledge Modeling Shape-First Modeling |  Product Discovery Experiment Canvas |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 1-4 Wochen | Halber Tag pro Domain Slice | 30-60 min | 1-5 Tage |
Participantsdifferent | 6-30 Experten | 1-4 | 1-5 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Completed Experiment Canvas, Success Metric | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ForecastingExpertsDecisionStrategy | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery |