Check whether resolved work is staying closed
A reopen percentage can show whether a team is solving issues cleanly or closing work too early.
Work Tools
Estimate how often resolved cases are later reopened.
Why this page exists
Support quality gets easier to track when reopened cases and resolved cases are turned into one percentage instead of being reviewed as separate counts. This calculator helps teams estimate reopen rate from reopened and resolved case volume.
Interactive tool
Enter your numbers and read the result first, then use the sections below to understand what affects the outcome.
Calculator
Estimate how often resolved cases are later reopened.
Result
Estimated reopen rate based on reopened cases divided by resolved cases.
This is a simple quality signal, not a full support-health diagnosis. Reopen definitions, time windows, and workflow rules can change what the rate means.
Planning note
Last updated April 16, 2026. Use this tool to compare scenarios and plan ahead, then confirm important details with the lender, employer, insurer, contractor, or other qualified provider involved in the final decision.
How it works
Enter reopened cases and resolved cases.
The calculator divides reopened cases by resolved cases.
It shows the reopen rate percentage and the counts used.
Understanding your result
This is a simple quality signal only. It can help surface premature closures or weak resolution quality, but the number is most useful when definitions and reporting windows stay consistent.
Browse more work toolsExamples
Example scenarios help turn a quick estimate into a more useful comparison or planning step.
A reopen percentage can show whether a team is solving issues cleanly or closing work too early.
A rate can make it easier to compare quality trends even when total resolved volume changes.
Reopen rate often becomes more useful when reviewed beside closure rate, first response time, and escalation metrics.
When to use it
Use this when you want a quick quality check on whether resolved tickets or cases are staying closed.
It is especially useful when you are comparing teams, periods, or workflow changes and want a cleaner percentage view.
Assumptions and limitations
The estimate assumes reopened and resolved cases are being counted on the same reporting basis and time window.
It does not tell you why the cases reopened or whether the underlying issues were unusually complex.
Common mistakes
Comparing reopen rates without confirming the same reopen definition can make the results misleading.
Treating one period of data as proof of a systemic quality problem can overstate what the number means.
Practical tips
Check the reopen rate alongside closure rate and resolution time so you can see whether speed is hurting quality.
Review a few reopened cases directly if the rate moves up, because the percentage alone will not explain the cause.
Worked example
A worked example shows how the estimate behaves when the inputs resemble a real planning decision.
A team resolves 420 cases and 18 of those are later reopened.
1. Enter 18 as reopened cases.
2. Enter 420 as resolved cases.
3. Divide reopened cases by resolved cases to estimate the reopen percentage.
Takeaway: The result gives a simple quality signal that is easier to trend than raw reopen counts alone.
FAQ
The calculator divides reopened cases by resolved cases and shows the result as a percentage.
Because it can help show whether resolved work is actually staying resolved or returning due to incomplete handling.
Not by itself. It is one signal and works best with other service and quality metrics.
Related tools
Closure, first-response, and resolution-time tools help show whether the reopen rate is part of a broader service-quality pattern.
Resolved-ticket cost and escalation tools can add context if quality issues are also affecting workload or cost efficiency.
Estimate case closure rate from total opened or assigned cases and the number closed.
Estimate average first response time from total response time across all cases and the number of cases handled.
Estimate average support cases per agent from total support cases and total agent count.
Estimate the average time it takes to fully resolve a case, ticket, or support request.
Estimate average support cost per resolved ticket from total support cost and resolved ticket count.