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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
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.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
HighHighMediumLow
Timedifferent
1-4 Wochen1-4 Wochen2–4 h review as a planning range; preparation and evaluation additional1-5 Tage
Participantsdifferent
6-30 Experten1-6Designers, developers as users, and facilitationNutzertraffic
Formatdifferent
AsyncAsyncWorkshop + asyncAsync
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
ArchitectureEngineeringFeedbackValidationTasks
ValidationExperimentsDemandGrowth
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