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| Criterion |  Engineering Goal Question Metric |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  UX Research HEART Framework |
|---|---|---|---|---|
Purposedifferent | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | 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. | 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. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 90-180 min | laufend | 30-90 min Setup, danach laufend | 120 min initial, dann laufend |
Participantsdifferent | 3-6 | 2-12 | 1-8 | 3-6 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | GQM Table, Metric Profiles | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | HEART-GSM Table, Dashboard |
Tagsno overlap | MetricsMeasurementEngineeringAlignment | EstimationForecastingFlow | ForecastingFlowDelivery | MetricsUX researchMeasurementSatisfaction |