Northwest Arkansas Democrat-Gazette
Robots slow to infiltrate many workplaces
CRAIG TORRES
Vik Singh’s company has powerful artificial intelligence software that helps firms hunt down the best sales leads. The effort to get somebody to use it says a lot about the U.S. economic expansion.
U.S. businesses have every incentive to adopt labor-saving technologies, replacing factory workers with robots and desk jobs with smart software. In some areas, such as finance, machine decisionmaking is advancing quickly. In others, there are obstacles. Overall, while the penetration of automation in the economy is happening, it is taking place at a slower pace than futurists expected.
Singh tells customers how his system can help trim sales prospecting staff and increase revenue. Managers are intrigued but sometimes reluctant to entrust a hightouch business such as sales to a black box.
“They just don’t understand it,” says the co-founder and chief executive officer of Infer Inc. in Mountain View, Calif. “And they don’t believe it.”
Hundreds of companies are trying to disrupt the way we consume, work, or move. The economy’s growth potential could be higher if smart machines could turbocharge how humans go about their tasks. Higher productivity, or output per hour, would increase corporate profits and may help U.S. workers get a pay raise.
But it just isn’t happening yet.
Productivity in the U.S. rose only 1.1 percent last year. Rather than being replaced by technology, more workers are being hired. Employers have added an average 180,000 new jobs a month this year, and investment in intellectual property products, such as software, has barely edged up as a share of gross domestic product.
“Low labor productivity is the biggest problem with the story that I tell,” said Andrew McAfee, co-director at the Massachusetts Institute of Technology’s Initiative on the Digital Economy and coauthor of The Second Machine
Age, a book about the next
wave of technology. “Some of these pretty profound innovations are going to take time to diffuse.”
Social Tables is a business that helps companies with event space sell it to planners who need it, while also providing collaborative tools. The Washington-based company started using Infer Inc. about three years ago after starting a mobile app that gave it about 12,000 new sales leads.
The event space and planning market is large and varied. Sorting through those leads to find potential subscribers would have been a gigantic human task, said Trevor Lynn, the chief marketing officer. The company also turns up about 3,000 new leads a month.
Social Tables had a couple of choices: Hire an expensive database engineer or many more salespeople to sift the data. Instead, they use Infer, which sorts, queries and offers up live feedback on how the leads are performing. This kind of big-data hunting and vision would be difficult for any human to replicate in real time.
“We don’t need as many lead qualification folks,” Lynn said. While Social Tables didn’t replace anybody with Infer’s
software, “it definitely shapes your hiring map in the future,” Lynn said.
Social Tables is the typical Infer Inc. customer — a young, fast-adapting company that is looking for ways to use technology to save money and move quickly. “One less person means more decisions in a rapid manner,” Lynn said.
Getting more-established companies to use the software is challenging, said Singh, who previously worked at Alphabet Inc.’s Google. About 25 percent of Infer’s customers have been around 10 years or more.
From baggage carousels to shifting stages at a rock concert, a motor made by Southern German Electric Motor WorksEurodrive — known by its German acronym SEW-Eurodrive Inc. — is probably the workhorse making things move.
Some of the most efficient manufacturing of precision casing and gearing this German company produces happens in a bustling plant on Old Spartanburg Highway in Lyman, S.C.
In 2000, there were no robots on the factory floor. Now there is one robot for every human, most made by Japan’s Fanuc Corp.
The infusion of automation into the plant didn’t push out a single worker. Robots added scale. The plant will produce 500,000 components this year, up from 78,000 in 1999. Total staff is up just 6 percent to 148 people.
The plant is so lean that the humans are having a difficult time keeping track of all that robots need and do.
The company is looking for a system to feed data from its production machinery into a computer dashboard that gives operators a real-time look at plant performance rather than scurrying around with clipboards.
“If we can make that product a little faster without jeopardizing quality or safety, then we win,” said Melvin Story, a supervisor at the plant.
If a robot is having trouble with a line of components, a human can be on the problem more quickly. If there is a maintenance program coming up, they can do it on time before something fails.
Melding big data with manufacturing is the next step for hundreds of companies, and it is challenging, said Bryan Tantzen, head of manufacturing and industry solutions at Cisco, the networking-technology giant.
On the plant floor, he said, there is a constant need to push up profits and productivity. “I think it is really about to hit an inflection point and accelerate, and therefore drive productivity.”