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| Criterion |  Product Strategy DIBB |  UX Research User Interviews |  Decision Making Force Field Analysis |  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. | When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | 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. |
Complexitysame | Low | Low | Low | Low |
Timedifferent | 1-2 h | 30–60 min per interview | 45-90 min | 30-60 min |
Participantsdifferent | 2-8 | 1 participant per interview | 3-12 | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Interview Notes, Themes, Insight Summary | Force Field Map, Change Levers, Risk Notes | Completed Experiment Canvas, Success Metric |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | QualitativeResearchCustomerDiscovery | ChangeDecisionStrategy | ExperimentsValidationDiscoveryHypothesis |