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Criterion
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.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.
Complexitydifferent
MediumHighLowLow
Timedifferent
15-45 min1-4 Wochen30-60 min1-2 h
Participantsdifferent
1-86-30 Experten1-52-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
PERT Estimate, Expected Value, Risk NotesExpert Forecast, Consensus Range, Assumption NotesCompleted Experiment Canvas, Success MetricDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
EstimationUncertaintyRisk
ForecastingExpertsDecisionStrategy
ExperimentsValidationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
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