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Criterion
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.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.Shape Up helps clarify scope, sequence, and delivery flow. It makes work boundaries and decisions explicit and captures results as pitches, bet-table decisions, and hill charts.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
MediumMediumMediumHigh
Timedifferent
Ongoing1-3 h6 Wochen Cycle + 2 Wochen Cool-Down30-90 min Setup, danach laufend
Participantsdifferent
2-124-102-4 pro Pitch1-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Kanban board, WIP policies, Flow metricsCurrent-state map, Future-state map, Bottleneck listPitches, Bet-table decisions, Hill charts, Cooldown outcomesForecast Percentiles, Throughput Dataset, Risk Communication
Tags1 shared
FlowVisual managementDelivery
LeanFlowWasteDelivery
PlanningDeliveryAutonomy
ForecastingFlowDelivery
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