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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Fault Isolation.
Engineering
Fault Isolation
Paper illustration for Hypothesis-Driven Troubleshooting.
Engineering
Hypothesis-Driven Troubleshooting
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 technical failures, the visible symptom often gets mixed up with the actual cause. Fault Isolation narrows the fault space and progressively reduces which part of the system is truly affected.When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable.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 Wochen30-180 min30-240 min1-2 h
Participantsdifferent
6-30 Experten1-61-62-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesFault Isolation Map, Test Log, Excluded Hypotheses, Narrowed Fault AreaHypothesis Log, Test Plan, Evidence Notes, Diagnosis SummaryDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
TroubleshootingDiagnosisEngineering
TroubleshootingProblem solvingDiagnosis
StrategyDecisionAssumptionsHypothesis
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