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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Fake Door Test
Product Discovery
Fake Door 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.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
HighHighMedium
Timedifferent
1-4 Wochen30-90 min Setup, danach laufend1-5 Tage
Participantsdifferent
6-30 Experten1-8Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncAsync
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk CommunicationClick Data, Interest Signal, Learning Decision
Tagsno overlap
ForecastingExpertsDecisionStrategy
ForecastingFlowDelivery
ValidationExperimentsDemandDiscovery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test