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Criterion
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
Paper illustration for NoEstimates.
Agile
NoEstimates
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.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.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
MediumMediumMediumHigh
Timedifferent
15-45 minlaufendMultiple workshops over several weeks30-90 min Setup, danach laufend
Participantsdifferent
1-82-122-81-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
PERT Estimate, Expected Value, Risk NotesThroughput Data, Flow Forecast, Slicing RulesHooked loop, Trigger map, Reward design, Ethics checkForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationUncertaintyRisk
EstimationForecastingFlow
GrowthBehaviorRetention
ForecastingFlowDelivery
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