MetTel is a telecommunications company providing data, network, cloud, and mobile IT solutions for businesses and government agencies. Like many large companies, MetTel has a trouble ticket system in place to respond to customer needs. Customers would submit tickets about any issues they were having with their services and an operator or engineer would manually sort and resolve each ticket.

As part of a plan to improve their operational efficiency and quality of service, they decided to automate most of these day-to-day repetitive maintenance tasks of monitoring and triage of network devices (SD-WAN).

A large volume of the corrective tasks that needed to be carried out to bring a device back into normal operation after a service outage required a complex triage operation to analyze the reason for failure. It would take a member of the support team an average of 10-15 minutes on each device to gather enough information to make a decision on how to proceed.

To help speed up this process, we decided that an automation solution would be the best approach. Implementing Intelligent Process Automation (IPA) would significantly increase efficiency as it would reduce triage and decision times to almost instant, and could even remove the need for human interaction in some cases.

We worked with MetTel to create Ticket Next Best Action (TNBA), a solution that uses programming techniques to automate each stage of the issue resolution process, where A.I. technology identifies and executes the best possible next action using historical data.

TNBA uses programming techniques to automate tasks and A.I. to decide the best possible next action.

First, each ticket is analyzed for the service error the customer is experiencing. Then, an alert is sent to take it to the next stage, where historical data from internal tools and logs is used to analyze the current and previous status of each affected system to determine the issue. Next, the automation engine connects to several different APIs to request the status of every related system and uses this information to assign the ticket to the best resolution team, or it will request a better decision from TNBA to achieve a resolution.

Within these process chains, TNBA was able to accurately identify the next stage of the ticket 75% of the time. A further 60% of the time, it can confidently predict the next stage of the ticket and, if applicable, automatically move it to the next stage to solve the customer’s issue.

A further 20% of the time, the solution can correctly suggest the next stage to an operator, helping to save time and drive further efficiency.

All triage of SD-WAN is now fully automated and 52% of corrective maintenance operations are now completely solved by A.I. This allows MetTel to dedicate valuable resources into offering more proactive services, and to drive the continous growth of their company without a significant increase in the department’s budget.