View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Domain Modeling Context Map |  Decision Making Force Field Analysis |  Product Discovery Experiment Canvas |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | When several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries. | 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. | 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. |
Complexitydifferent | Medium | Low | Low | Low |
Timedifferent | 1-3 h | 45-90 min | 30-60 min | 1-2 h |
Participantsdifferent | 2-8 | 3-12 | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Context Map, Integration Patterns, Boundary Notes | Force Field Map, Change Levers, Risk Notes | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | Domain-Driven DesignBoundariesStrategy | ChangeDecisionStrategy | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |