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Criterion
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.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
LowHighLow
Timedifferent
45-90 min1-4 Wochen1-2 h
Participantsdifferent
3-121-62-8
Formatdifferent
WorkshopAsyncWorkshop + async
Outputdifferent
Force Field Map, Change Levers, Risk NotesExperiment results, Decision log, Learning summaryDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ChangeDecisionStrategy
ExperimentsGrowthAnalyticsValidation
StrategyDecisionAssumptionsHypothesis
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test