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| Criterion |  UX Research Diary Study |  Engineering Kanban |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |
|---|---|---|---|---|
Purposedifferent | When experiences build up over days or weeks and a single session cannot capture them, Diary Study records the course of everyday life. Recurring triggers, moods, and habits become visible this way, beyond the sharpness of memory. | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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. | 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 | Medium | High | Medium |
Timedifferent | 1-4 Wochen | Ongoing | 30-90 min Setup, danach laufend | laufend |
Participantsdifferent | 5-20 | 2-12 | 1-8 | 2-12 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Diary Entries, Longitudinal Patterns, Experience Timeline | Kanban board, WIP policies, Flow metrics | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | UX researchTrackingBehavior | FlowVisual managementDelivery | ForecastingFlowDelivery | EstimationForecastingFlow |