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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
Paper illustration for Bucket System.
Agile
Bucket System
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.When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
30-90 min Setup, danach laufend30-60 min10-30 min je Item30-90 min
Participantsdifferent
1-82-61-83-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationSmaller Stories, Acceptance Criteria, Split RationaleThree-Point Estimate, Risk Range, Assumption NotesBucketed Backlog, Relative Estimates, Split Candidates
Tagsno overlap
ForecastingFlowDelivery
BacklogIterationDelivery
EstimationUncertaintyForecasting
EstimationBacklogRelative sizing
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