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Criterion
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
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
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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.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.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
MediumMediumLowHigh
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-DownOngoing10-20 min daily30-90 min Setup, danach laufend
Participantsdifferent
2-4 pro Pitch2-1211-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesKanban board, WIP policies, Flow metricsDaily Plan, Time Estimates, Review NotesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
PlanningDeliveryAutonomy
FlowVisual managementDelivery
PlanningTime managementProductivityOperations
ForecastingFlowDelivery
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