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Criterion
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption 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.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.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
MediumMediumLowHigh
Timedifferent
10-30 min je Itemlaufend1-2 h30-90 min Setup, danach laufend
Participantsdifferent
1-82-122-81-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Three-Point Estimate, Risk Range, Assumption NotesThroughput Data, Flow Forecast, Slicing RulesDIBB document, Belief list, Bet list, Learning reportForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationUncertaintyForecasting
EstimationForecastingFlow
StrategyDecisionAssumptionsHypothesis
ForecastingFlowDelivery
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