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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Paper illustration for Current Reality Tree
Systems Thinking
Current Reality Tree
Causal Loop Diagram workspace showing the question, observations, and next decision.
Systems Thinking
Causal Loop Diagram
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.For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput.A Current Reality Tree condenses many symptoms into a few causal chains. The method makes visible which core problems drive several negative effects at once.A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations.
Complexitydifferent
HighMediumHighMedium
Timedifferent
30-90 min Setup, danach laufend1-3 h2-6 h1-3 h
Participantsdifferent
1-83-83-82-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationBottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresCurrent Reality Tree, Core Problems, Intervention IdeasCausal Loop Diagram, Feedback Notes, Leverage Points
Tagsno overlap
ForecastingFlowDelivery
FlowMeasurementConstraints
Systems thinkingRoot causeConstraintsCausality
FeedbackSystems thinkingCausalityDynamics
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