View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making DACI |  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 cross-functional decisions, responsibilities quickly blur between approval, influence, and execution. DACI arranges these roles so decision pressure, contribution, and information stay cleanly separated. | 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 | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 30-60 min | Ongoing |
Participantsdifferent | 1-8 | 2-10 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | DACI Matrix, Decision Owner, Decision Log | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | DecisionRolesGovernanceAlignment | FlowVisual managementDelivery |
Often compared together
Methods with strong topical overlap with the current selection, not yet in the comparison.
