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| Criterion |  Knowledge Modeling PARA Method |  Delivery Monte Carlo Forecasting |  Operations ALPEN Method |  Agile NoEstimates |
|---|---|---|---|---|
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. | 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. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | 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 | Medium | High | Low | Medium |
Timedifferent | 1-3 h Setup, laufend | 30-90 min Setup, danach laufend | 10-20 min daily | laufend |
Participantsdifferent | 1 | 1-8 | 1 | 2-12 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Forecast Percentiles, Throughput Dataset, Risk Communication | Daily Plan, Time Estimates, Review Notes | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | KnowledgeProductivityOrganization | ForecastingFlowDelivery | PlanningTime managementProductivityOperations | EstimationForecastingFlow |