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Criterion
Paper radar with five axes, two current and target profiles, and evidence cards beside each dimension.
Decision Making
Radar
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
When capabilities, maturity levels, or market positions need to be compared across several dimensions, overview is easily lost. Radar brings different characteristics into a shared picture and shows patterns faster than tables do.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.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.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
MediumMediumLowHigh
Timedifferent
1-2 h30-90 min1-2 h1-4 Wochen
Participantsdifferent
2-101-62-86-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Radar Map, Capability Scores, Action AreasDecision Tree, Option Map, Assumption ListDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
AssessmentPortfolioCapability
DecisionTreeOptions
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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