6 Ways Analytics Will Take Your IT Service Data to the Next Level

In Analytics

IT organizations are under increasing pressure to improve their service delivery to both internal and external customers. Fortunately, ServiceNow® provides the operational information needed to streamline and automate your processes. The application captures data on your people, processes, and technology assets, which can be analyzed to drive improvements throughout your IT services.

Here are six key areas where you can employ analytics to get the most out of your ServiceNow data. Maximize your IT metrics with the tools to identify trends and become more proactive while simultaneously improving service delivery.
 

1. Outages

Your business needs to understand the frequency, scope, and duration of outages, as well as pinpoint the underlying cause. This understanding allows you to see trends and identify issues that, when resolved, can improve application reliability and uptime.

More importantly, you want to be able to link outages to business metrics, such as the number of customers impacted or the revenue outcome if the affected system is customer-facing. Even with internal systems like a billing application, you can quantify the impact. Attaching a monetary value can help anchor all of the technical factors to a common business metric.

An analytics application will help you connect the origin of an outage with its overall impact. Numerify is designed to predict outages and their revenue impact so that such service disruptions can be prevented, as shown in the dashboard below.

predict-dashboard

2. Volume

Understanding incident volume helps you properly staff your IT service organization, which can be particularly valuable for those with a seasonal business. If you’ve identified that incident volume is highest between May and September, for instance, you can proactively increase staff to avoid backlog.

One university customer I worked with saw incidents surge during fall and winter. Just knowing the increase in volume was not enough – they had to slice and dice the data to figure out exactly which assignment groups and skillsets were needed. The extra staff necessary for student signup systems was easy to predict, but less obvious was the additional support required for networking systems. With analytics, the customer determined that a recent firewall rollout was creating networking issues for some devices, increasing the number of incident escalations sent to the networking group.
 

3. Reassignment Count

The number of times an incident, request, change, or problem is reassigned correlates directly with a process gap. For example, the reassignment count can help you identify outlier processes that would benefit from better documentation or more training. If incidents are being reassigned five times, you may need to set up an alert system so that you can resolve issues more quickly. You might also consider examining incidents with a high reassignment count to see if there’s an issue with the initial routing setup.
 

4. Change-to-Incident Relationship

In my experience, customers often suspect that a large number of incidents logged are the result of changes, but they lack the means to definitively establish that correlation. If your organization introduces hundreds of changes a month like some of our customers do, it would be difficult for you, too.

The problem is that not all organizations have a mature CMDB that tracks change-to-incident relationships. In the absence of such data, change owners can correlate data using assignment groups, business services/applications, locations, and users to infer change-to-incident relationships automatically. By using IT analytics to drill down into the connection between incidents and changes, you can better understand where your operations need tightening and ensure a smoother change management process.
 

5. Age

The overall age of incidents impacts resolve time, mean time to resolve, and SLAs. It’s important to dig in and conduct analyses to see if you can resolve incidents that have been open for a long time. One customer set up alerts that he calls “love darts”: whenever incident age crosses a certain threshold, an automated email is sent to the assignee and their manager reminding them to close the incident. The darts get more forceful if the incident age crosses the next threshold, or if individuals have too many aging incidents.

Below you can see how IT managers use an application like Numerify to monitor staff workloads, including total open work and aging work.

service-need-illustration

6. Open Problems

Reducing the number of open problems is also helpful, since they are the underlying cause of incidents – a single problem may be responsible for hundreds of incidents. Performing root cause analysis and fixing the underlying problem can greatly reduce incidents and positively impact your environment as a whole.

[Photo courtesy of Pixabay.]
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