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| Criterion |  Decision Making Delphi Method |  Delivery Monte Carlo Forecasting |  Product Discovery Smoke 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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | High | High | Low | Medium |
Timedifferent | 1-4 Wochen | 30-90 min Setup, danach laufend | 1-5 Tage | 1-5 Tage |
Participantsdifferent | 6-30 Experten | 1-8 | Nutzertraffic | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Interest Metrics, Conversion Signal, Learning Note | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ForecastingFlowDelivery | ValidationExperimentsDemandGrowth | ValidationExperimentsDemandDiscovery |