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Criterion
Paper illustration for Story Points.
Agile
Story Points
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When teams want to rate complexity rather than hours, it creates a shared, relative scale. It sorts work by value, risk, and delivery ability. The result is captured as Point Estimates, Reference Stories, and Velocity Data.A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes.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.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
MediumMediumMediumHigh
Timedifferent
laufend, 1-5 min je Item10-30 min je Itemlaufend30-90 min Setup, danach laufend
Participantsdifferent
3-91-82-121-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Point Estimates, Reference Stories, Velocity DataThree-Point Estimate, Risk Range, Assumption NotesThroughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationAgileMeasurement
EstimationUncertaintyForecasting
EstimationForecastingFlow
ForecastingFlowDelivery
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