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| Criterion |  Agile NoEstimates |  UX Research HEART Framework |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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 observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | 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 | Medium | Medium | High |
Timedifferent | laufend | 120 min initial, dann laufend | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-6 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | HEART-GSM Table, Dashboard | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | MetricsUX researchMeasurementSatisfaction | ForecastingFlowDelivery |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
