Our team struggled with unpredictable sprint outcomes because unplanned defects constantly derailed our commitments. We’d plan a sprint with story points allocated to features, then critical bugs would arrive mid-sprint forcing us to drop planned work. Velocity became meaningless and carryover rates climbed above 30%.
We implemented a defect buffer approach in Jira 9. Now we estimate bugs in story points just like features and reserve a dedicated swimlane on our sprint board with a WIP limit of 15 points for in-sprint defects. Automation flags critical bugs that arrive mid-sprint so the team can assess impact immediately. Board filters highlight bugs separately from planned stories, giving us visibility into how much capacity defects actually consume each sprint. After three sprints our velocity stabilized and carryover dropped to 12%.