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Criterion
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
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
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.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.For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput.
Complexitydifferent
MediumLowHighMedium
Timedifferent
laufend, 1-5 min je Item5-20 min30-90 min Setup, danach laufend1-3 h
Participantsdifferent
3-93-201-83-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Point Estimates, Reference Stories, Velocity DataEffort Heatmap, Risk Signals, Discussion TargetsForecast Percentiles, Throughput Dataset, Risk CommunicationBottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures
Tagsno overlap
EstimationAgileMeasurement
EstimationEffortRisk
ForecastingFlowDelivery
FlowMeasurementConstraints
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