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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Paper illustration of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
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.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.After missions or project phases with unclear outcomes, the method makes visible what actually happened and what can be learned from it. It separates course, effect, and causes so experience turns into solid improvement.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
HighMediumLowMedium
Timedifferent
30-90 min Setup, danach laufend1-3 h20-45 minlaufend
Participantsdifferent
1-83-83-122-12
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationBottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresLessons learned, Action items, Event summaryThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
ForecastingFlowDelivery
FlowMeasurementConstraints
LearningOperationsImprovement
EstimationForecastingFlow
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