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Criterion
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
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
When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets.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
5-20 min60-90 min1-2 h30-60 min
Participantsdifferent
3-203-82-81-5
Formatdifferent
WorkshopWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Effort Heatmap, Risk Signals, Discussion TargetsPrioritization Canvas, Hypothesis BacklogDIBB document, Belief list, Bet list, Learning reportCompleted Experiment Canvas, Success Metric
Tagsno overlap
EstimationEffortRisk
ExperimentsPrioritizationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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