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Criterion
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 of Shape Up with its method-specific working model.
Delivery
Shape Up
Paper illustration for ALPEN Method
Operations
ALPEN Method
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.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.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.
Complexitydifferent
HighMediumMediumLow
Timedifferent
30-90 min Setup, danach laufendOngoing6 Wochen Cycle + 2 Wochen Cool-Down10-20 min daily
Participantsdifferent
1-82-122-4 pro Pitch1
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationKanban board, WIP policies, Flow metricsPitches, Bet-table decisions, Hill charts, Cooldown outcomesDaily Plan, Time Estimates, Review Notes
Tagsno overlap
ForecastingFlowDelivery
FlowVisual managementDelivery
PlanningDeliveryAutonomy
PlanningTime managementProductivityOperations
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