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Criterion
Paper illustration for Bucket System.
Agile
Bucket System
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets.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
MediumLowHigh
Timedifferent
30-90 min5-20 min30-90 min Setup, danach laufend
Participantsdifferent
3-123-201-8
Formatdifferent
WorkshopWorkshopWorkshop + async
Outputdifferent
Bucketed Backlog, Relative Estimates, Split CandidatesEffort Heatmap, Risk Signals, Discussion TargetsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationBacklogRelative sizing
EstimationEffortRisk
ForecastingFlowDelivery
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