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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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
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.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
HighHighMediumHigh
Timedifferent
30-90 min Setup, danach laufend1-4 h or multiple roundslaufend1-4 Wochen
Participantsdifferent
1-84-12 Experten2-126-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationEstimate Range, Assumption Log, Expert Consensus NotesThroughput Data, Flow Forecast, Slicing RulesExpert Forecast, Consensus Range, Assumption Notes
Tags1 shared
ForecastingFlowDelivery
EstimationExpertsForecasting
EstimationForecastingFlow
ForecastingExpertsDecisionStrategy
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