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Criterion
Paper illustration for Failure Scenario Analysis.
Engineering
Failure Scenario Analysis
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage.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.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.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
MediumMediumLowHigh
Timedifferent
1-3 h1-3 h45-120 min30-90 min Setup, danach laufend
Participantsdifferent
3-84-102-81-8
Formatdifferent
WorkshopWorkshopWorkshopWorkshop + async
Outputdifferent
Failure Scenarios, Risk Notes, Control Gaps, Test and Response ActionsCurrent-state map, Future-state map, Bottleneck listWaste Map, Prioritized Waste, Improvement BacklogForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
FailureResilienceRisk
LeanFlowWasteDelivery
WasteLeanProcess improvement
ForecastingFlowDelivery
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