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| Criterion | ![]() Agile NoEstimates | ![]() Agile Bucket System | ![]() Operations Bottleneck Analysis | ![]() Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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 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. | For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. | 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 | laufend | 30-90 min | 1-3 h | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-12 | 3-8 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Bucketed Backlog, Relative Estimates, Split Candidates | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | EstimationBacklogRelative sizing | FlowMeasurementConstraints | ForecastingFlowDelivery |



