methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Paper illustration for DMAIC.
Operations
DMAIC
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together.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 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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
HighLowHighMedium
Timedifferent
2-12 Wochen1 h bis mehrere Wochen1-4 Wochen1-5 Tage
Participantsdifferent
3-101-81-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Project Charter, Measurement Plan, Cause Analysis, Control PlanPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning Decision
Tagsno overlap
Continuous improvementQualityProcess improvement
Continuous improvementLeanExperiments
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
Add more methods