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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Kaizen Event.
Operations
Kaizen Event
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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.For a tightly scoped process segment with noticeable waste, the method bundles shared energy for change. It suits situations that call for fast learning loops and visible adjustments.For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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
HighMediumLowLow
Timedifferent
1-4 Wochen0.5-5 Tage1 h bis mehrere Wochen30-60 min
Participantsdifferent
1-64-101-81-5
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryKaizen Charter, Waste List, Improvement Experiments, Standard Work UpdatePDCA Log, Experiment Plan, Learning Outcome, Standard ChangeCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
LeanContinuous improvementOperations
Continuous improvementLeanExperiments
ExperimentsValidationDiscoveryHypothesis
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