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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Incident Command workspace showing the question, observations, and next decision.
DevOps
Incident Command
Game Day workspace showing the question, observations, and next decision.
DevOps
Game Day
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.During an acute incident with several people involved, the method creates a clear leadership and communication structure. It reduces chaos when fast coordination and clean situational awareness are both needed at once.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.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
HighMediumHighLow
Timedifferent
1-4 WochenAs neededHalber Tag1-2 h
Participantsdifferent
6-30 Experten4-155-202-8
Formatdifferent
AsyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesIncident Log, Action Tracker, Stakeholder UpdatesSimulation Notes, Gaps List, Updated RunbooksDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
IncidentOperationsReliability
ResilienceOperationsIncident
StrategyDecisionAssumptionsHypothesis
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