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Criterion
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify.When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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
MediumMediumMediumHigh
Timedifferent
30-60 min30-90 min45-60 min1-4 Wochen
Participantsdifferent
2-63-122-81-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Smaller Stories, Acceptance Criteria, Split RationaleAffinity Size Map, Grouped Estimates, Unclear ItemsAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
BacklogIterationDelivery
EstimationBacklogRelative sizing
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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