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Criterion
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes.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.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
15-45 minMultiple workshops over several weeks30-90 min Setup, danach laufend
Participantsdifferent
1-82-81-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
PERT Estimate, Expected Value, Risk NotesHooked loop, Trigger map, Reward design, Ethics checkForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationUncertaintyRisk
GrowthBehaviorRetention
ForecastingFlowDelivery
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Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation