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Criterion
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Paper illustration for Root Cause Analysis.
Operations
Root Cause Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree Analysis
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.When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another.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 problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie.
Complexitydifferent
LowMediumHighMedium
Timedifferent
1 h bis mehrere Wochen1-4 h1-4 Wochen1-3 h
Participantsdifferent
1-83-81-62-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeProblem Statement, Cause Hypotheses, Confirmed Causes, Action PlanExperiment results, Decision log, Learning summaryCause Tree, Evidence Notes, Countermeasures
Tagsno overlap
Continuous improvementLeanExperiments
Root causeProblem solvingQualityIncident
ExperimentsGrowthAnalyticsValidation
Root causeTreeIncidentQuality
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