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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Process Mapping method illustration showing its working structure
Operations
Process Mapping
Paper illustration of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk
Purposedifferent
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.With a confusing workflow that has many handoffs, the method makes the actual process visible. It shows where work is passed on, delayed, or duplicated, so improvement targets the right spots.After missions or project phases with unclear outcomes, the method makes visible what actually happened and what can be learned from it. It separates course, effect, and causes so experience turns into solid improvement.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.
Complexitydifferent
HighMediumLowLow
Timedifferent
30-90 min Setup, danach laufend1-3 h20-45 min30-120 min
Participantsdifferent
1-83-103-122-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationProcess Map, Handoff List, Improvement BacklogLessons learned, Action items, Event summaryObservation Notes, Improvement Ideas
Tagsno overlap
ForecastingFlowDelivery
ProcessOperationsImprovement
LearningOperationsImprovement
LeanObservationProcessOperations
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