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Criterion
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration for OODA Loop.
Decision Making
OODA Loop
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 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 The result is captured as a prioritization canvas and a hypothesis backlog.In dynamic situations, decisions become outdated faster than they can be prepared. The OODA Loop holds observing, orienting, deciding, and acting together as a recurring rhythm so reaction does not slide into inertia.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
MediumMediumLowLow
Timedifferent
60-90 min15-60 min je Zyklus1-2 h30-60 min
Participantsdifferent
3-81-82-81-5
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Prioritization Canvas, Hypothesis BacklogSituation Assessment, Decision Loop, Action UpdatesDIBB document, Belief list, Bet list, Learning reportCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsPrioritizationDiscoveryHypothesis
DecisionChangeLearningStrategy
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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