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| Criterion |  Delivery Monte Carlo Forecasting |  Knowledge Modeling Knowledge Mapping |  Product Discovery Smoke Test |
|---|---|---|---|
Purposedifferent | 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. | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | 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 | High | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 1-5 Tage |
Participantsdifferent | 1-8 | 3-12 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ForecastingFlowDelivery | KnowledgeMappingRisk | ValidationExperimentsDemandGrowth |
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