Measure closures, backlog shifts, reopen pressure, and SLA delivery. Compare critical issues and daily throughput. Turn engineering support data into confident improvement actions today.
This page keeps a stacked single-column page flow, while the form itself uses 3 columns on large screens, 2 on smaller screens, and 1 on mobile.
| Week | Reported | Resolved | Reopened | Within SLA | Resolution Rate |
|---|---|---|---|---|---|
| Week 1 | 32 | 28 | 3 | 24 | 87.50% |
| Week 2 | 29 | 27 | 2 | 23 | 93.10% |
| Week 3 | 34 | 30 | 1 | 27 | 88.24% |
| Week 4 | 25 | 24 | 1 | 21 | 96.00% |
Use similar period-based data from sprints, weeks, or monthly service reviews.
1) Issue Resolution Rate
Issue Resolution Rate (%) = (Issues Resolved ÷ Issues Reported) × 100
2) Net Resolution Rate
Net Resolution Rate (%) = ((Issues Resolved − Reopened Issues) ÷ Issues Reported) × 100
3) Reopen Rate
Reopen Rate (%) = (Reopened Issues ÷ Issues Resolved) × 100
4) SLA Compliance Rate
SLA Compliance (%) = (Resolved Within SLA ÷ Issues Resolved) × 100
5) Critical Resolution Rate
Critical Resolution Rate (%) = (Critical Issues Resolved ÷ Critical Issues Opened) × 100
6) Backlog Clearance Rate
Backlog Clearance (%) = ((Backlog Start − Backlog End) ÷ Backlog Start) × 100
7) Throughput
Resolved per Engineer = Issues Resolved ÷ Engineers Handling Issues
Resolved per Workday = Issues Resolved ÷ Working Days
8) Overall Performance Score
Score = 35% Resolution Rate + 25% SLA + 20% Critical Resolution + 10% Speed Score + 10% Backlog Clearance
These formulas help engineering teams evaluate closure efficiency, quality stability, speed, and backlog direction in one structured view.
It measures how many reported issues were resolved during a selected period. It helps engineering teams understand closure efficiency and compare performance across weeks, sprints, or months.
Reopened issues indicate closures that did not hold. Tracking them separately prevents inflated success rates and highlights quality gaps in debugging, testing, verification, or handoff processes.
A team may resolve many issues but still miss required timelines. SLA compliance adds time-based accountability and shows whether service expectations were met consistently.
Backlog clearance shows whether the unresolved queue shrank or grew. This helps leaders judge if the team is only keeping pace or truly reducing pending engineering work.
It should be reviewed beside the overall rate. A strong general rate can still hide weak performance on urgent incidents, outages, or high-risk production defects.
Not always. A high rate looks better when reopen rates stay low and SLA success stays high. Quality and speed should be evaluated together, not in isolation.
Yes. It works well for sprint retrospectives, support dashboards, reliability reviews, maintenance reporting, and service management checkpoints where engineering issues are tracked quantitatively.
Use one consistent period such as a week, sprint, month, or quarter. Keeping the same timeframe across reports makes trends more reliable and easier to compare.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.