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| Criterion |  Delivery Monte Carlo Forecasting |  Growth Hooked Model |  Agile Ideal Days |
|---|---|---|---|
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. | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. |
Complexitydifferent | High | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | Multiple workshops over several weeks | 15-60 min |
Participantsdifferent | 1-8 | 2-8 | 2-9 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Hooked loop, Trigger map, Reward design, Ethics check | Ideal Day Estimates, Assumption Notes, Capacity Caveats |
Tagsno overlap | ForecastingFlowDelivery | GrowthBehaviorRetention | EstimationEffortAgile |
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