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Criterion
Paper illustration for Current Reality Tree
Systems Thinking
Current Reality Tree
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
A Current Reality Tree condenses many symptoms into a few causal chains. The method makes visible which core problems drive several negative effects at once.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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
HighHighMediumLow
Timedifferent
2-6 h1-4 Wochen60-90 min25-40 min
Participantsdifferent
3-81-63-81-5
Formatdifferent
WorkshopAsyncWorkshopWorkshop + async
Outputdifferent
Current Reality Tree, Core Problems, Intervention IdeasExperiment results, Decision log, Learning summaryPrioritization Canvas, Hypothesis BacklogLearning Card with evidence and next action
Tagsno overlap
Systems thinkingRoot causeConstraintsCausality
ExperimentsGrowthAnalyticsValidation
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsValidationDiscoveryLearning
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