Discover PerformanceHP Software's community for IT leaders // September 2014
Can Big Data save your help desk?
People are messy, compared to your structured help desk systems. Soon, Big Data tools will make service desk interactions a little more human.
By Mike Shaw, HP Software Strategic Marketing
Sadly, we are not judged on our performance during normal operations. It’s when something goes wrong that our customers form their strongest opinions of us—and switch to our competition, and condemn us loudly via social media. Interactions with a help desk—whether it’s an IT service desk, a tax agency’s, or an insurance company’s—are vital to success in the age of the software-defined enterprise. That’s why finding ways to turn the help desk experience into a positive and engaging one is so important—and part of the changes we’ll see Big Data bring to IT in the years ahead.
A key challenge is that the help desk is approached by humans, who like to interact like humans—in strings of text or spoken words. Yet our help desks organize and deliver information in structured records, creating a rigid, unnatural, and often frustrating experience for the user. No one wants to conform to an artificial system of record. Businesses will have to find ways to deliver what IT guru Geoffrey Moore calls “systems of engagement,” which humans can approach … as humans.
Moving forward, Big Data analytics tools that understand speech, text, and pictures will augment our help desks. These will let us create applications that engage with people more naturally and produce results more quickly, with fewer escalations to (and failures in) the call center, and fewer angry Facebook posts. Let’s look at the ways your analytics evolution will let your help desk deliver a more engaging experience.
How Big Data will help your help desk
1. Auto-augmenting a conversation with relevant information.
As your help desk agent chats with a customer, the Big Data system will interpret the conversation, understanding what you are talking about. It will then search for relevant information and display it to the help desk agent.
2. Automatic entry and categorization of cases.
Imagine that an application crashes on your PC. You could use a mobile app to take a picture of the error message on your screen and send it to the IT service desk system. Analytics tools would use optical character recognition to understand the image and automatically categorize the incident. This makes case entry so much easier for your users and the help desk agents.
3. Easy, forgiving searches.
It is frustrating for customers that they have to know exactly how you have arranged the information in your help desk—the knowledge articles, known problems, and the like. So, give customers’ search strings to a smarter analytics tool, and it will give back all the different keywords your help desk needs to search for. This gives your help desk Google-like search flexibility.
4. Automatic clustering of search topics.
Big Data analytics tools will automatically cluster the topics people search for on your help system. You’ll then see which topics are well served by your help system, and which need to be augmented. You might determine that there are lots of searches of your insurance help system regarding making claims while abroad, but that your help topics really don’t serve that topic very well.
5. Automatic clustering of calls into problem areas.
The IT standard for service management, ITIL, calls for incidents to be grouped into problems. For example, there may be hundreds of open incidents that relate to issues with the company’s VPN. These would then result in a problem being raised, perhaps calling for an increase in the capacity of the VPN system. While it’s difficult, or slow and costly, for humans to go through hundreds or thousands of incidents, an advanced analytics tool could automatically understand and cluster the incidents. Service desk agents can then view each cluster to decide whether to create a problem.
The use of Big Data tools to assist in incident-to-problem clustering is not unique to IT service desks—it can be applied to any help desk situation.
6. Clustering and sentiment analysis of community activity “out there.”
The prevalence of social media means that your help desk is just the tip of the iceberg when it comes to customer dissatisfaction. My daughter recently faced a severe delay on her train journey returning home from university. She tweeted her frustration using the hash tag for the rail operator. To her amazement, she was tweeted by someone from the rail operator, apologizing and offering an alternative route for her trip. A lack of delay would have been best, but she was impressed that social media was being monitored—and helpful actions were being taken.
Big Data tools allow you to monitor a whole series of social media sources, including, of course, Twitter. You can look for clustering of conversations (“Lots of people are talking about making insurance claims when traveling abroad”). You can then monitor sentiment (“People are very frustrated at how difficult it is to make these claims, and the frustration is increasing”).
An analytic approach to your customers
Humans interact in spoken word, in text strings, and with pictures. And it’s not always the help desk that they turn to when they want to vent their frustrations—in fact, the help desk is a last resort.
The increasing ability of Big Data analytics tools to understand human interaction allows us to make our help desks more customer-friendly and more proactive for the needs of our users—who are increasingly satisfied with nothing less.
Mike Shaw’s recent columns on Big Data form the core of the new Enterprise 20/20 chapter, "Big Data 20/20," which looks at the transformative future of advanced analytics. Download the complete chapter on our Enterprise 20/20 page.
For more on extracting social knowledge for the help desk, check out the white paper, “Turn data into knowledge: Social collaboration empowers a more intelligent service desk,” in our "relevant help desk" toolkit (reg. req’d).
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