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Criterion
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for NoEstimates.
Agile
NoEstimates
A structured reflection surfaces what was liked, learned, lacked, and longed for. It is a conversation format and does not validate actions automatically.
Agile
4Ls Retrospective
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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 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 a sprint should not only be assessed but also learned from, it captures experience in clear learning categories. It records what worked, what's missing, and what should run differently next time.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
MediumMediumLowHigh
Timedifferent
10-30 min je Itemlaufend45–75 min30-90 min Setup, danach laufend
Participantsdifferent
1-82-12Team members involved1-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Three-Point Estimate, Risk Range, Assumption NotesThroughput Data, Flow Forecast, Slicing Rules4Ls Board, Learning Themes, Improvement ActionsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationUncertaintyForecasting
EstimationForecastingFlow
RetrospectiveLearningReflectionTeam
ForecastingFlowDelivery
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