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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Ideal Days.
Agile
Ideal Days
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
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.When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats.When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets.
Complexitydifferent
MediumHighLowLow
Timedifferent
30-90 min30-90 min Setup, danach laufend15-60 min5-20 min
Participantsdifferent
3-121-82-93-20
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsForecast Percentiles, Throughput Dataset, Risk CommunicationIdeal Day Estimates, Assumption Notes, Capacity CaveatsEffort Heatmap, Risk Signals, Discussion Targets
Tagsno overlap
EstimationBacklogRelative sizing
ForecastingFlowDelivery
EstimationEffortAgile
EstimationEffortRisk
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