Request aging report

The Request Aging report helps you understand how long requests in your workspace remain unresolved, and how different stages in their lifecycle impact resolution times. By tracking request age, assignments, and distribution across time buckets, admins and analysts can get a clear view of backlogs, bottlenecks, and efficiency opportunities.

To access this report, navigate to Analytics > [Workspace name] > Request Aging.

The report covers general requests, service requests, incidents and problems.

Understanding request aging analytics

The report includes several key metrics that are designed to highlight how long requests stay unresolved and where delays may occur.

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Metric

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Description

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Why it matters

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Request age

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Shows how long each open request has been active, measured from creation until the present. Calculated in absolute hours.

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Helps you understand the age of unresolved requests and spot items that may need escalation.

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Time to first assignment

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Measures the time taken for a request to be assigned to an agent for the first time. Calculated in business hours.

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A long time here may indicate delays in triage or routing. Only applies to requests that have been assigned at least once.

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Number of re-assignments

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Counts how many times a request was reassigned between agents or teams after the first assignment.

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Frequent reassignments often signal unclear ownership or process gaps.

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Age distribution of unresolved requests

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Groups open requests into time buckets (e.g., 0–2 hrs, 2–4 hrs, etc.) to show how many requests fall into each age bracket. Buckets are dynamically sized based on your dataset.

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Gives you a quick view of backlog composition and where requests tend to “pile up.”

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Request lifecycle breakdown

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Displays how much time requests spend in different statuses (such as Open, In Progress, On Hold). Measured from status change timestamps.

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Useful for identifying where requests get stuck for long periods.

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Request volume by time

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Breaks down the number of requests into time buckets for metrics like time to first response, resolution time, or time to first assignment. Calculated in business hours.

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Lets you compare performance across different time ranges and spot trends in responsiveness.

For example, in the Age distribution of unresolved requests, you notice a growing number of requests in the 3–5 day bucket over the last quarter. You also notice the Time to first assignment widget and see a high average for the same period. Cross-referencing both reveal that the backlog isn’t caused by long resolutions, but because they’re sitting unassigned at the start. This points to a need to streamline intake and routing processes.

Filtering the report

You can filter the Request Aging report at two levels:

• Global filters: These apply to the entire report and are available at the top of the report. Filters include:

  • Duration – Choose the time period for which requests are included.

  • Request type – Focus on general, incident, problem, or service requests.

  • Request attributes – Narrow your view by agent, group, status, priority, urgency, category, and more.

• Widget-level filters: These apply only to the specific chart or widget you’re viewing. For example, in the Age distribution of unresolved requests chart, you can filter by request type to see how ageing differs across request categories.

Global filters always apply first, and widget filters refine the view within that dataset.

For instance, if you set the global filters Duration = This month & Request type = Service requests, then add a widget filter for Priority = High, you’ll only see high-priority service requests created this month in that widget.

Drilling down into metrics

You can drill down into any widget in the Request Aging Report to see the underlying requests that make up the data. Clicking on a chart or bucket opens a detailed view with request-level information such as subject, requestor, status, priority, SLA, agent, and group.

You can also add more columns, apply additional filters, and export the dataset for deeper analysis. This makes it easy to move from high-level trends to the specific requests driving them.

Exporting the report

You can export the Request Aging report as a CSV file, with all the filters you’ve applied carried over. This will compile the date related to all open requests. Once you trigger the export, the file is generated and sent to your email, so you can easily work with the data in Excel or other BI tools.