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Criterion
Paper illustration for Theory of Constraints.
Operations
Theory of Constraints
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Paper illustration of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
Purposedifferent
For a system that does not get faster despite effort, the method directs attention to the bottleneck. It concentrates improvement on the point that actually limits throughput.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.When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable.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.
Complexitydifferent
HighHighMediumLow
Timedifferent
2-4 h Analyse, laufend30-90 min Setup, danach laufendOngoing20-45 min
Participantsdifferent
3-121-82-123-12
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Constraint Map, Improvement Plan, Flow MetricsForecast Percentiles, Throughput Dataset, Risk CommunicationKanban board, WIP policies, Flow metricsLessons learned, Action items, Event summary
Tagsno overlap
OperationsConstraintsFlowImprovement
ForecastingFlowDelivery
FlowVisual managementDelivery
LearningOperationsImprovement
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