U.S. companies facing worker shortage race to automate

U.S. companies facing worker shortage race to automate
By David Randall

NEW YORK (Reuters) – U.S. companies are responding to the lowest unemployment rate in almost 50 years by increasing their focus on automation in order to maintain healthy margins as labor costs tick higher, a Reuters analysis of corporate earnings transcripts shows.

The attempt to save money through technology does not come down to just installing more robots in factories. Instead, companies appear to be confronting the lack of low-cost workers by investing in software and machines that can perform tasks ranging from human resources management to filling prescriptions.

Citigroup Inc, for instance, said that it is expanding its cloud infrastructure to replace routine tasks that used to require human labor. Health insurance company UnitedHealth Group told investors that its automation efforts should save the company over $1 billion next year. And Corona beer brewer Constellation Brands Inc said that its spending on automation should increase the efficiency in which it packs bottles in a variety pack, shaving costs.

Those investments are helping keep wage growth in line despite historically-low unemployment. Average hourly earnings were unchanged in October despite the unemployment rate falling to 3.5% from 3.7%, while the annual increase in wages fell slightly to 2.9%.

“I’m not at all worried about margin pressure from wages” because of increased productivity due to corporate spending on automation, said Jonathan Golub, chief U.S. equities strategist at Credit Suisse Securities.

Overall, companies have discussed automation on quarterly earnings calls more than 1,110 times since the beginning of the year, a 15% increase from this time last year and nearly double the mentions by this time in October, 2016, according to Refinitiv data. Corporate orders of robotics alone rose 7.2% over the first half of this year compared with 2018, totaling $869 million in spending, according to the Association for Advancing Automation.

Fund managers and analysts say that corporate spending on automation is contributing to positive earnings surprises. Nearly 83% of companies in the S&P 500 that have release third quarter earnings so far have reported earnings above expectations, compared with an average 65% beat rate since 1994, according to I/B/E/S data from Refinitiv.

“You’re seeing companies benefit in ways that aren’t easy to see when you look at the balance sheet, and all those investments start to add up and help protect margins,” said Matt Watson, a portfolio manager at James Investment Research.

Watson said that he is now buying companies that are benefiting from the use of automation because they trade at much more attractive valuations than the companies that provide it, which he is steering clear of.

FedEx Corp, for example, is investing in systems to both automate its shipping facilities and is testing robots that can handle some deliveries, he said. He is also buying shares of broker-dealer LPL Financial Holdings Inc, which is automating more of its client-relations platform to increase efficiency, he said.

“You don’t need to get into the nitty gritty when it’s back-of-the-napkin obvious that these companies are saving money” through increased productivity, Watson said.

The fastest-growing sectors of automation are in logistics and healthcare, said Jeremie Capron, head of research at ROBO Global, the company behind the $1.2-billion Robo Global Robotics & Automation ETF <ROBO.P>. The firm’s ETF is up nearly 20% for the year to date, in line with the performance of the benchmark S&P 500 index.

Capron sees the greatest opportunity in companies like Zebra Technologies Corp <ZBRA.O>, which makes radio-frequency identification device readers and real-time location systems that are used in hospitals and e-commerce fulfillment centers, he said. Shares of the company are up nearly 30% for the year to date.

Declining costs and a new generation of smaller systems should continue to push revenue growth in the sector, he said.

“We’ve hit the level where you don’t need great engineering skills to deploy automation because the software has made it so much easier to use,” he said. “You’re seeing not only large multi-national groups automate, but those technologies are increasingly available to smaller and mid-sized businesses.”

(Reporting by David Randall; Editing by Alden Bentley and Nick Zieminski)

U.S. companies put record number of robots to work in 2018

FILE PHOTO: Attendees look over a demonstration of industrial robots at the Omron booth during the 2019 CES in Las Vegas, Nevada, U.S. January 9, 2019. REUTERS/Steve Marcus/File Photo

(Reuters) – U.S. companies installed more robots last year than ever before, as cheaper and more flexible machines put them within reach of businesses of all sizes and in more corners of the economy beyond their traditional foothold in car plants.

Shipments hit 28,478, nearly 16 percent more than in 2017, according to data seen by Reuters that was set for release on Thursday by the Association for Advancing Automation, an industry group based in Ann Arbor, Michigan.

Shipments increased in every sector the group tracks, except automotive, where carmakers cut back after finishing a major round of tooling up for new truck models.

Other sectors boomed. Shipments to food and consumer goods companies surged 60 percent compared to the year before. Shipments to semiconductor and electronics plants were up over 50 percent, while shipments to metal producers rose 13 percent.

