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Criterion
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Purposedifferent
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.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.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 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.
Complexitydifferent
MediumHighMediumMedium
Timedifferent
laufend30-90 min Setup, danach laufend6 Wochen Cycle + 2 Wochen Cool-Down1-3 h
Participantsdifferent
2-121-82-4 pro Pitch4-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Throughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk CommunicationPitches, Bet-table decisions, Hill charts, Cooldown outcomesCurrent-state map, Future-state map, Bottleneck list
Tagsno overlap
EstimationForecastingFlow
ForecastingFlowDelivery
PlanningDeliveryAutonomy
LeanFlowWasteDelivery
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