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| Criterion |  Operations Bottleneck Analysis |  Product Discovery Dual-Track Agile |  Agile NoEstimates |  Engineering Kanban |
|---|---|---|---|---|
Purposedifferent | 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. | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-3 h | Laufend, Wochen bis Monate | laufend | Ongoing |
Participantsdifferent | 3-8 | 4-10 | 2-12 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Throughput Data, Flow Forecast, Slicing Rules | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | FlowMeasurementConstraints | AgileDiscoveryDelivery | EstimationForecastingFlow | FlowVisual managementDelivery |