Importance and Benefits of ML in IT Service Management
The traditional IT service management (ITSM) solutions have become ineffective in maintaining customer satisfaction levels and meeting the rising customer demands in a fast-paced digital world.
FREMONT, CA: The service desk acts as a 'go-to' place in an organization for every IT related issues and needs such as managing incidents, service disruptions, changes, or requests.
The scope of work in the service desk is enormous and wide-ranging, depending on the nature and size of the organization. Hence, as a part of the critical function, the service desk needs to be managed appropriately. The traditional IT service management (ITSM) solutions have become ineffective in maintaining customer satisfaction levels and meeting the rising customer demands in a fast-paced digital world. Thankfully, technology has changed the way work is done across all industries around the world.
SolarWinds IT Trends Report 2019: Skills for Tech Pros of Tomorrow points out that due to interruptions with day-to-day support-related issues, 79 percent of IT managers weren't able to spend sufficient time on value-added business activities or initiatives. As a result of which they end up making incorrect manual entries into a problem log leading to misinformed decision-making. An overburdened manager is more likely to fall the victim of manual or human errors.
With the changing landscape of IT enviromments, it's crucial for IT service desks to adopt emerging technologies. Data explosion in recent years has exaggerated the pressure for IT professionals. The sigh of relief is that automated processes and ML have alleviated the pressure significantly. Gone are the days when AI and ML were just buzzwords. Industries across the world are incorporating these technologies to enhance and improve operational efficiencies.
Be it predictive analytics, performance monitoring of networks, business intelligence, applications, and systems, or even for its importance in self-driving cars, AI and ML are transforming the IT space. It is interesting to note the applications of ML when it comes to ITSM. The service desk, being an essential business operator, can employ ML to streamline processes, reduce time-intensive and manual tasks, which frees up time for other projects and training to deliver business-wide transformation.
Efficient Handling of Incidents
ML has the potential to cut down the incident resolution time almost to half. With the use of ML, technicians are no more required for incident resolution, and users can easily search for solutions themselves. Chatbots have taken over the role of voice technicians and can give information to end-users by providing easy access to relevant knowledge base articles based on their queries, without them having to log a ticket. ML can help desks to route tickets to the appropriate technician or support group through their past experiences.
Asset Management
Traditional and obsolete IT assets can cause performance degradation for employees who rely on traditional assets to do their jobs. Organizations spend a lot of money on software and hardware because of asset management solutions with poor transparency. Asset management can turn this around with solutions like ML technology that can help to track their performance based on insights from performance levels or incidents associated with a given asset.
Problem Prediction and Prevention
Using large datasets of past performance, ML can make an analysis of incidents to predict future problems. This predictive capability of ML can help save money, time, and effort for the entire organization as steps can be taken before the severity or impact of the incident increases.
Automated Ticket Routing Supported by ML
To ensure accurate routing, automation rules rely heavily on data like categories and subcategories when end users submit a ticket. ML helps facilitate this process by providing end-users with suggestions for the most relevant categories and subcategories for a given ticket.
