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| Criterion |  Knowledge Modeling PARA Method |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Decision Making Three-Point Estimation |
|---|---|---|---|---|
Purposedifferent | The PARA Method organizes knowledge into Projects, Areas, Resources, and Archives. It creates order when digital notes, files, and tasks no longer cleanly fit current work. | 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. | 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. | A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 1-3 h Setup, laufend | laufend | 30-90 min Setup, danach laufend | 10-30 min je Item |
Participantsdifferent | 1 | 2-12 | 1-8 | 1-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | Three-Point Estimate, Risk Range, Assumption Notes |
Tagsno overlap | KnowledgeProductivityOrganization | EstimationForecastingFlow | ForecastingFlowDelivery | EstimationUncertaintyForecasting |