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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
Process Mapping method illustration showing its working structure
Operations
Process Mapping
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.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.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.
Complexitydifferent
HighLowMedium
Timedifferent
30-90 min Setup, danach laufend20-45 min1-3 h
Participantsdifferent
1-83-123-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationLessons learned, Action items, Event summaryProcess Map, Handoff List, Improvement Backlog
Tagsno overlap
ForecastingFlowDelivery
LearningOperationsImprovement
ProcessOperationsImprovement
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Often compared together

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

Paper illustration for Theory of Constraints.
Operations
Theory of Constraints
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk
Paper illustration for Learning Review.
Operations
Learning Review