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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Paper illustration for ALPEN Method
Operations
ALPEN Method
Paper illustration for NoEstimates.
Agile
NoEstimates
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.Shape Up helps clarify scope, sequence, and delivery flow. It makes work boundaries and decisions explicit and captures results as pitches, bet-table decisions, and hill charts.With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time.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.
Complexitydifferent
HighMediumLowMedium
Timedifferent
30-90 min Setup, danach laufend6 Wochen Cycle + 2 Wochen Cool-Down10-20 min dailylaufend
Participantsdifferent
1-82-4 pro Pitch12-12
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationPitches, Bet-table decisions, Hill charts, Cooldown outcomesDaily Plan, Time Estimates, Review NotesThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
ForecastingFlowDelivery
PlanningDeliveryAutonomy
PlanningTime managementProductivityOperations
EstimationForecastingFlow
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