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Criterion
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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 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.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.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
HighHighMediumHigh
Timedifferent
1-4 h or multiple rounds1-4 Wochenlaufend30-90 min Setup, danach laufend
Participantsdifferent
4-12 Experten6-30 Experten2-121-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Estimate Range, Assumption Log, Expert Consensus NotesExpert Forecast, Consensus Range, Assumption NotesThroughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk Communication
Tags1 shared
EstimationExpertsForecasting
ForecastingExpertsDecisionStrategy
EstimationForecastingFlow
ForecastingFlowDelivery
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