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Criterion
Paper illustration for Contextual Inquiry.
UX Research
Contextual Inquiry
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
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 process that keeps people busy but creates little value, the method exposes waste. It directs attention to unnecessary movement, waiting times, rework, and overdelivery.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.
Complexitydifferent
MediumHighLowMedium
Timedifferent
1-3 Wochen30-90 min Setup, danach laufend45-120 minOngoing
Participantsdifferent
4-12 Beobachtungen1-82-82-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Field Notes, Workflow Insights, Pain PointsForecast Percentiles, Throughput Dataset, Risk CommunicationWaste Map, Prioritized Waste, Improvement BacklogKanban board, WIP policies, Flow metrics
Tagsno overlap
UX researchObservationContext
ForecastingFlowDelivery
WasteLeanProcess improvement
FlowVisual managementDelivery
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