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| Criterion |  Engineering Kanban |  Product Discovery Dual-Track Agile |  Agile Story Points |  Agile NoEstimates |
|---|---|---|---|---|
Purposedifferent | 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 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 teams want to rate complexity rather than hours, it creates a shared, relative scale. It sorts work by value, risk, and delivery ability. The result is captured as Point Estimates, Reference Stories, and Velocity Data. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Ongoing | Laufend, Wochen bis Monate | laufend, 1-5 min je Item | laufend |
Participantsdifferent | 2-12 | 4-10 | 3-9 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Point Estimates, Reference Stories, Velocity Data | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | FlowVisual managementDelivery | AgileDiscoveryDelivery | EstimationAgileMeasurement | EstimationForecastingFlow |