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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
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.When content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations.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
LowLowHigh
Timedifferent
1-2 h20-45 min1-4 Wochen
Participantsdifferent
2-8Based on research question6-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportContent groups, Label set, IA hypothesesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
Information architectureNavigationStructure
ForecastingExpertsDecisionStrategy
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing