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Criterion
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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.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.
Complexitydifferent
LowMediumLowHigh
Timedifferent
1 h bis mehrere Wochen1-3 h45-120 min30-90 min Setup, danach laufend
Participantsdifferent
1-84-102-81-8
Formatdifferent
Workshop + asyncWorkshopWorkshopWorkshop + async
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeCurrent-state map, Future-state map, Bottleneck listWaste Map, Prioritized Waste, Improvement BacklogForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
Continuous improvementLeanExperiments
LeanFlowWasteDelivery
WasteLeanProcess improvement
ForecastingFlowDelivery
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