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Criterion
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
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
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.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.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
LowMediumMediumHigh
Timedifferent
45-120 min2–4 h review as a planning range; preparation and evaluation additional1-3 h30-90 min Setup, danach laufend
Participantsdifferent
2-8Designers, developers as users, and facilitation4-101-8
Formatdifferent
WorkshopWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Waste Map, Prioritized Waste, Improvement BacklogPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsCurrent-state map, Future-state map, Bottleneck listForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
WasteLeanProcess improvement
ArchitectureEngineeringFeedbackValidationTasks
LeanFlowWasteDelivery
ForecastingFlowDelivery
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