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Criterion
Paper illustration for DMAIC.
Operations
DMAIC
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together.For a process that keeps people busy but creates little value, the method exposes waste. It directs attention to unnecessary movement, waiting times, rework, and overdelivery.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.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
HighLowMediumHigh
Timedifferent
2-12 Wochen45-120 min1-3 h30-90 min Setup, danach laufend
Participantsdifferent
3-102-84-101-8
Formatdifferent
Workshop + asyncWorkshopWorkshopWorkshop + async
Outputdifferent
Project Charter, Measurement Plan, Cause Analysis, Control PlanWaste Map, Prioritized Waste, Improvement BacklogCurrent-state map, Future-state map, Bottleneck listForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
Continuous improvementQualityProcess improvement
WasteLeanProcess improvement
LeanFlowWasteDelivery
ForecastingFlowDelivery
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