Info-Tech Research Group Publishes New Research Blueprint to Optimize Service Desk Operations

‘Info-Tech Research Group, a global IT research and advisory firm, has published new service desk research blueprint that will enable organizations to leverage service desk ticket data to gain insight on how to  improve operations.

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Organizations that leverage a data-driven approach to their service desk can efficiently allocate resources and communicate their current and future value of the service desk to the business.

“Service desks can improve their services by leveraging ticket data to inform their actions,” explains Research Analyst Benedict Chang. “However, many organizations don’t know where to start. It’s tempting to wait for perfect data, but there’s a lot of value in analyzing your ticket data as it exists today. Start small. Track key tension metrics based on the out-of-the-box functionality in your existing service desk tool. Review the metrics regularly to stay on track.”

Slow and steady improvements of the service desk can add business value and positively impact customer satisfaction. Some of the benefits outlined in this new research are as follows:

1. IT Benefits – The discovery and implementation of proper metrics to improve the service desk, as well as increased visibility within the business and other IT departments in a structured manner.
2. Business Benefits – More effective support and quicker resolutions to incidents and service requests, as well as better visibility into the current state, challenges, and goals of the service desk.

“By reviewing your ticket data, you’re going to get better organically,” adds Chang. “You’re going to learn about the state of your environment, the health of your processes, and the quality of your services. Regularly analyze your data to drive improvements.”

The research blueprint includes Info-Tech’s methodology for a data-driven approach to service desk optimization. The firm recommends continuous analysis of ticket data to improve the service desk. The data-driven recommendation will:

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• Reduce noise and allow for the standardization of ticket data in a format that will ease analysis.
• Define ticket expectations and keep data up to date.
• Implement low-effort improvements for quick successes.
• Create better communication of findings to the business through a data-driven approach