methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Paper illustration for Waste Analysis.
Operations
Waste Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify.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.For a process that keeps people busy but creates little value, the method exposes waste. It directs attention to unnecessary movement, waiting times, rework, and overdelivery.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
MediumMediumLowHigh
Timedifferent
30-60 minOngoing45-120 min30-90 min Setup, danach laufend
Participantsdifferent
2-62-122-81-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Smaller Stories, Acceptance Criteria, Split RationaleKanban board, WIP policies, Flow metricsWaste Map, Prioritized Waste, Improvement BacklogForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
BacklogIterationDelivery
FlowVisual managementDelivery
WasteLeanProcess improvement
ForecastingFlowDelivery
Add more methods