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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
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Planning Poker.
Agile
Planning Poker
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.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 many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.When estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.
Complexitydifferent
MediumMediumMediumLow
Timedifferent
Ongoing30-60 min30-90 min2-5 min je Item
Participantsdifferent
2-122-63-123-9
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Kanban board, WIP policies, Flow metricsSmaller Stories, Acceptance Criteria, Split RationaleAffinity Size Map, Grouped Estimates, Unclear ItemsRelative Estimates, Assumption Notes, Split Candidates
Tagsno overlap
FlowVisual managementDelivery
BacklogIterationDelivery
EstimationBacklogRelative sizing
EstimationAgileRelative sizingTeam
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