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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Ideal Days.
Agile
Ideal Days
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for NoEstimates.
Agile
NoEstimates
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.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.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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.
Complexitydifferent
MediumLowHighMedium
Timedifferent
30-90 min15-60 min30-90 min Setup, danach laufendlaufend
Participantsdifferent
3-122-91-82-12
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsIdeal Day Estimates, Assumption Notes, Capacity CaveatsForecast Percentiles, Throughput Dataset, Risk CommunicationThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
EstimationBacklogRelative sizing
EstimationEffortAgile
ForecastingFlowDelivery
EstimationForecastingFlow
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