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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration for NoEstimates.
Agile
NoEstimates
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.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
MediumHighMediumHigh
Timedifferent
30-90 min1-4 h or multiple roundslaufend1-4 Wochen
Participantsdifferent
1-64-12 Experten2-126-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListEstimate Range, Assumption Log, Expert Consensus NotesThroughput Data, Flow Forecast, Slicing RulesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
DecisionTreeOptions
EstimationExpertsForecasting
EstimationForecastingFlow
ForecastingExpertsDecisionStrategy
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