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| Criterion |  Systems Thinking Causal Loop Diagram |  Product Discovery Experiment Canvas |  Decision Making Assumption Surfacing |  Product Strategy DIBB |
|---|---|---|---|---|
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. | 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. | 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 | 30-60 min | 45-90 min | 1-2 h |
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 | Assumption List, Critical Assumptions, Learning Plan | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | FeedbackSystems thinkingCausalityDynamics | ExperimentsValidationDiscoveryHypothesis | AssumptionsRiskDecisionDiscovery | StrategyDecisionAssumptionsHypothesis |