Sprint Delivery Data Audit: Carry-Over and Scope Change
Analyse several sprints for predictability.
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Analyse delivery across our last sprints. For each sprint: committed items, completed items, items added mid-sprint, items removed, and carry-over: [SPRINT_DATA]. Present the numbers first, then the story. Calculate completion rate (completed divided by committed), scope change rate (added plus removed, divided by committed) and carry-over share, with arithmetic for each sprint and the average, rounded to one decimal place. Say which sprints look unusual compared with the average. Identify patterns: sprints with big additions, stories that carry over twice, and sprints where the goal was missed. Offer three hypotheses about causes, each with a cheap test, such as comparing carried-over items with completed ones to see whether they were larger, older or dependent on another team. Return a table. Small samples limit what these numbers can show, and they must not be used to compare teams or people. Say how many sprints you were given, because fewer than six is a very small sample. Keep the explanation of each hypothesis to two sentences and label every cause as a possibility, not a finding.
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Invented sprints. S1: committed 20, completed 17, added 2, removed 1, carry-over 3. S2: committed 22, completed 15, added 6, removed 0, carry-over 7. S3: committed 18, completed 16, added 1, removed 1, carry-over 2. Completion rate: S1 17 / 20 = 85 percent; S2 15 / 22 = 68 percent; S3 16 / 18 = 89 percent. Average = 80.7 percent. Scope change: S1 (2 + 1) / 20 = 15 percent; S2 6 / 22 = 27 percent; S3 2 / 18 = 11 percent. Pattern: the sprint with the most added work had the lowest completion. Hypothesis: urgent requests bypass planning. Three sprints are a small sample.
Illustrative only, made-up data. Your results will differ and must be reviewed.