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| Criterion | ![]() Engineering Kanban | ![]() Decision Making Force Field Analysis | ![]() Product Discovery Experiment Canvas | ![]() Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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 | Ongoing | 45-90 min | 30-60 min | 1-2 h |
Participantsdifferent | 2-12 | 3-12 | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Force Field Map, Change Levers, Risk Notes | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | FlowVisual managementDelivery | ChangeDecisionStrategy | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |



