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| Criterion |  Delivery Monte Carlo Forecasting |  Systems Thinking Current Reality Tree |  Systems Thinking Causal Loop Diagram |  Operations Bottleneck Analysis |
|---|---|---|---|---|
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. | 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. | 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. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 2-6 h | 1-3 h | 1-3 h |
Participantsdifferent | 1-8 | 3-8 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current Reality Tree, Core Problems, Intervention Ideas | Causal Loop Diagram, Feedback Notes, Leverage Points | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures |
Tagsno overlap | ForecastingFlowDelivery | Systems thinkingRoot causeConstraintsCausality | FeedbackSystems thinkingCausalityDynamics | FlowMeasurementConstraints |