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Criterion
Paper illustration of a branching tree with an outcome at its root, customer opportunities, solution options and small experiment cards.
Product Discovery
Opportunity Solution Tree
Paper illustration for Knowledge Mapping.
Knowledge Modeling
Knowledge Mapping
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Purposedifferent
When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure.Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable.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 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.
Complexitydifferent
MediumMediumLowMedium
Timedifferent
1-2 h Setup, laufend1-3 h1-2 h60-90 min
Participantsdifferent
2-63-122-83-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop
Outputdifferent
Opportunity Solution Tree, Experiment Backlog, Learning LogKnowledge Map, Critical Knowledge Areas, Transfer PlanDIBB document, Belief list, Bet list, Learning reportPrioritization Canvas, Hypothesis Backlog
Tagsno overlap
DiscoveryOutcomesExperimentsOpportunity
KnowledgeMappingRisk
StrategyDecisionAssumptionsHypothesis
ExperimentsPrioritizationDiscoveryHypothesis
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