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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Delphi Method |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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 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. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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. |
Complexitydifferent | Medium | High | Medium | Low |
Timedifferent | Halber Tag pro Domain Slice | 1-4 Wochen | 60-90 min | 30-60 min |
Participantsdifferent | 1-4 | 6-30 Experten | 3-8 | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Expert Forecast, Consensus Range, Assumption Notes | Prioritization Canvas, Hypothesis Backlog | Completed Experiment Canvas, Success Metric |
Tagsno overlap | Knowledge graphValidationSemantic | ForecastingExpertsDecisionStrategy | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsValidationDiscoveryHypothesis |