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Criterion
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration for Planning Poker.
Agile
Planning Poker
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
A single opinion rarely holds up for planning when the future is genuinely uncertain. It separates options, evaluation criteria, and open risks. The result is captured as an Estimate Range, Assumption Log, and Expert Consensus Notes.When estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.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 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
HighLowMediumHigh
Timedifferent
1-4 h or multiple rounds2-5 min je Item30-90 min1-4 Wochen
Participantsdifferent
4-12 Experten3-93-126-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
Estimate Range, Assumption Log, Expert Consensus NotesRelative Estimates, Assumption Notes, Split CandidatesAffinity Size Map, Grouped Estimates, Unclear ItemsExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
EstimationExpertsForecasting
EstimationAgileRelative sizingTeam
EstimationBacklogRelative sizing
ForecastingExpertsDecisionStrategy
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