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Criterion
Scenario Planning method illustration showing its working structure
Business Strategy
Scenario Planning
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
Scenario Planning opens the view to several plausible futures instead of a single forecast. The method protects strategies from depending on too narrow an expected path.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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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.
Complexitydifferent
HighLowLowHigh
Timedifferent
0.5-2 Tage1-2 h1-5 Tage1-4 Wochen
Participantsdifferent
4-122-8Nutzertraffic1-6
Formatdifferent
WorkshopWorkshop + asyncAsyncAsync
Outputdifferent
Scenario Set, Strategic Implications, Robust OptionsDIBB document, Belief list, Bet list, Learning reportInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
StrategyUncertaintyPlanning
StrategyDecisionAssumptionsHypothesis
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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