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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Blameless Postmortem workspace showing the question, observations, and next decision.
DevOps
Blameless Postmortem
Incident Command workspace showing the question, observations, and next decision.
DevOps
Incident Command
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.After an incident with damage or a near miss, the method creates a sober field for learning without assigning blame. It directs attention to the course of events, conditions, and effective countermeasures.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.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
HighMediumMediumLow
Timedifferent
1-4 Wochen30-90 minAs needed1-2 h
Participantsdifferent
6-30 Experten3-124-152-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesPostmortem Doc, Action Items, TimelineIncident Log, Action Tracker, Stakeholder UpdatesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
Site Reliability EngineeringIncidentLearningReliability
IncidentOperationsReliability
StrategyDecisionAssumptionsHypothesis
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