Pressure to automate is growing as companies seek to cut labor costs in a tight job market. Many companies that are considering bringing work back from overseas in response to the Trump administration’s trade wars may find automation the best way to stay competitive, even with higher-cost U.S. workers.

Bob Doyle, vice president of the Association for Advancing Automation, said automation is moving far beyond its traditional foothold in auto assembly plants and other large manufacturers into warehouses and smaller factories.

One of those is Metro Plastics Technologies Inc, a family-owned business in Noblesville, Indiana, which has only 125 employees and got its start in the 1970s making, among other things, mood rings. Last March, the company bought its first robot, an autonomous machine that carries finished parts from the production area to quality inspectors. In the past, that work was done by workers driving forklifts.

“We had three propane, 5,000-pound forklifts,” said Ken Hahn, the company’s president.  “We’ve eliminated those.” Hahn’s robot cost $40,000, about twice that of the cheapest option he considered, but far below the $125,000 machines also on offer.

Last year marked the first time since 2010 that auto and auto part companies failed to account for more than half of shipments, coming at just under 49 percent instead, according to the report. In 2017, over 60 percent of shipments went to automakers.

“The food industry is really starting to take off as a market for automation,” said Dan Hasley, director of sales and marketing for Kawasaki Robotics (USA) Inc, part of Japan’s Kawasaki HeavyIndustries.. He added that “food and beverage is one of the segments that really responds to tight labor markets.”

(Reporting by Timothy Aeppel; Editing by Joe White and Tom Brown)

As companies embrace AI, it’s a tech job-seeker’s market

Students wait in line to enter the University of California, Berkeley's electrical engineering and computer sciences career fair in Berkeley, California, in September. REUTERS/Ann Saphir

By Ann Saphir

SAN FRANCISCO (Reuters) – Dozens of employers looking to hire the next generation of tech employees descended on the University of California, Berkeley in September to meet students at an electrical engineering and computer science career fair.

Boris Yue, 20, was one of thousands of student attendees, threading his way among fellow job-seekers to meet recruiters.

But Yue wasn’t worried about so much potential competition.  While the job outlook for those with computer skills is generally good, Yue is in an even more rarified category: he is studying artificial intelligence, working on technology that teaches machines to learn and think in ways that mimic human cognition.

His choice of specialty makes it unlikely he will have difficulty finding work. “There is no shortage of machine learning opportunities,” he said.

He’s right.

Artificial intelligence is now being used in an ever-expanding array of products: cars that drive themselves; robots that identify and eradicate weeds; computers able to distinguish dangerous skin cancers from benign moles; and smart locks, thermostats, speakers and digital assistants that are bringing the technology into homes. At Georgia Tech, students interact with digital teaching assistants made possible by AI for an online course in machine learning.

The expanding applications for AI have also created a shortage of qualified workers in the field. Although schools across the country are adding classes, increasing enrollment and developing new programs to accommodate student demand,  there are too few potential employees with training or experience in AI.

That has big consequences.

Students attend the University of California, Berkeley's electrical engineering and computer sciences career fair in Berkeley, California, in September. REUTERS/Ann Saphir

Students attend the University of California, Berkeley’s electrical engineering and computer sciences career fair in Berkeley, California, in September. REUTERS/Ann Saphir  Too few AI-trained job-seekers has slowed hiring and impeded growth at some companies, recruiters and would-be employers told Reuters. It may also be delaying broader adoption of a technology that some economists say could spur U.S. economic growth by boosting productivity, currently growing at only about half its pre-crisis pace.

Andrew Shinn, a chip design manager at Marvell Technology Group who was recruiting interns and new grads at UC Berkeley’s career fair, said his company has had trouble hiring for AI jobs.

“We have had difficulty filling jobs for a number of years,” he said. “It does slow things down.”

“COMING OF AGE”

Many economists believe AI has the potential to change the economy’s basic trajectory in the same way that, say, electricity or the steam engine did.

“I do think artificial intelligence is … coming of age,” said St. Louis Federal Reserve Bank President James Bullard in an interview. “This will diffuse through the whole economy and will change all of our lives.”

But the speed of the transformation will depend in part on the availability of technical talent.

A shortage of trained workers “will definitely slow the rate of diffusion of the new technology and any productivity gains that accompany it,” said Chad Syverson, a professor at the University of Chicago Booth School of Business.

