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Criterion
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Purposedifferent
When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets.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.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
LowHighMedium
Timedifferent
5-20 min30-90 min Setup, danach laufendMultiple workshops over several weeks
Participantsdifferent
3-201-82-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Effort Heatmap, Risk Signals, Discussion TargetsForecast Percentiles, Throughput Dataset, Risk CommunicationHooked loop, Trigger map, Reward design, Ethics check
Tagsno overlap
EstimationEffortRisk
ForecastingFlowDelivery
GrowthBehaviorRetention
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