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Criterion
Paper illustration of the Lightning Decision Jam working structure.
Facilitation
Decision Jam
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When a decision is stuck, Decision Jam loosens the knot through structured separation of problem, idea, and selection. The format creates movement without jumping prematurely at the first seemingly elegant answer.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.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.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
LowHighHighLow
Timedifferent
60-90 min30-90 min Setup, danach laufend1-4 Wochen1-2 h
Participantsdifferent
4-101-86-30 Experten2-8
Formatdifferent
WorkshopWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Problem Cluster, Prioritized Challenge, ExperimentForecast Percentiles, Throughput Dataset, Risk CommunicationExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
FacilitationDecisionProblem solvingWorkshop
ForecastingFlowDelivery
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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