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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for ALPEN Method
Operations
ALPEN Method
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
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.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.With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time.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.
Complexitydifferent
LowMediumLowHigh
Timedifferent
1-2 h30-90 min10-20 min daily1-4 Wochen
Participantsdifferent
2-81-616-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportDecision Tree, Option Map, Assumption ListDaily Plan, Time Estimates, Review NotesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
DecisionTreeOptions
PlanningTime managementProductivityOperations
ForecastingExpertsDecisionStrategy
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