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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Purposedifferent
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.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.The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
30-90 min Setup, danach laufend60-120 minlaufendMultiple workshops over several weeks
Participantsdifferent
1-83-82-122-8
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationFlywheel Map, Friction Points, Growth Levers, Experiment BacklogThroughput Data, Flow Forecast, Slicing RulesHooked loop, Trigger map, Reward design, Ethics check
Tagsno overlap
ForecastingFlowDelivery
GrowthRetentionConversion
EstimationForecastingFlow
GrowthBehaviorRetention
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