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| Criterion |  Systems Thinking Causal Loop Diagram |  Engineering Kanban |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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. | 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. | 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. |
Complexitydifferent | Medium | Medium | High |
Timedifferent | 1-3 h | Ongoing | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-8 | 2-12 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Causal Loop Diagram, Feedback Notes, Leverage Points | Kanban board, WIP policies, Flow metrics | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FeedbackSystems thinkingCausalityDynamics | FlowVisual managementDelivery | ForecastingFlowDelivery |
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