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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 Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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.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.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.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
MediumMediumHighLow
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-DownOngoing30-90 min Setup, danach laufend10-20 min daily
Participantsdifferent
2-4 pro Pitch2-121-81
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesKanban board, WIP policies, Flow metricsForecast Percentiles, Throughput Dataset, Risk CommunicationDaily Plan, Time Estimates, Review Notes
Tagsno overlap
PlanningDeliveryAutonomy
FlowVisual managementDelivery
ForecastingFlowDelivery
PlanningTime managementProductivityOperations
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