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Criterion
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 Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes.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
MediumMediumMediumHigh
Timedifferent
Ongoing6 Wochen Cycle + 2 Wochen Cool-Down10-30 min je Item30-90 min Setup, danach laufend
Participantsdifferent
2-122-4 pro Pitch1-81-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Kanban board, WIP policies, Flow metricsPitches, Bet-table decisions, Hill charts, Cooldown outcomesThree-Point Estimate, Risk Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
FlowVisual managementDelivery
PlanningDeliveryAutonomy
EstimationUncertaintyForecasting
ForecastingFlowDelivery
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