methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Bucket System.
Agile
Bucket System
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.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
MediumMediumHigh
Timedifferent
30-90 min30-90 min30-90 min Setup, danach laufend
Participantsdifferent
3-123-121-8
Formatdifferent
WorkshopWorkshopWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsBucketed Backlog, Relative Estimates, Split CandidatesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationBacklogRelative sizing
EstimationBacklogRelative sizing
ForecastingFlowDelivery
Add more methods

Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.