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| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making Option Framing |  Agile NoEstimates |  Engineering Kanban |
|---|---|---|---|---|
Purposedifferent | 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. | In early decisions, alternatives are often still vague, incomplete, or blended together. Option Framing brings every possibility into a comparable form and makes visible which variant actually fits the question. | 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. | 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 | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 45-120 min | laufend | Ongoing |
Participantsdifferent | 1-8 | 3-8 | 2-12 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Option Frames, Assumption Notes, Comparable Shortlist, Decision Inputs | Throughput Data, Flow Forecast, Slicing Rules | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | OptionsDecision framingStrategyComparison | EstimationForecastingFlow | FlowVisual managementDelivery |