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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
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.A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes.
Complexitydifferent
HighMediumMedium
Timedifferent
30-90 min Setup, danach laufend30-60 min10-30 min je Item
Participantsdifferent
1-82-61-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationSmaller Stories, Acceptance Criteria, Split RationaleThree-Point Estimate, Risk Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
BacklogIterationDelivery
EstimationUncertaintyForecasting
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