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| Criterion |  UX Research Contextual Inquiry |  Delivery Monte Carlo Forecasting |  Operations Bottleneck Analysis |
|---|---|---|---|
Purposedifferent | When work processes are known only from accounts and the real context stays hidden, Contextual Inquiry makes behavior at the workplace visible. Observation and follow-up questions together show how people actually work, get interrupted, and improvise. | 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. | For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. |
Complexitydifferent | Medium | High | Medium |
Timedifferent | 1-3 Wochen | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 4-12 Beobachtungen | 1-8 | 3-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Field Notes, Workflow Insights, Pain Points | Forecast Percentiles, Throughput Dataset, Risk Communication | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures |
Tagsno overlap | UX researchObservationContext | ForecastingFlowDelivery | FlowMeasurementConstraints |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
