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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree Analysis
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.For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie.
Complexitydifferent
HighHighMediumMedium
Timedifferent
1-4 Wochen2-6 h30-90 min1-3 h
Participantsdifferent
6-30 Experten3-101-62-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesEvent Timeline, Causal Factor Chart, Cause List, Corrective ActionsDecision Tree, Option Map, Assumption ListCause Tree, Evidence Notes, Countermeasures
Tagsno overlap
ForecastingExpertsDecisionStrategy
CausalityIncidentRoot causeTimeline
DecisionTreeOptions
Root causeTreeIncidentQuality
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