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Criterion
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Story Points.
Agile
Story Points
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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.When delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible.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.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
1-3 h1-3 hlaufend, 1-5 min je Item30-90 min Setup, danach laufend
Participantsdifferent
3-84-103-91-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Bottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresCurrent-state map, Future-state map, Bottleneck listPoint Estimates, Reference Stories, Velocity DataForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
FlowMeasurementConstraints
LeanFlowWasteDelivery
EstimationAgileMeasurement
ForecastingFlowDelivery
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