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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Process Mapping method illustration showing its working structure
Operations
Process Mapping
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.With a confusing workflow that has many handoffs, the method makes the actual process visible. It shows where work is passed on, delayed, or duplicated, so improvement targets the right spots.
Complexitydifferent
HighMediumMedium
Timedifferent
30-90 min Setup, danach laufend1-3 h1-3 h
Participantsdifferent
1-83-83-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationBottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresProcess Map, Handoff List, Improvement Backlog
Tagsno overlap
ForecastingFlowDelivery
FlowMeasurementConstraints
ProcessOperationsImprovement
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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 of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk