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| Criterion |  Facilitation Dot Estimation |  Agile NoEstimates |  Architecture C4 Model |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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. | 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 | Low | Medium | Low | High |
Timedifferent | 5-20 min | laufend | 1-4 h | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-20 | 2-12 | 1-5 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Effort Heatmap, Risk Signals, Discussion Targets | Throughput Data, Flow Forecast, Slicing Rules | Context Diagram, Container Diagram, Component Diagram | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationEffortRisk | EstimationForecastingFlow | ArchitectureCommunicationVisualization | ForecastingFlowDelivery |