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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Bucket System.
Agile
Bucket System
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.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 delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible.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
MediumMediumMediumHigh
Timedifferent
30-90 min30-90 min1-3 h30-90 min Setup, danach laufend
Participantsdifferent
3-123-124-101-8
Formatdifferent
WorkshopWorkshopWorkshopWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsBucketed Backlog, Relative Estimates, Split CandidatesCurrent-state map, Future-state map, Bottleneck listForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationBacklogRelative sizing
EstimationBacklogRelative sizing
LeanFlowWasteDelivery
ForecastingFlowDelivery
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