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Criterion
Paper illustration of Leverage Points with its method-specific working model.
Systems Thinking
Leverage Points
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Context Map workspace showing the question, observations, and next decision.
Domain Modeling
Context Map
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Purposedifferent
Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy.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.When several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighHighMediumMedium
Timedifferent
Half day1-4 Wochen1-3 h45-60 min
Participantsdifferent
3-121-62-82-8
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Leverage Map, Action StrategyExperiment results, Decision log, Learning summaryContext Map, Integration Patterns, Boundary NotesAssumption map, Test backlog, Risk ranking
Tagsno overlap
Systems thinkingChangeStrategy
ExperimentsGrowthAnalyticsValidation
Domain-Driven DesignBoundariesStrategy
AssumptionsRiskExperimentsValidation
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