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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
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk
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.When there is uncertainty about the real course of a process, the method brings observation to the place where work happens. It combines perception, follow-up questions, and process knowledge so decisions rest on actual workflows instead of assumptions.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 h30-120 min30-90 min Setup, danach laufend
Participantsdifferent
1-84-102-61-8
Formatdifferent
Workshop + asyncWorkshopWorkshopWorkshop + async
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeCurrent-state map, Future-state map, Bottleneck listObservation Notes, Improvement IdeasForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
Continuous improvementLeanExperiments
LeanFlowWasteDelivery
LeanObservationProcessOperations
ForecastingFlowDelivery
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