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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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
LowHighHighLow
Timedifferent
30–45 min1-4 Wochen1-4 Wochen1-5 Tage
Participantsdifferent
1-106-30 Experten1-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsExpert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
FramingOpportunityIdeationQuestions
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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