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Criterion
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
A3 Problem-Solving workspace showing the question, observations, and next decision.
Operations
A3 Problem Solving
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
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.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 complex deviation with several people involved, the method bundles problem, analysis, and decision onto one page. It creates a shared working space where causes, countermeasures, and follow-up fit together.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.
Complexitydifferent
LowHighMediumMedium
Timedifferent
1 h bis mehrere Wochen30-90 min Setup, danach laufend45-90 min1-3 h
Participantsdifferent
1-81-82-54-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeForecast Percentiles, Throughput Dataset, Risk CommunicationA3 Report, Action Plan, Root Cause AnalysisCurrent-state map, Future-state map, Bottleneck list
Tagsno overlap
Continuous improvementLeanExperiments
ForecastingFlowDelivery
LeanProblem solvingCoachingOperations
LeanFlowWasteDelivery
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