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Criterion
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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.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 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.
Complexitydifferent
LowLowHigh
Timedifferent
1 h bis mehrere Wochen1-2 h1-4 Wochen
Participantsdifferent
1-82-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsync
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeDIBB document, Belief list, Bet list, Learning reportExperiment results, Decision log, Learning summary
Tagsno overlap
Continuous improvementLeanExperiments
StrategyDecisionAssumptionsHypothesis
ExperimentsGrowthAnalyticsValidation
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration for Smoke Test.
Product Discovery
Smoke Test