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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.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.
Complexitydifferent
MediumHigh
Timedifferent
30-90 min30-90 min Setup, danach laufend
Participantsdifferent
3-121-8
Formatdifferent
WorkshopWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationBacklogRelative sizing
ForecastingFlowDelivery
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