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Criterion
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Paper illustration for ALPEN Method
Operations
ALPEN Method
Purposedifferent
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.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.When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable.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.
Complexitydifferent
MediumHighMediumLow
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-Down30-90 min Setup, danach laufendOngoing10-20 min daily
Participantsdifferent
2-4 pro Pitch1-82-121
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesForecast Percentiles, Throughput Dataset, Risk CommunicationKanban board, WIP policies, Flow metricsDaily Plan, Time Estimates, Review Notes
Tagsno overlap
PlanningDeliveryAutonomy
ForecastingFlowDelivery
FlowVisual managementDelivery
PlanningTime managementProductivityOperations
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