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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.
Complexitydifferent
MediumMediumHigh
Timedifferent
60-120 minlaufend30-90 min Setup, danach laufend
Participantsdifferent
3-82-121-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogThroughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
GrowthRetentionConversion
EstimationForecastingFlow
ForecastingFlowDelivery
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