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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Purposedifferent
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.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.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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
MediumLowHighMedium
Timedifferent
30-90 min1-2 h1-4 Wochen45-60 min
Participantsdifferent
1-62-81-62-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListDIBB document, Belief list, Bet list, Learning reportExperiment results, Decision log, Learning summaryAssumption map, Test backlog, Risk ranking
Tagsno overlap
DecisionTreeOptions
StrategyDecisionAssumptionsHypothesis
ExperimentsGrowthAnalyticsValidation
AssumptionsRiskExperimentsValidation
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