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Criterion
ChatOps workspace showing the question, observations, and next decision.
DevOps
ChatOps
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
For operational work in a distributed team, the method links communication with direct system control. It records decisions right where the signal, the context, and the execution come together.A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation.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.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
MediumHighHighLow
Timedifferent
Ongoing2-4 h1-4 Wochen1-2 h
Participantsdifferent
2-203-86-30 Experten2-8
Formatdifferent
Workshop + asyncWorkshopAsyncWorkshop + async
Outputdifferent
Chat Transcript, Action Log, AutomationsFuture Reality Tree, Negative Branches, Assumption List, Improved InjectionsExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
CollaborationEngineeringIncident
Theory of ConstraintsSystems thinkingChange
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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