View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Product Strategy DIBB |  Knowledge Modeling Competency Questions |  Decision Making Assumption Surfacing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. | 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 | Low | Medium | Low | Low |
Timedifferent | 1-2 h | 2-4 h | 45-90 min | 30-60 min |
Participantsdifferent | 2-8 | 2-8 | 2-8 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Assumption List, Critical Assumptions, Learning Plan | Completed Experiment Canvas, Success Metric |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | OntologyKnowledge graphScopeRequirementsSemantic | AssumptionsRiskDecisionDiscovery | ExperimentsValidationDiscoveryHypothesis |