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| Criterion |  Agile Planning Poker |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Agile Ideal Days |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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. | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. |
Complexitydifferent | Low | Medium | High | Low |
Timedifferent | 2-5 min je Item | laufend | 30-90 min Setup, danach laufend | 15-60 min |
Participantsdifferent | 3-9 | 2-12 | 1-8 | 2-9 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Relative Estimates, Assumption Notes, Split Candidates | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | Ideal Day Estimates, Assumption Notes, Capacity Caveats |
Tagsno overlap | EstimationAgileRelative sizingTeam | EstimationForecastingFlow | ForecastingFlowDelivery | EstimationEffortAgile |