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Criterion
Paper illustration for DMAIC.
Operations
DMAIC
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Kaizen Event.
Operations
Kaizen Event
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.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 tightly scoped process segment with noticeable waste, the method bundles shared energy for change. It suits situations that call for fast learning loops and visible adjustments.
Complexitydifferent
HighLowHighMedium
Timedifferent
2-12 Wochen45-120 min30-90 min Setup, danach laufend0.5-5 Tage
Participantsdifferent
3-102-81-84-10
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop
Outputdifferent
Project Charter, Measurement Plan, Cause Analysis, Control PlanWaste Map, Prioritized Waste, Improvement BacklogForecast Percentiles, Throughput Dataset, Risk CommunicationKaizen Charter, Waste List, Improvement Experiments, Standard Work Update
Tagsno overlap
Continuous improvementQualityProcess improvement
WasteLeanProcess improvement
ForecastingFlowDelivery
LeanContinuous improvementOperations
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