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Criterion
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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 two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.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.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
MediumHighMediumLow
Timedifferent
Ongoing1-4 Wochen60-90 min30-60 min
Participantsdifferent
2-121-63-81-5
Formatdifferent
Workshop + asyncAsyncWorkshopWorkshop + async
Outputdifferent
Kanban board, WIP policies, Flow metricsExperiment results, Decision log, Learning summaryPrioritization Canvas, Hypothesis BacklogCompleted Experiment Canvas, Success Metric
Tagsno overlap
FlowVisual managementDelivery
ExperimentsGrowthAnalyticsValidation
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsValidationDiscoveryHypothesis
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