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| Criterion |  Engineering Kanban |  Agile NoEstimates |  Delivery Shape Up |  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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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 | Medium | Medium | Medium | High |
Timedifferent | Ongoing | laufend | 6 Wochen Cycle + 2 Wochen Cool-Down | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 2-12 | 2-4 pro Pitch | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Throughput Data, Flow Forecast, Slicing Rules | Pitches, Bet-table decisions, Hill charts, Cooldown outcomes | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FlowVisual managementDelivery | EstimationForecastingFlow | PlanningDeliveryAutonomy | ForecastingFlowDelivery |