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| Criterion |  Growth Hooked Model |  Delivery Monte Carlo Forecasting |  Facilitation Dot Estimation |
|---|---|---|---|
Purposedifferent | 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. | 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 size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. |
Complexitydifferent | Medium | High | Low |
Timedifferent | Multiple workshops over several weeks | 30-90 min Setup, danach laufend | 5-20 min |
Participantsdifferent | 2-8 | 1-8 | 3-20 |
Formatdifferent | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Forecast Percentiles, Throughput Dataset, Risk Communication | Effort Heatmap, Risk Signals, Discussion Targets |
Tagsno overlap | GrowthBehaviorRetention | ForecastingFlowDelivery | EstimationEffortRisk |
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