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Criterion
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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 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
LowMediumHighLow
Timedifferent
45-90 min30-90 min1-4 Wochen30-60 min
Participantsdifferent
2-81-61-61-5
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Assumption List, Critical Assumptions, Learning PlanDecision Tree, Option Map, Assumption ListExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success Metric
Tagsno overlap
AssumptionsRiskDecisionDiscovery
DecisionTreeOptions
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
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