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Criterion
Paper illustration for Contextual Inquiry.
UX Research
Contextual Inquiry
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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.When delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible.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
MediumMediumHigh
Timedifferent
1-3 Wochen1-3 h30-90 min Setup, danach laufend
Participantsdifferent
4-12 Beobachtungen4-101-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + async
Outputdifferent
Field Notes, Workflow Insights, Pain PointsCurrent-state map, Future-state map, Bottleneck listForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
UX researchObservationContext
LeanFlowWasteDelivery
ForecastingFlowDelivery
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