Smarts from within: 3 reasons to embrace machine learning

Why investing in machine learning technology and AI capabilities makes sense to drive smarter and more automated enterprise service management.

artificial intelligence / machine learning
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At Dreamforce earlier this month, a key theme to Salesforce’s annual event that attracts over 100,000 attendees was intelligence. Salesforce’s artificial intelligence (AI) platform, Salesforce Einstein, and the launch of myEinstein, drove forward that theme, introducing a new machine learning platform to help customers build custom AI applications across Salesforce using point-and-click methods instead of manual coding.

With myEinstein, Salesforce is further pushing automated capabilities into customer relationship management (CRM), helping companies deploy new AI features such as predictive functionality and bots that arm customer service agents with new tools to help them to be more strategic and effective in their jobs. CRM plays a critical role as the interface between customer requests and company services. Automated service management provides a similar function within the organization in departments including IT, HR and Finance, giving internal service desks the functionality to enable more efficient employee onboarding, IT help desk support and payment tracking.

There are three reasons CIOs would do well to embrace machine learning in their own enterprise service management solutions to drive smarter and automated capabilities.

1. It is what your users expect

The consumerization of IT is driving demand for intuitive and comprehensive platforms that better understand and serve user needs, intelligently remembering and leveraging past engagements to predict service requests. Much like a traveler ordering an Uber instead of hailing a cab, employees will start expecting a similar experience from the technology within IT service management. This applies to external customers and internal employees who both expect new intelligent features that can rapidly and accurately route their issues to rapid resolution, ultimately providing a better experience through improved self-service.

2. There’s money to be saved

In today’s enterprise environments, many departments track service requests manually through spreadsheets and emails, or by using a basic ticket management system. Those manual processes very quickly require massive amounts of money and personnel to maintain. With machine learning, companies can rapidly save money and achieve massive productivity gains thanks to new features that automate those previously manual processes.

Technicians usually inspect the vital pieces of information that are submitted, such as who submitted it, from which department, under what category, and if approvals are necessary. Following that first review, they will route the ticket or request to where it belongs based on that information. When adding up all of those tickets and requests, that’s a lot of time. For HR and IT staff, more autonomous service management means hours of time savings, which can be used to focus on more strategic tasks instead, and deliver consistently high-quality services.

3. Services to self-resolve

Machine learning will power the self-resolving service platform. Thanks to machine learning capabilities that can constantly track user behavior and make smart suggestions, service management solutions will be able to offer self-help options that reduce the number of tickets entered into the service desk. Most tickets that are submitted to service desks are issues that have been previously addressed. By comparing and analyzing new tickets against historical ticket data, service management platforms powered by machine learning can suggest categories and sub-categories for submitted tickets, and identify and group similar tickets as a possible growing trend thereby helping administrators more quickly recognize larger issues that need to be escalated. This approach can dramatically simplify the ticket routing process to drive faster time to resolution, as well as more accurate reporting.

As technology evolves, the future of service management will incorporate bots and voice recognition to provide more versatility in resolutions for users. For example, an account executive on the road will be able to communicate an issue through the Bluetooth in their car, while a bot suggests self-service solutions or offers to create a ticket.

The role of the CIO is to spearhead the adoption of new technology innovation to support company growth and momentum. In the same way that CIOs were on the front lines to deploy cloud-based solutions and internet-connected services five years ago, it’s only a matter of time before machine learning capabilities become a standard feature in any organization that values customer and employee service support.

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