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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration of Leverage Points with its method-specific working model.
Systems Thinking
Leverage Points
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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.
Complexitydifferent
MediumHighMediumHigh
Timedifferent
60-120 minHalf day1-2 Wochen pro Iteration1-4 Wochen
Participantsdifferent
3-83-122-61-6
Formatdifferent
WorkshopWorkshopWorkshop + asyncAsync
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogLeverage Map, Action StrategyPrioritized Assumption List, Test Plan, Results ReportExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthRetentionConversion
Systems thinkingChangeStrategy
ExperimentsValidationDiscoveryAssumptions
ExperimentsGrowthAnalyticsValidation
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