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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.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.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.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
HighHighLowLow
Timedifferent
1-4 Wochen1-4 Wochen20-35 min1-2 h
Participantsdifferent
6-30 Experten1-61-52-8
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryTest Card with a pre-set thresholdDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
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