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Criterion
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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
HighHighMediumLow
Timedifferent
2-6 h1-4 Wochen1-2 Wochen pro Iteration30-60 min
Participantsdifferent
3-101-62-61-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Event Timeline, Causal Factor Chart, Cause List, Corrective ActionsExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
CausalityIncidentRoot causeTimeline
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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