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| Criterion |  Agile Bucket System |  Engineering Kanban |  Decision Making Delphi Method |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | 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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 | High | High |
Timedifferent | 30-90 min | Ongoing | 1-4 Wochen | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-12 | 2-12 | 6-30 Experten | 1-8 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop + async |
Outputdifferent | Bucketed Backlog, Relative Estimates, Split Candidates | Kanban board, WIP policies, Flow metrics | Expert Forecast, Consensus Range, Assumption Notes | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationBacklogRelative sizing | FlowVisual managementDelivery | ForecastingExpertsDecisionStrategy | ForecastingFlowDelivery |