Guest Column | June 13, 2018

AI, AR, And Combating The Ongoing Technician Brain-Drain

By Tom Paquin, Market Insights Analyst, Aberdeen

AI and AR

Many years ago, before I was a Service Analyst, I was a Service Technician. What I learned in those early years of my career continues to shade my understanding of field service operations across industries, crystalized in one fact: Being a novice technician is hard.

I still remember one of my first customer interactions. I had read all the training manuals. I had run the diagnostics. Still, the machine was only giving me very ambiguous symptoms. I had no idea what was causing it to fail.

“Don’t you know how to fix it?” the increasingly agitated customer asked me. I did know how to fix it. I had memorized and prepared for every possible scenario. I just had no idea what was wrong with it.

There seems to be a prevailing wisdom that a technician needs simply show up, flip the “broken” switch on your serviceable asset to “not broken,” and gallop triumphantly to the next job. But newer technicians, even with fresh training, often lack the experience needed to diagnose and manage problems as quickly as possible. Isolating issues is rarely black-and-white, technicians don’t know what they don’t know, and greener employees are much less likely to have “seen it all.”

Experience will always be the most important measure of a great technician. Unfortunately for service, with many industries seeing nearly 50 percent technician turnover, a lengthy ramp-up is becoming an unaffordable luxury. Business needs move quickly, technologies serviced change rapidly, and there’s already a labor shortage in service. So—for those employees that are left, what can organizations do to give technicians the building blocks to seasoned success, while enabling them to efficiently tackle today’s challenges?

The Value Of Knowledge Sharing Among Field Technicians

The most obvious thing to start with is knowledge sharing, and it’s a relatively low bar—get your field workers in contact with someone who’s done the job repeatedly and can map out the possible causes of an issue. But there’s quite a bit that’s improved the way that this is managed since the days of call centers and hold music. Consider the role of augmented reality (AR). By using a device’s camera to create a dynamic workspace, technicians can work alongside more seasoned off-site employees, who can provide audio instructions or put annotations on the screen.

As an added bonus: take the technician out of this scenario, and there’s something even more interesting here—the opportunity for remote resolution and guided self-service. Using visual utilities is not always the best way to diagnose problems, but combined with internal sensor data, this could effectively save a truck roll, and allow your technicians to close more tickets in a day.

There are some drawbacks to this, of course. Performing these measures on a consumer device like a phone or a tablet and your hands are suddenly occupied. Wearables can solve that problem, but today’s wearable leaders still produce headsets that can’t be worn comfortably for more than fifteen minutes. This tech has some growing to do, still, but the time to lay the groundwork is now. You can always adjust the execution as your experience changes.

Another way to support knowledge sharing? Artificial intelligence (AI). AI gets bandied about from time to time with respect to service interactions, mostly on the call center side, but consider its usefulness for the novice technician. An AI system, at least today, lacks the instinct, dynamism, and rugged good looks of the average service technician, sure — but there’s one area in which these systems can be invaluable: good AI knows every interaction, every symptom, and every workflow that would be needed on-site. They never need to check their notes to make sure they’re doing things correctly. Additionally, AI systems can weigh scenarios based on historical interaction data and recommend the appropriate customer service fix, in the event that the firm needs to go above and beyond to save a customer relationship.

In speaking with some executives that are employing AI for certain systems, especially for remote resolution, the prevailing wisdom is to make interactions AI-first, with the ability for a human to intercede if the AI can’t perform the task. I’d argue that you should flip that on its head, and start with a human who can be fed information in real-time from the AI. Think of it as a machine-augmented technician force.

Years ago, when I didn’t know what to do, I had to call a more seasoned tech in to help with my repair. They quickly identified the issue, but bringing them on-site not only wasted time and manpower, it was the end of my credibility with the customer. Back then, this was the only solution. Hopefully soon, for all technicians, there will be a better way.