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Criterion
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for NoEstimates.
Agile
NoEstimates
Purposedifferent
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.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
MediumHighMedium
Timedifferent
1-3 h30-90 min Setup, danach laufendlaufend
Participantsdifferent
3-81-82-12
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Bottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresForecast Percentiles, Throughput Dataset, Risk CommunicationThroughput Data, Flow Forecast, Slicing Rules
Tags1 shared
FlowMeasurementConstraints
ForecastingFlowDelivery
EstimationForecastingFlow
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Theory of Constraints.
Operations
Theory of Constraints
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation