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| Criterion |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |  Growth Flywheel |
|---|---|---|---|
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. | When delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 60-120 min |
Participantsdifferent | 1-8 | 4-10 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog |
Tagsno overlap | ForecastingFlowDelivery | LeanFlowWasteDelivery | GrowthRetentionConversion |
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