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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
LowHighMediumLow
Timedifferent
1-2 hHalf day1-2 Wochen pro Iteration30-60 min
Participantsdifferent
2-83-122-61-5
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportLeverage Map, Action StrategyPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
Systems thinkingChangeStrategy
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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