Customer service is exactly what the tech industry shouldn't be trying to eliminate
I think about customer service jobs every time I'm getting a briefing in a field like robotics process automation or machine learning. I have lost count of the number of cloud-based services or business processes that are meant to reduce the client-vendor relationship to a tidily-mapped decision tree in which the customer steers through a series of decisions that make sense from the corporation's point of view, then hands over a wad of money -- without once bothering any employee at that corporation.
Sometimes, the sales pitch focuses on empowerment, as in: Think of all the people who will be empowered to fulfill their real potential once they're freed from the shackles of call-center employment.
(I once asked in a briefing, "What is it you think someone working in a Kuching container ship terminal is going to do to follow their bliss after you eliminate their job?" No good answer.)
Sometimes, the sales pitch focuses on data collection, as in: Think of how you'll be able to optimize your future business by analyzing current customer interactions and just leaning into more of that.
(I often think about how Amazon's recommendations for me read like, "You've just bought a portable air conditioner! Would you like to buy another five to round out your collection?")
Sometimes, the rhetoric focuses on eliminating human error, because an automated system designed by people and powered by computer programs written by people or written in a language that people invented won't have any errors in it.
But what if … what if we stopped saddling customer service with the nasty, gendered baggage that goes along with any skilled labor that requires identifying and meeting someone else's needs? What if we recognized that good customer service is a blend of industry-specific expertise, relationship management and marketing skills?
The one tech demo that convinced me customer service was a field with real growth potential was the Microsoft Hololens. When I participated in a demonstration of the augmented reality headset, my "job" was to repair a broken pipe. Hovering at the leftmost edge of my peripheral vision was the plumbing schematic; on the right was a call button and a live customer service rep who could hijack my ocular feed to see what I saw, then walk me through the actual repair. The entire experience -- accessing the materials for a DIY repair and chatting with the expert who could save me from my DIY ineptitude -- convinced me that what our attention economy really needs is more people who get paid for paying attention to customers.
I couldn't stop thinking about the possibilities after that demo -- imagine being a skilled contractor whose knees or back couldn't hack physical labor. Why not become an on-call troubleshooter for hire? Then I thought: This has potential for anyone who has a body of specialized knowledge and the ability to communicate well.
Concierges -- people you pay to assume the stress of specialized decision-making and iron out the details -- exist as a service for the wealthy. A smart company could offer this kind of expert labor as the competitive differentiator that sets them apart from all the other automated, frictionless, frustrating services out there. These people would be evangelists for a new way of working with tech. We have a user base in the U.S. that's already habituated to YouTube and Tiktok as vectors for instructional content, and we have a built-in user base that's already used to augmented reality thanks to premium gaming rigs and Pokemon Go; it wouldn't be hard to make attention-intensive customer service part of a revenue model -- which means expert customer agents become part of a skilled workforce and the people who collect valuable experiences and insights for making future tech even better.
Think about the growth potential for sales. While machine learning and robotics process automation do really well with easily-standardized and repetitive tasks, we are a long way off from really offloading the customer-retention type business interactions to the machines.
Think about the growth potential for jobs. Situations that require improvisation, or arise because of unique circumstances, or require defusing an emotionally labile situation still need the human touch. These so-called "soft" skills could be a long-term growth market, both for workers and for the firms that are willing to put in the resources now to develop the industry practices later.
Of course, if this going to work, we'd have to address some of gendered idiocy inherent in the idea that paying attention to and responding to a person's needs is "soft," or this type of work is owed to employers without compensation. For that to happen, the biggest "disruption" of all won't come from a revolutionary new AI-powered customer service bot -- but from how we see the people with whom we share this economy and country and world.
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FURTHER READING
"Women’s Gains in the Work Force Conceal a Problem" (New York Times, January 21, 2020) -- "The occupations that are shrinking tend to be male-dominated, like manufacturing, while those that are growing remain female-dominated, like health care and education. That puts men at a disadvantage in today’s economy — but it also ensures that the female-dominated jobs remain devalued and underpaid."
"Recognizing the Role of Emotional Labor in the On-Demand Economy" (Harvard Business Review, August 26, 2016) -- "What’s revolutionary (and troubling) about the present moment is how much companies in the on-demand economy, including Uber, are taking emotional labor for granted, especially given its centrality to their ongoing success."
"New Blue-Collar Jobs Will Survive the Rise of AI" (Bloomberg, November 1, 2018) -- "For all the technical marvels inside this fully automated, eight-year-old facility, [plant manager Lorin] Sodell talks a lot about soft skills such as trouble shooting and intuition."
"AR Will Spark the Next Big Tech Platform—Call It Mirrorworld" (Wired, February 12, 2019) -- "The mirrorworld—a term first popularized by Yale computer scientist David Gelernter—will reflect not just what something looks like but its context, meaning, and function. We will interact with it, manipulate it, and experience it like we do the real world."
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