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 Planning Poker.
Agile
Planning Poker
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.
Complexitydifferent
MediumLowLowHigh
Timedifferent
30-90 min2-5 min je Item1-2 h1-4 Wochen
Participantsdifferent
3-123-92-86-30 Experten
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsRelative Estimates, Assumption Notes, Split CandidatesDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
EstimationBacklogRelative sizing
EstimationAgileRelative sizingTeam
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
Add more methods