How AI Can Improve IT Service Management In A Pandemic | Straight Talk

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This article is by Featured Blogger Louis Columbus from his Blog Page. Republished with the author’s permission.

  • A few CIOs with call center-based Incident Management systems can’t see the bottom of incident queues due to the thousands of pending laptop connectivity, remote access login, and VPN support requests still unanswered.
  • Previous approaches to prioritizing critical incidents aren’t keeping up with the volume, variety, and velocity of inbound requests for support with all employees now working from home.
  • IT teams need their IT Service Management (ITSM) Systems to provide a more automated approach to routing critical incidents to specialist teams in real-time.

IT service operations teams and their leaders are in the middle of the busiest weeks of their careers right now. They’re scrambling to help many first-time work-from-home employees get securely connected as ITSM systems bog down under the weight of workloads they weren’t designed for. Incident queues are thousands of requests long in many companies, waiting for assignment.

Thwarting The Pandemic’s Effects on IT With AI and Predictive Routing

A quick Pareto Analysis of an Incident Management queue with trouble tickets shows that approximately 75% to 80% of the requests for service are from the top 20% of connectivity and security login issues all IT users face. Adopting an AI-based approach to Incident Deflection that seeks the best IT service resource starting with help files and videos and then progressing to an IT service agent would reduce the queue quickly. According to a recent study by Bain & Company titled AI Is Lifting Service-Center Performance, found the following:


BAIN & COMPANY, AI IS LIFTING SERVICE-CENTER PERFORMANCE,2019. 

 

 

 

 

 

 

 

 

 

 

 

 

 

The metrics from Bain’s study apply equally well to customer call centers as they do to IT service desks and the teams staffing them. By using AI to match inbound IT requests with services agents across all channels, the service bottlenecks created with a first-in, first-out approach are alleviated. Algorithms need to be trained to interpret a given IT request in the context of every available IT agent’s unique strengths and capabilities. Matching inbound requests that can’t be solved by Incident Deflection with the best available agent can eliminate the sizeable trouble ticket, and Incident Management backlogs many IT departments are struggling with today. The bottom line is that the AI-based approach to modernizing ITSM shows the potential to lower IT costs, reduce errors, increase user satisfaction levels while improving response times and speed. Best of all, IT agents are going to be able to focus on more challenging work because AI can handle the more mundane tasks by constantly learning how Incident Deflection, predictive routing, and performance analytics can improve. 

The Roadmap To More AI-Driven ITSM Starts With IT Operations Management 

No one designed an ITSM system assuming everyone in an organization would want assistance at the same time, and the evidence of this being true are everywhere in IT teams today. It’s time to re-think the platforms that IT uses to support an entirely virtual workforce.  

One of the more interesting perspectives on how IT needs to change to support more AI-enabled ITSM and other enterprise systems is from BMC Software - their premise is that AI is a core component of all technology systems and applications within an Autonomous Digital Enterprise. Its recent study, Maximizing the Value of Hybrid IT with Holistic Monitoring and AIOps (10 pp., PDF) conducted by Hanover Research, is based on interviews with 340 IT and Infrastructure and Operations (I&O) professionals. The goal of the study was to look at the current state of IT Operations Management (ITOM) and IT Service Management (ITSM) convergence across the industry. Applying AI and machine learning techniques to IT is how AIOps is often defined. Gartner has reported a 25% increase in end-user inquiries on AIOps as of their latest quarter. It’s time to de-hype and demystify AIOps by applying it to the most urgent business cases organizations have. For many, their IT service desks are overwhelmed today, making for an excellent first use case to put the technology to work. 

For AI-enabled ITSM systems to succeed, they’ll need to have an underlying IT infrastructure capable of providing high-quality data to enable AI and machine learning algorithms to learn continually. Key insights from the study include the following: 

  • 71% of IT leaders are relying on SaaS-based platforms for integrating ITOM and ITSM in their organizations. They’re prioritizing this approach due to the speed, ease of deployment and upgrade, elastic scalability, and enterprise-grade performance. 

  • The majority of IT leaders expect to see improvements in service quality, speed, and issue resolution from integrating ITOM and ITSM into a unified platform. The majority of IT leaders are motivated by the potential of managing data complexity more effectively, followed by faster MTTR for service issues. The following graphic reflects the main findings:


MAXIMIZING THE VALUE OF HYBRID IT WITH HOLISTIC MONITORING AND AIOPS

 

 

 

 

 

 

 

 

 

  • 76% of IT leaders consider it very important or extremely important to be able to use converged ITOM-ITSM to prioritize tickets based on impact, understand their cause, and understand how to resolve them. With an integrated platform, IT incident reports can be created with information about the higher-level effects of problems with both the causal incident (CI) and other impacted incidents. IT can see how key business services or applications might be interrupted and can prioritize resources and effort where they will provide the most value. ​

Additional reading: 

BMC Blogs, 2019 Gartner Market Guide for AIOps Platforms, December 2, 2019 

Boston Consulting Group, Ready Or Not, AI Is Coming To IT Operations (PDF, 7 pp.) 

Digital McKinsey, Modernizing IT for digital reinvention (PDF, 75 pp.) 

McKinsey & Company, Global AI Survey: AI proves its worth, but few scale impact (PDF, 11 pp.) 

McKinsey Global Institute, Visualizing the uses and potential impact of AI and other analytics, interactive online