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| Criterion |  Delivery Monte Carlo Forecasting |  Growth North Star Metric |  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 product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | 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 | 1-2 h | 60-120 min |
Participantsdifferent | 1-8 | 3-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | North Star metric, Input metric tree, Measurement cadence | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog |
Tagsno overlap | ForecastingFlowDelivery | GrowthMetricsAlignmentRetention | GrowthRetentionConversion |
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