Making the help desk even more helpful

The help desk support technician who can quickly find answers and solve an IT application user’s problem is the unsung hero of any IT department or firm, especially for Managed Service Providers (MSPs).

MSPs have been around for over two decades, ever since companies realized that it was more cost effective to focus on their core competencies and let someone else manage their IT. Often, the same help desk engineer at an MSP will be asked to troubleshoot multiple applications supporting vastly different customers in the course of a single shift. Yet, even when the help desk closes a ticket, about 50% of customers feel that their problem has not been resolved adequately.

The founders of CrushBank know firsthand the challenges that IT support staff face in trying to provide personalized service. For more than 20 years, they operated an MSP in the New York metropolitan area that supported several lines of business for customers ranging from 100-person law firms to 1,500-person medical practices and everything in between.

Learn more about IBM Watson® Discovery

Help desk engineers are expected to be experts in both the IT applications and in their customers’ specific configurations, history and issues. When customers call in to the help desk with a problem, they expect that the presumed expert will resolve it without excuses, and without delay. CrushBank recognized that with the growing layers of technology piling up in most companies, those expectations of instant resolution were becoming nearly impossible for help desk staff to meet.

According to Brian Mullaney, Principal and Chief Revenue Officer at CrushBank, this current information-provision model is proving increasingly inefficient and costly to the MSP for several reasons.

First, there is the vast amount of information that the help desk engineer must sift through. “It’s a struggle for these organizations to extract all that data and turn it into useful information on the spot while they’re being challenged and bombarded by their clients on the phone,” he says. “Eighty percent of the data that IT firms are accessing is unstructured. It’s not in a metadata field that you can pull out of a database.”

In Mullaney’s experience, around 50% of an engineer’s time is spent just searching for information before he or she can even begin to troubleshoot the customer’s problem. This leads to a second problem for firms: a direct impact on their bottom line. Help desk engineers are paid to solve problems, but only half their time is spent doing so. As he points out, “Half of [their salary] is going to just finding information before the first morsel of technical competency is leveraged ... . ”

Finally, the reality is that highly experienced and knowledgeable IT help desk personnel are getting harder to find and keep. Most IT graduates now gravitate toward jobs in application development. Further compounding the problem is the high turnover rate among personnel—38.3% every year, according to Mullaney. So companies that invest the six months of time and expense to train and onboard help desk engineers see that money walk out the door only 18 months later.

CrushBank approached IBM and soon became one of the original IBM Watson ecosystem partners using Watson application programming interfaces (APIs) for business purposes. As CrushBank experimented with the early Watson Natural Language Processing (NLP) products and APIs, it became clear that the machine learning and AI technology could be turned into a viable offering to other service providers.

In early 2019, CrushBank launched its eponymous CrushBank solution running on the IBM Watson Discovery platform to perform AI-assisted searches that enable help desk personnel to quickly find the most relevant information to solve customers’ problems. The solution takes in an organization’s structured and unstructured support information, interprets it using machine learning algorithms and presents it to the help desk engineer in a useable format.

CrushBank hosts the software as a service (SaaS) solution to MSP and industry customers on a per-user basis. It comes preloaded and pretrained with documentation from key manufacturers such as Microsoft and trusted community expert updates from StackExchange. CrushBank then adds all the relevant support information from its customers’ systems, including unstructured data such as call logs and ticket notes, into the IBM Watson Discovery platform.

To quickly find product and customer information, help desk engineers are able to query all the resources that they would typically retrieve from separate systems using a single-pane-of-glass web interface. The machine learning capabilities of the IBM Watson Discovery solution continuously refine and improve its search and results capabilities. This continuous filtering ultimately creates a bank of intellectual property that help desk workers can tap into for instant answers.

Even the smallest firm of 5–10 employees can use the CrushBank solution. And, in a marketplace that constantly changes through a rising number of mergers and acquisitions, the solution becomes even more valuable and important, according to Mullaney. “Every time you put two companies together, that’s two systems that don’t talk to each other,” he says. “And CrushBank can pull those systems together and make them intelligent and legible from one dashboard.”

Early on, CrushBank realized that teaming with IBM would allow it to focus on the front-end user interface (UI) and user experience (UX), while IBM continues to improve and enhance the underlying AI technology behind its solution. “We’re a faster, more responsive, more agile organization because somebody bigger and better is dealing with the platform,” says Tan.

CrushBank recently launched two new services based on its proprietary offering and IBM Watson Discovery technology.

The first, Resolve, simplifies the help desk engineers’ work even further. They select an assigned ticket and click “work on ticket,” and the CrushBank application returns the best suggested information from the available resources. “It threads the results onto one pane of glass listed in order of clearly identified and order of confidence,” says Tan. It further speeds the problem-resolution process and provides information that a newer user might not otherwise know to look for or consider.

The other service, Insight, as its name suggests, uses the power of the IBM Watson Discovery platform to help MSPs uncover insights that previously lay buried in the vast repository of their help desk interaction data. A key feature of the Insight module is root cause analysis. Before developing this solution, a customer might not notice an emerging problem with one of its supported systems unless tickets were very well categorized and tagged up front, which is often not the case. Although 10 calls or tickets might have the same root cause, a problem can manifest itself in different ways, or end users might report it differently.

Tan explains: “Sometimes someone will call up and say, ‘I can’t log in to my system.’ Sometimes someone will say they can’t log in to Citrix. Sometimes someone will say, ‘my password doesn’t work.’ All of those may have the same exact cause and resolution. And once people actually start working on it and put their notes in, [Insight] can highlight that and pull that out and make that information available.”

Ultimately, the CrushBank solutions enable help desk employees to work smarter, not harder, with the help of AI. As Mullaney says, “It’s about taking the efficiencies that are available and driving them down to the employees to make them better employees.”