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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Game Day workspace showing the question, observations, and next decision.
DevOps
Game Day
A3 Problem-Solving workspace showing the question, observations, and next decision.
Operations
A3 Problem Solving
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
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.In preparing for rare incidents, the method tests response capability under controlled conditions. It shows where assumptions about stability, roles, and recovery are too optimistic.For a complex deviation with several people involved, the method bundles problem, analysis, and decision onto one page. It creates a shared working space where causes, countermeasures, and follow-up fit 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
HighHighMediumLow
Timedifferent
1-4 WochenHalber Tag45-90 min1-2 h
Participantsdifferent
6-30 Experten5-202-52-8
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesSimulation Notes, Gaps List, Updated RunbooksA3 Report, Action Plan, Root Cause AnalysisDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
ResilienceOperationsIncident
LeanProblem solvingCoachingOperations
StrategyDecisionAssumptionsHypothesis
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