Executive Summary

ITSM Incident Analysis

Comprehensive qualitative and quantitative analysis from the most recent data run.

57,875 Total Incidents (12 mo)
4,451 Avg Monthly Volume
5,533 Peak Month (October 2025)
23.8h Avg Time to Assign
99.8h Avg Time to Resolve
97.6% Closure Rate

Workload Distribution

The top assignment group, eClinicalWorks, handles 23.8% of all incidents, indicating a high concentration of workload. The top 5 groups account for the majority of ticket volume:

eClinicalWorks 23.8%
IT Service Desk 18.3%
Office 365 Team 14.4%
VOIP Support Team 8.4%
IT Network Monitoring Team 8.1%

Priority Mix & Risk

The vast majority of incidents are classified as Low priority (86.9%), while High/Urgent incidents represent 8.2% of total volume.

Low
86.9%
High/Urgent
8.2%

While low-priority tickets dominate, the 8.2% high/urgent rate warrants monitoring for spikes that could indicate service instability.

Operational Efficiency

Incidents take an average of 23.8 hours to assign and 99.8 hours to resolve. The gap between assignment and resolution (76.0 hours) represents the active work and queue time within teams.

The overall closure rate of 97.6% indicates strong throughput. Remaining open tickets should be reviewed for aging.

Group & Team Analysis

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1 Requests by Group (12 Months)

Chart 1 Requests by Group (12 Months)

This chart displays the total incident volume distributed across the top individual assignment groups over the last 12 months, highlighting which teams carry the largest support load.

Trend

A small number of groups handle a disproportionately large volume of incidents. The volume drops off sharply after the top 5 groups, indicating a high degree of specialization. The top group, 'eClinicalWorks', managed 23.8% of all incidents, showing its central role in IT support.

2 Offshore Requests by Group

Chart 2 Offshore Requests by Group

This chart simplifies the operational view by consolidating numerous specific IT teams into broader functional categories, such as 'Offshore IT Support Desk'.

Trend

The 'Offshore IT Support Desk' is the single largest category, responsible for 50.7% of all incidents. This demonstrates a significant reliance on this consolidated team for front-line and core service support.

3 Most Recent Month — Group Share

Chart 3 Most Recent Month — Group Share

This pie chart illustrates the distribution of incident tickets across different assignment groups for the most recent full month (2026-02).

Trend

In the most recent month, 'eClinicalWorks' handled the largest share of tickets, accounting for 23.5% of the total. This highlights its continued central role in incident management.

10 IT Service Desk Volume

Chart 10 IT Service Desk Volume

This chart displays the monthly incident volume handled specifically by the 'IT Service Desk' over the last 12 months.

Trend

The IT Service Desk handled a total of 10574 incidents over the past year, averaging 813 incidents per month. A notable peak in volume occurred in 2025-10, indicating periods of increased demand or specific events driving more tickets to the service desk.

11 IT Deskside Support Volume

Chart 11 IT Deskside Support Volume

This chart displays the monthly incident volume handled specifically by the 'IT Deskside Support' team over the last 12 months.

Trend

The IT Deskside Support team handled a total of 4110 incidents over the past year, averaging 316 incidents per month. A notable peak in volume occurred in 2025-10, indicating periods of increased on-site support needs.

12 eClinicalWorks Volume

Chart 12 eClinicalWorks Volume

This chart displays the monthly incident volume handled specifically by the 'eClinicalWorks' team over the last 12 months.

Trend

The eClinicalWorks team handled a total of 13797 incidents over the past year, averaging 1061 incidents per month. A notable peak in volume occurred in 2025-10, indicating periods of increased activity or issues related to the eClinicalWorks system.

13 eCares Support Volume

Chart 13 eCares Support Volume

This chart displays the monthly incident volume handled by the 'eCares Support' groups (Ecares issues and Enhancement, Analytics, Enhancement Group) over the last 12 months.

Trend

The eCares Support groups handled a total of 3117 incidents over the past year, averaging 240 incidents per month. A notable peak in volume occurred in 2026-01, suggesting periods of increased development, enhancement, or analytical support needs.

9 Hardware Requests by Month

Chart 9 Hardware Requests by Month

This stacked bar chart, with an overlaid line for total volume, illustrates the monthly breakdown of hardware-related requests (Printer, Laptop, Desktop) handled by IT Deskside Support over the last 12 months.

Trend

Desktop requests consistently represent the largest portion of hardware support. The total volume of IT Deskside Support requests peaked in 2025-10, suggesting a period of high demand or specific hardware refresh cycles.

23 Resolution Time by Group

Chart 23 Resolution Time by Group

This chart shows average time to resolve (create-to-resolve) by assignment group, highlighting which groups have the longest resolution times.

Trend

The group with the longest average resolution time among those with sufficient volume is 'IT Network' (542.4 hours average). Comparing groups helps target process improvement and capacity.

Time-Series Trends

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7 Incident Timeseries (Weekdays)

Chart 7 Incident Timeseries (Weekdays)

This chart tracks key efficiency metrics for incidents created on weekdays, comparing the monthly volume of new incidents against the average time (in hours) to assign, resolve, and close them.

Trend

Weekday incident volume and processing times show typical operational fluctuations. Analyzing these trends helps in understanding the core performance of the support team during standard business hours.

8 Incident Timeseries (Weekends)

Chart 8 Incident Timeseries (Weekends)

This chart tracks key efficiency metrics for incidents created on weekends, providing insight into off-hours support performance.

