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Criterion
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Kaizen Event.
Operations
Kaizen Event
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 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
LowHighMedium
Timedifferent
1 h bis mehrere Wochen30-90 min Setup, danach laufend0.5-5 Tage
Participantsdifferent
1-81-84-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop
Outputdifferent
PDCA Log, Experiment Plan, Learning Outcome, Standard ChangeForecast Percentiles, Throughput Dataset, Risk CommunicationKaizen Charter, Waste List, Improvement Experiments, Standard Work Update
Tagsno overlap
Continuous improvementLeanExperiments
ForecastingFlowDelivery
LeanContinuous improvementOperations
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
A3 Problem-Solving workspace showing the question, observations, and next decision.
Operations
A3 Problem Solving
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk