Efficiency
The Efficiency tab measures the support burden an application creates for IT, based on service request tickets. Use it to identify which employee groups generate the most support burden and where application owners should focus to reduce it.
Review service request metrics
The top section of the Efficiency tab shows how often employees encounter issues with the application over time.

From the Efficiency tab of the target application:
Review the Service requests / employee KPI to see how often employees raise tickets for the application over the last 30 days, with the month-over-month change.
Explore the column chart to see how the metric evolves over the last 13 months. All data on this tab reflects the ticket creation date, not when tickets are revised or resolved.
Review the Total service request tickets metric to see the total number of tickets raised for the application. Hover over it to open the action menu and drill down into the specific tickets behind the aggregate.
The Efficiency dimension of the AHEAD score maps the Service requests / employee ratio to a percentage:
0.00
100%
0.02
80%
0.05
50%
0.08
20%
0.10 or more
0%
Analyze efficiency across employee groups
Examine the bar chart to identify which employee groups struggle the most with the application.

From the Efficiency tab of the target application:
Filter the bar chart by organizational dimensions, such as Department, Group, Team, or Business Unit, to identify which employee groups struggle the most. Note that the available options depend on the user organization fields configured in your Nexthink environment.
Review Service requests / employee and Total service request tickets per group using the inline bar indicators for quick visual comparison.
Focus improvement efforts on the groups that struggle most.
Investigate efficiency insights
Use the AI-powered Insights to understand the causes behind rising support tickets and which employee groups are most affected. The insights cover:
Why the selected efficiency pattern matters.
The main drivers and root causes behind the pattern.

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