U.S. government data does not track job openings or hires in artificial intelligence specifically, but online job postings tracked by jobsites including Indeed, Ziprecruiter and Glassdoor show job openings for AI-related positions are surging. AI job postings as a percentage of overall job postings at Indeed nearly doubled in the past two years, according to data provided by the company. Searches on Indeed for AI jobs, meanwhile increased just 15 percent. (For a graphic, please see https://tmsnrt.rs/2CEi4eG

Universities are trying to keep up. Applicants to UC Berkeley’s doctoral program in electrical engineering and computer science numbered 300 a decade ago, but by last year had surged to 2,700, with more than half of applicants interested in AI, according to professor Pieter Abbeel. In response, the school tripled its entering class to 30 in the fall of 2017.

At the University of Illinois, professor Mark Hasegawa-Johnson last year tripled the enrollment cap on the school’s intro AI course to 300. The extra 200 seats were filled in 24 hours, he said.

Carnegie Mellon University this fall began offering the nation’s first undergraduate degree in artificial intelligence. “We feel strongly that the demand is there,” said Reid Simmons, who directs CMU’s new program. “And we are trying to supply the students to fill that demand.”

Still, a fix for the supply-demand mismatch is probably five years out, says Anthony Chamberlain, chief economist at Glassdoor. The company has algorithms that trawl job postings on company websites, and their data show AI-related job postings having doubled in the last 11 months. “The supply of people moving into this field is way below demand,” he said.

 

A JOB-SEEKER’S MARKET

The demand has driven up wages. Glassdoor estimates that average salaries for AI-related jobs advertised on company career sites rose 11 percent between October 2017 and September 2018 to $123,069 annually.

Michael Solomon, whose New York-based 10X Management rents out technologists to companies for specific projects, says his top AI engineers now command as much as $1000 an hour, more than triple the pay just five years ago, making them one of the company’s two highest paid categories, along with blockchain experts.

Liz Holm, a materials science and engineering professor at Carnegie Melon, saw the increased demand first-hand in May, when one of her graduating PhD students, who used machine learning methods for her research, was overwhelmed with job offers, none of which were in materials science and all of them AI-related. Eventually, the student took a job with Proctor & Gamble, where she uses AI to figure out where to put items on store shelves around the globe. “Companies are really hungry for these folks right now,” Holm said.

Mark Maybury, an artificial intelligence expert who was hired last year as Stanley Black and Decker’s first chief technology officer, agreed. The firm is embedding AI into the design and production of tools, he said, though he said details are not yet public.

“Have we been able to find the talent we need? Yes,” he said. “Is it expensive? Yes.”

The crunch is great news for job-seeking students with AI skills. In addition to bumping their pay and giving them more choice, they often get job offers well before they graduate.

Derek Brown, who studied artificial intelligence and cognitive science as an undergraduate at Carnegie Mellon, got a full-time post-graduation job offer from Salesforce at the start of his senior year last fall. He turned it down in favor of Facebook, where he started this past July.

(Additional reporting by Jane Lee; Editing by Greg Mitchell and Sue Horton)

Rookies and robots brace for first UK rate rise since 2007

Office lights are on at dusk in the Canary Wharf financial district, London, Britain,

By Fanny Potkin and Polina Ivanova

LONDON (Reuters) – Financial markets braced this week for what could be the Bank of England’s first rate rise in a decade – a step into the unknown for a generation of young traders who started work after 2007 but also for the state-of-the-art technology they use.

After a decade that included a global financial crash, numerous investigations into market collusion and relentless automation, trading floors at banks in London have been transformed in ways not obvious at first glance.

The newest kid on the block is not necessarily the rookie trader with a PhD in physics but the latest computer model or algorithm. How these models will perform under the almost novel circumstances of tightening monetary policy is as much a question as how the human neophytes will react.

Using past market data, assessments of demand, valuation models and even measures of how upbeat news headlines are, computers crunch the numbers, game the scenarios and buy or sell in the blink of an eye.

But shocks such as Brexit have shown that computer-driven trading can end in stampedes, or so-called flash crashes.

“You’ve got to weigh up the strength of the traders and the strength of the algorithms that have been developed and whether they can manage this kind of a process when the rate hike does come in,” said Benjamin Quinlan, CEO of financial services strategy consultancy Quinlan & Associates.

At Citibank’s expansive trading floor in London, the dealing room doesn’t look much different from a decade ago with traders hunched in front of banks of screens, the odd national flag perched on top, and television screens on mute.

But beneath the outward appearance, foreign exchange trading has undergone a seismic shift: more than 90 percent of cash transactions and a growing proportion of derivatives trades in the global $5 trillion a day FX market are done electronically.

So-called smart algos, or fully automated algorithmic trading programs that react to market movements with no human involvement, were virtually non-existent in 2007. Now, almost a third of foreign exchange trades are driven solely by algorithms, according to research firm Aite Group.

“Most of these algorithms haven’t really been tested in a rising interest rate scenario so the next few months will be crucial,” said a portfolio manager at a hedge fund in London.

To be sure, the U.S. Federal Reserve’s first rate rise in a decade in 2015 provided a dry run for this week’s UK decision – but the two economies are in very different positions and the knock-on effects on the wider financial markets of a Bank of England move are hard to predict.

 

ROOKIES AND ROBOTS

Much has changed since the Bank of England raised rates by 0.25 percent on July 5, 2007 to 5.75 percent. The first iPhone had yet to reach British shores, the country’s TVs ran on analogue signals and Northern Rock bank was alive and well.

Where once lightning decision-making and a calm head in a crisis were at a premium, the bulk of trading today is done by machines and the job of a foreign exchange sales trader is often little more than minding software and fielding client queries.

Itay Tuchman, head of global FX trading at Citi and a 20-year market veteran, said while the bank employs roughly the same number of people in currency trading as over the last few years, fewer are dedicated to business over the phone.

“We have an extensive electronic trading business, powered by our algorithmic market making platform, which is staffed by many people that have maths and science PhDs from various backgrounds,” said Tuchman, who heads trading for Citi’s global developed and emerging currency businesses.

London is the epicenter of those changes with the average daily turnover of foreign exchange trades executed directly over the phone down by a fifth to $566 billion in just three years to 2016, according to the Bank of England.

At Dutch bank ING’s London trading room, Obbe Kok, head of UK financial markets, said the floor now has about 165 people but the bank wants to make it 210 by the end of the year – searching mainly for traders attuned to technological innovations and keen on artificial intelligence.

The proportion of people employed in trading with degrees in mathematics and statistics has increased by a 58 percent over the last 10 years, Emolument, a salary benchmarking site, said.

“What banks have started to do is trade experience for technological skill and with electronic platforms growing, the average age on the floor is a bit younger,” said Adrian Ezra, CEO of financial services recruitment agency Execuzen.

 

TAPER TANTRUM

The increasing use of technology means traders can gauge the depth of market liquidity at the click of a button or quickly price an option based on volatility – a major change from a few years ago when they had to scour the market discreetly for fear of disclosing their interest to rivals.

Ala’A Saeed, global head of institutional electronic sales and one of the brains behind Citi’s trading platform FX Velocity, said its electronic programs process thousands of trades per minute.

Most of the currency trading models used by banks incorporate variables such as trading ranges, valuation metrics including trade-weighted indexes and trends in demand based on internal client orders to get a sense of which way markets are moving – and the potential impact of a new trade.

Nowadays, the models also incorporate sentiment analysis around news headlines and economic data surprises.

These electronic trading platforms also have years of financial data plugged into them with various kinds of scenario analyses, but one thing they have sometimes appeared unprepared for is a sudden change in policy direction.

Witness the market mayhem exacerbated by trend-following algorithms when Switzerland’s central bank scrapped its currency peg in 2015, or the taper tantrum in 2013 when the U.S. Federal Reserve said it would stop buying bonds.

Or Britain’s vote last year to leave the European Union.

Indeed, the biggest risk for financial markets cited by money managers in a Bank of America Merrill Lynch poll in October was a policy misstep from a major central bank.

 

EASY CREDIT, LOW VOLATILITY

One concern is that the rise in automation has coincided with a prolonged decline in market volatility as central banks from the United States to Japan have kept interest rates close to zero and spent trillions of dollars dragging long-term borrowing costs lower to try to reboot depressed economies.

While central banks have been careful to get their messages across as they end the years of stimulus, there are concerns about whether quantitative trading models can capture all the qualitative policy shifts.

For example, a growing number of investors expect the Bank of England to raise its benchmark interest rate to 0.5 percent on Nov. 2, and then leave it at that for the foreseeable future.

But futures markets are expecting another rate rise within six to nine months, injecting a new level of risk around interest rate moves and potentially boosting volatility.

Neale Jackson, a portfolio manager at 36 South Capital Advisors, a $750 million volatility hedge fund in London, said young traders have never seen an environment other than central banks supporting markets, and that has fueled risk-taking underpinned by the belief that “big brother has got our backs”.

“The problem these days is that there’s a whole generation of traders who have never seen interest rates, let alone interest rates hikes,” said Kevin Rodgers, a veteran FX trader and the author of “Why Aren’t They Shouting?”, a book about the computer revolution within financial markets.

 

(Additional reporting by Maiya Keidan and Simon Jessop; writing by Saikat Chatterjee; editing by Mike Dolan and David Clarke)