Trend

Weekend volumes are naturally lower. However, response times (assign, resolve, close) may be higher due to reduced staffing. Consistently high weekend resolution times could indicate a need for better on-call procedures.

16 Deskside Support Timeseries

Chart 16 Deskside Support Timeseries

This chart provides a detailed timeseries analysis for the 'IT Deskside Support' group, focusing on weekday incident volume and key performance indicators (KPIs) like time to assign, resolve, and close.

Trend

The chart shows the monthly fluctuation in ticket volume for IT Deskside Support on weekdays. It correlates this volume with the average time taken for different stages of the incident lifecycle. Any significant deviations in the time-based metrics, especially during high-volume months, could indicate stress on the team's resources.

SLA & Response Times

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5 Create-to-Assign Time by Month

Chart 5 Create-to-Assign Time by Month

This chart visualizes the average time taken from ticket creation to its first assignment (Create to Assign Time) on a monthly basis over the last 12 months.

Trend

The average Create to Assign Time is 24.62 hours. Performance was best in 2026-02 and worst in 2025-03, indicating fluctuations in initial response efficiency. This metric is crucial for understanding the speed of initial triage and workload distribution.

6 Create-to-Resolve Time by Month

Chart 6 Create-to-Resolve Time by Month

This chart illustrates the average time taken from ticket creation to its resolution (Create to Resolve Time) on a monthly basis over the last 12 months.

Trend

The average Create to Resolve Time is 99.17 hours. Similar to assignment time, there are fluctuations, with the best performance in 2026-02 and the worst in 2025-04. This metric directly impacts user satisfaction and operational efficiency.

14 Assign Time Distribution (Weekdays)

Chart 14 Assign Time Distribution (Weekdays)

This chart shows the distribution of the time it takes to assign an incident on weekdays.

Trend

The bell curve is right-skewed, indicating that most incidents are assigned quickly, but a long tail of outliers takes significantly longer. The median (0.25 hours) is lower than the mean (23.95 hours), which is characteristic of this skew.

15 Assign Time Distribution (Weekends)

Chart 15 Assign Time Distribution (Weekends)

This chart shows the distribution of the time it takes to assign an incident on weekends.

Trend

Similar to weekdays, the weekend distribution is right-skewed. However, the mean (19.40 hours) and median (0.51 hours) are likely higher than their weekday counterparts, reflecting slower response times during off-hours.

21 Create-to-Close Distribution

Chart 21 Create-to-Close Distribution

This chart shows the full lifecycle: distribution of time from incident creation to closure (create-to-close) for weekday incidents.

Trend

Mean create-to-close time is 113.1 hours and median is 29.4 hours. The distribution is typically right-skewed; the long tail indicates some incidents take much longer to close and may warrant focus.

20 Overdue SLA by Month

Chart 20 Overdue SLA by Month

This chart tracks the percentage of incidents that are resolution-overdue and first-response-overdue by month, showing SLA compliance trends.

Trend

Overall, 13.6% of incidents were resolution overdue and 36.9% were first response overdue in the last 12 months. Rising trends indicate capacity or process issues; declining trends indicate improvement.

Priority & Category Breakdown

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4 Incidents by Priority (12 Months)

Chart 4 Incidents by Priority (12 Months)

This chart breaks down all incidents by their assigned priority. The overwhelming majority are classified as 'Low' priority (86.6%), while a small but significant portion are 'High' or 'Urgent' (8.2%).

Trend

The overall distribution of priorities has remained relatively stable. However, there was a notable spike in High/Urgent incidents during 2026-01, suggesting a period of service instability or a critical business event that required significant IT attention.

19 Category Volume by Month

Chart 19 Category Volume by Month

This chart shows incident volume by Category (e.g. User & Administration, Devices & Application) by month, revealing where demand is concentrated.

Trend

The top category is 'User & Administration' (13.1% of volume). Category trends help prioritize knowledge base, automation, and training by demand area.

22 Request Mode Volume

Chart 22 Request Mode Volume

This chart shows how users contact support: E-Mail, Web Form, Alert, Mobile, etc., revealing channel mix and where to invest in self-service or automation.

Trend

The dominant channel is 'E-Mail' (67.2% of incidents). Channel mix informs portal design, email handling, and alert integration.

18 Closure Code Distribution

Chart 18 Closure Code Distribution

This chart shows why closed incidents were closed: Success, Moved, Failed, or Not Assigned, providing a quality and process view.

Trend

0.0% of closed incidents have Closure Code 'Success'. The rest are Moved, Failed, or Not Assigned. Improving Success rate and reducing 'Not Assigned' supports accurate reporting and quality.

17 Request Status by Month

Chart 17 Request Status by Month

This chart shows how incidents move through statuses (Closed, In Progress, Pending, etc.) by month, with a closure rate trend line.

Trend

97.6% of incidents in the last 12 months are Closed. 1097 incidents remain in progress or pending. Tracking closure rate over time helps assess backlog and throughput.

Key Takeaways & Recommended Actions

1

Balance Workload

Review resource allocation for high-volume groups to reduce bottlenecks and prevent burnout in top-performing teams.

2

Investigate Spikes

Conduct root cause analysis for High/Urgent incident spikes to prevent recurrence and improve service stability.

3

Monitor SLA Trends

Track create-to-assign and create-to-resolve trends monthly to align with SLAs and user expectations.

4

Team-Specific Metrics

Use per-team metrics (IT Service Desk, Deskside, eClinicalWorks, eCares) for targeted process and capacity improvements.

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