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Criterion
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Story Points.
Agile
Story Points
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.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.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.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
MediumMediumLowHigh
Timedifferent
laufendlaufend, 1-5 min je Item5-20 min30-90 min Setup, danach laufend
Participantsdifferent
2-123-93-201-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Throughput Data, Flow Forecast, Slicing RulesPoint Estimates, Reference Stories, Velocity DataEffort Heatmap, Risk Signals, Discussion TargetsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationForecastingFlow
EstimationAgileMeasurement
EstimationEffortRisk
ForecastingFlowDelivery
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