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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Story Splitting |  Agile Planning Poker |  Agile NoEstimates |
|---|---|---|---|---|
Purposedifferent | 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 a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify. | 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. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 30-60 min | 2-5 min je Item | laufend |
Participantsdifferent | 1-8 | 2-6 | 3-9 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Smaller Stories, Acceptance Criteria, Split Rationale | Relative Estimates, Assumption Notes, Split Candidates | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | ForecastingFlowDelivery | BacklogIterationDelivery | EstimationAgileRelative sizingTeam | EstimationForecastingFlow |