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| Criterion |  Agile NoEstimates |  Agile Planning Poker |  Product Discovery Dual-Track Agile |  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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions. | 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. | 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 | Low | Medium | High |
Timedifferent | laufend | 2-5 min je Item | Laufend, Wochen bis Monate | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-9 | 4-10 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Relative Estimates, Assumption Notes, Split Candidates | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | EstimationAgileRelative sizingTeam | AgileDiscoveryDelivery | ForecastingFlowDelivery |