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Criterion
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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.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.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.DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.
Complexitydifferent
LowLowHighLow
Timedifferent
45-90 min30-60 min1-4 Wochen1-2 h
Participantsdifferent
2-81-51-62-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Assumption List, Critical Assumptions, Learning PlanCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summaryDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
AssumptionsRiskDecisionDiscovery
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
StrategyDecisionAssumptionsHypothesis
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