View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Systems Thinking Causal Loop Diagram |  Product Discovery Experiment Canvas |  Product Strategy DIBB |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations. | 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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | Low | Low | Medium |
Timedifferent | 1-3 h | 30-60 min | 1-2 h | 45-60 min |
Participantsdifferent | 2-8 | 1-5 | 2-8 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Causal Loop Diagram, Feedback Notes, Leverage Points | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | FeedbackSystems thinkingCausalityDynamics | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | AssumptionsRiskExperimentsValidation |