View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Operations DMAIC |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Engineering Kanban |
|---|---|---|---|---|
Purposedifferent | For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together. | 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. | 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. | 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 | High | Medium |
Timedifferent | 2-12 Wochen | laufend | 30-90 min Setup, danach laufend | Ongoing |
Participantsdifferent | 3-10 | 2-12 | 1-8 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Project Charter, Measurement Plan, Cause Analysis, Control Plan | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | Continuous improvementQualityProcess improvement | EstimationForecastingFlow | ForecastingFlowDelivery | FlowVisual managementDelivery |