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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Story Points.
Agile
Story Points
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Paper illustration for NoEstimates.
Agile
NoEstimates
Purposedifferent
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 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.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.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
HighMediumMediumMedium
Timedifferent
30-90 min Setup, danach laufendlaufend, 1-5 min je Item1-3 hlaufend
Participantsdifferent
1-83-93-82-12
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationPoint Estimates, Reference Stories, Velocity DataBottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
ForecastingFlowDelivery
EstimationAgileMeasurement
FlowMeasurementConstraints
EstimationForecastingFlow
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