Automation Will Supplant Globalization As The Answer To Scale

Up until very recently, the answer to the problem of scale in labor intensive industries was outsourcing. The low cost of foreign labor made sending manufacturing jobs, data-entry duties, and customer service positions overseas affordable at scale — companies could hire fifty employees for the price of one American employee (not to mention the savings in operating capital and laxer labor regulations). However, as consumer demands have grown steeper and steeper, even foreign labor forces cannot keep up in a world of instant replies and two-day shipping.

What Happens When Globalization Reaches Its Tipping Point

Retail manufacturing provides a perfect example for what happens when an industry scales through foreign labor without innovating the technologies that the industry depends on.

Over the past few decades, the process by which clothing is made has remained largely unchanged. After laborers pick cotton, clean it, press it, and dye it — all with the help of automation machinery, the work becomes largely manual: humans hand-cut the fabric based on patterns and then pass it along to a different group of humans who do all of the sewing (manually, using a sewing machine).

This process is incredibly labor intensive: most factories require hundreds of workers who often labor for long hours under less-than-ideal conditions. Perhaps more important to the businesses employing them, though, is that the process is slow.

It should come as no surprise, then, that in April of 2017 Amazon filed a patent for “stitch on demand” technology that would sew clothing immediately after an order is placed. This concept would do three things:

  1. Bring manufacturing back to America (which, politically, is certainly desirable)
  2. Eliminate overstock clothing supply
  3. Increase speed and accuracy of clothing creation

In fact, a Chinese company has already begun using sewbots in a factory that will open in 2018 in Arkansas. The factory will employ 400 American workers, cut emissions by 10 percent, and will produce 1.2 million t-shirts per year at a cost that rivals even the cheapest countries for labor. Automation has hit the retail manufacturing industry, and it’s likely to completely alter the face of its labor force.

The Tip Of The Iceberg: Why Customer Service Is Next

While clothing and customer service may appear to be dissimilar industries, they have developed in similar ways. The customer service industry responded to an increase in demand at cost by sending its workforce overseas. In 2015, over 50 percent of companies had outsourced customer service to foreign labor providers, often in India or the Philippines. Recently, however, customer expectations for customer support have outpaced foreign labor supply. Eighty-six percent of customers are willing to pay more for good customer service, but only one percent of customers believe that their expectations are met. What are these expectations? Speed. Eighty-two percent of customers say that having issues resolved quickly is the most important factor for a great customer support experience.

Businesses responded much in the same way that the retail manufacturing industry did: they tried to improve speed by providing foreign laborers with new tools to increase efficiency. Through chat, IVF, automated ticket routing and automated responses, businesses were able to temporarily manage to even out supply and demand. Like the machines that processed and cleaned cotton, though, these new technologies improved customer service, but did not solve the fundamental problem.

Any Labor Intensive Industry Begs For Automation

Retail got the sewbot, customer service is getting the chatbot. While neither the retail manufacturing industry nor the customer service industry is at the point of eliminating human labor, both can significantly reduce reliance on outsourced labor, and in the process improve speed and efficiency and bring jobs back to the U.S through the use of automation.

In customer service, this means implementing decision-tree based chatbots. Like a menu, decision-based chatbots direct users down a path based on keywords. For instance, if a user asks about tracking an order, the chatbot would pick out the two keywords in that query, and direct the user to a self-service page on shipment tracking. If the user requested further help, the chatbot would direct them to an agent who specializes in shipping.

This relegates agents to a similar realm as those 400 employees in the Chinese sewing factory did. Rather than dealing with the minutiae of every ticket, agents simply oversee machines and get involved when a machine cannot deal with a problem. This dramatically reduces ticket volume that is sent to agents, thereby addressing the issue of scale.

It should not be surprising that customer service is in need of such automation: any labor intensive industry begs for it. And given the current political climate, shifting from outsourcing to automation will prove to be appealing across industries beyond retail and customer service.

Similar Posts