Self-Driving Cars and Self-Service Contact Centers: How Close are We?

Remember the days of travel before GPS? The days where we were dependent on AAA, purchasing large, clunky maps that often caused strife on many a family road trip?   

You would buy whatever maps that covered all the places you might want to go. Then to get to your destination, it was up to you to know where you were, find where you wanted to go, and then interpret on the map the best way to get there. These maps had limitations. Along the way, if you made a wrong turn, you would have to figure out where you were again and determine the best way back to your route. Also, they contained no information on traffic jams, construction, or weather conditions. How much further to your destination? How long would it take to get there? When would you need gas? We had to figure all of this on our own.   

Of course, no one uses paper maps for driving anymore because we have GPS navigation systems.    

GPS is a great example of Intelligence Augmentation (IA). IA is the use of technology to enhance human thought or action in a way that makes humans more capable. Or in the context of our contact center world, to make an agent more effective at resolving customer issues.   

When we first started using technology to augment humans’ ability to drive, tools like MapQuest used mapping data to determine the best route between two points and then spat out a list of directions. Then you would print it out and take it with you in the car. Not long after MapQuest came around, you could buy a device that used GPS satellites to locate your vehicle and give you real-time directions, adjusting the route as you go. Eventually, weather and traffic data were added to these devices to provide more information and more helpful directions. And later on, the car manufacturers stepped up their game by adding things like self-parking features, lane-keeping assist, and dynamic cruise control to enhance the driver’s abilities further.  

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Today, as we get closer to the promise land of fully self-driving cars, the driver is becoming less and less necessary. But let’s examine how we got to this point.   

We began with a PROCESS (the road) and a person (driver).   

Then building on this foundation, we layered in technology as it became available to augment the human so that over time less and less involvement was required of the driver. Today, when assessing the capabilities of self-driving cars, manufacturers are measured by the number of miles a car can go without a human having to touch the wheel. So, by continually augmenting drivers with new technology, we have taken the idea of self-driving cars from the stuff of science fiction to the imminent reality it is today. It has been an iterative process that incorporated new capabilities that augment the driver until, ultimately, we have a holistic, comprehensive, and interconnected technology environment that can facilitate any drive, whether you’re headed across town or the country.   

For those of us in the contact center industry, perhaps you’ve dreamt of a future in which technology can handle any customer issue correctly, efficiently, and entirely autonomously, much like a self-driving car. There is certainly no shortage of technologies available to contact centers that get us closer to that goal. Robotic Process Automation (RPA), chatbots, workflow engines, Natural Language Processing (NLP), and Artificial Intelligence (AI)—the list goes on. We’ve seen many contact centers add new technology to either create a better self-service customer experience or reduce costs by limiting human involvement until absolutely necessary. But, the spend on technology for contact centers often seems to be focused on the promise and hype of any given technology. So, the holistic, comprehensive, and interconnected technology environment that exists for self-driving cars remain elusive for contact centers.   

What if we took the same approach to contact centers that we took with creating self-driving cars?  

What technology would we add first? To build an autonomous vehicle, we wouldn’t just bolt on technology like satellite positioning or artificial intelligence without planning how those technologies fit into the larger mission. But if we focus on enhancing the human behind the wheel, we could, for example, start by adding mapping data that tells the driver the most direct route. We get an objectively better process that is easy to adopt because it provides an obvious and immediate benefit, even without all the other technologies needed for an autonomous car. Then maybe we add more technology like GPS data for real-time turn-by-turn directions. We still wouldn’t have a self-driving car, but again, adoption isn’t a challenge because the benefits are obvious and immediate, we’re one step closer to peak automation, AND we get to enjoy the benefits of a smoother process in the meantime.   

A fully-automated contact center isn’t always the end goal because there is value in the human connection an agent can develop with our customers. But initially, maybe we can handle 20 calls out of 100 autonomously. Then as we continue to iterate, 50 out of 100 calls and so on. The point is with a process clearly defined, we can add technology to augment the humans involved in that process and simultaneously reduce the need for human interaction on some calls while improving the efficiency, accuracy, and experience of the complex calls that remain.   

The key is Intelligence Augmentation. With your vision in mind, you start with a PROCESS (map) and a human (a driver). Then focus on adding technology to that process to automate calls when possible and augments the agents handling the remaining complex calls to be as efficient and accurate as possible. Following this plan is the key to creating a technology environment that reduces costs, provides your customers with a seamless interaction, and creates differentiation and a competitive advantage for your organization.  

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