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Criterion
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.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.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 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.
Complexitydifferent
LowMediumLowLow
Timedifferent
25-40 min60-90 min1-2 h30-60 min
Participantsdifferent
1-53-82-81-5
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Learning Card with evidence and next actionPrioritization Canvas, Hypothesis BacklogDIBB document, Belief list, Bet list, Learning reportCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsValidationDiscoveryLearning
ExperimentsPrioritizationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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