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Criterion
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Paper illustration for Theory of Constraints.
Operations
Theory of Constraints
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Process Mapping method illustration showing its working structure
Operations
Process Mapping
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.For a system that does not get faster despite effort, the method directs attention to the bottleneck. It concentrates improvement on the point that actually limits 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.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
MediumHighHighMedium
Timedifferent
1-3 h2-4 h Analyse, laufend30-90 min Setup, danach laufend1-3 h
Participantsdifferent
3-83-121-83-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Bottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresConstraint Map, Improvement Plan, Flow MetricsForecast Percentiles, Throughput Dataset, Risk CommunicationProcess Map, Handoff List, Improvement Backlog
Tagsno overlap
FlowMeasurementConstraints
OperationsConstraintsFlowImprovement
ForecastingFlowDelivery
ProcessOperationsImprovement
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