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Criterion
How Might We
Innovation
How Might We
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
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
With a stuck problem carrying many implicit assumptions, the method translates observations into open, workable questions. It sharpens the problem frame without pre-thinking the solution, turning frustration or fuzziness into a search space with clear direction.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 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
LowHighLowHigh
Timedifferent
30–45 min1-4 Wochen1-5 Tage1-4 Wochen
Participantsdifferent
1-106-30 ExpertenNutzertraffic1-6
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsExpert Forecast, Consensus Range, Assumption NotesInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
FramingOpportunityIdeationQuestions
ForecastingExpertsDecisionStrategy
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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