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| Criterion |  Product Strategy DIBB |  Engineering Kanban |  Product Discovery Hypothesis Prioritization Canvas |  Decision Making Assumption Surfacing |
|---|---|---|---|---|
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 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. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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. |
Complexitydifferent | Low | Medium | Medium | Low |
Timedifferent | 1-2 h | Ongoing | 60-90 min | 45-90 min |
Participantsdifferent | 2-8 | 2-12 | 3-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Kanban board, WIP policies, Flow metrics | Prioritization Canvas, Hypothesis Backlog | Assumption List, Critical Assumptions, Learning Plan |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | FlowVisual managementDelivery | ExperimentsPrioritizationDiscoveryHypothesis | AssumptionsRiskDecisionDiscovery |