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| Criterion |  Delivery Monte Carlo Forecasting |  Architecture C4 Model |  Agile NoEstimates |
|---|---|---|---|
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 C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | 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. |
Complexitydifferent | High | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-4 h | laufend |
Participantsdifferent | 1-8 | 1-5 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Context Diagram, Container Diagram, Component Diagram | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | ForecastingFlowDelivery | ArchitectureCommunicationVisualization | EstimationForecastingFlow |
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