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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
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for NoEstimates.
Agile
NoEstimates
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 delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible.When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.
Complexitydifferent
MediumHighMediumMedium
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-Down30-90 min Setup, danach laufend1-3 hlaufend
Participantsdifferent
2-4 pro Pitch1-84-102-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesForecast Percentiles, Throughput Dataset, Risk CommunicationCurrent-state map, Future-state map, Bottleneck listThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
PlanningDeliveryAutonomy
ForecastingFlowDelivery
LeanFlowWasteDelivery
EstimationForecastingFlow
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