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Criterion
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When there is uncertainty about the real course of a process, the method brings observation to the place where work happens. It combines perception, follow-up questions, and process knowledge so decisions rest on actual workflows instead of assumptions.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.
Complexitydifferent
LowMediumHigh
Timedifferent
30-120 minlaufend30-90 min Setup, danach laufend
Participantsdifferent
2-62-121-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Observation Notes, Improvement IdeasThroughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
LeanObservationProcessOperations
EstimationForecastingFlow
ForecastingFlowDelivery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
A3 Problem-Solving workspace showing the question, observations, and next decision.
Operations
A3 Problem Solving
Paper illustration for Kaizen Event.
Operations
Kaizen Event