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| Criterion |  Agile NoEstimates |  Growth Flywheel |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. | 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 | laufend | 60-120 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-8 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | GrowthRetentionConversion | ForecastingFlowDelivery |
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