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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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.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.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.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
MediumHighLowLow
Timedifferent
60-120 min1-4 Wochen30-60 min1-2 h
Participantsdifferent
3-86-30 Experten1-52-8
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogExpert Forecast, Consensus Range, Assumption NotesCompleted Experiment Canvas, Success MetricDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
GrowthRetentionConversion
ForecastingExpertsDecisionStrategy
ExperimentsValidationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
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