Daily Archives: July 2, 2017

Kal Juman, principal of Industry Labs and business sales consultant; Imran Abdool, president of Blue Krystal Technologies and Business Insights, and lecturer on finance, economics, and strategy at the University of Windsor; Richard Douglas-Chin, associate professor, English Literature, University of Windsor

In their continual quest to cut costs, boost revenue and maximize shareholders value, todays corporate bosses have made automation their standard modus operandi.

However, what is often good at the individual firm level is problematic at the societal one: automation has meant bigger bottom lines for shareholders at the expense of less-skilled workers becoming unemployed or underemployed. With the rise of populist politicians in America and Europe, companies would be well-placed to rethink their level of automation going forward.

There are two important aspects to increased automation: brand experience and long-term strategic planning. Automation affects brand experience through reduced or even eliminated interaction with the customer. Almost everyone has heard an anecdotal story of a frustrating experience with a self-service or self-checkout counter. Automation has touched all industries; even law and finance have now seen their consumer-interaction significantly eroded. At the corporate level, increased automation represents a trade-off between brand experience and cost savings. The challenge for companies is to find the optimal level in this trade-off, but the difficulty arises in comparing a tangible quantity (cost savings) with an intangible one (brand experience).

The iconic retailer Sears has had ailing brand experience for years preceding its current financial decline. During Sears profitable years the company hastily paid out excess cash to shareholders rather than reinvesting in Sears in-store experience. In decades past, Sears had a unique brand experience. Now, Craftsman has been sold off from the larger Sears Holding Corp. and the fate of Kenmore is questionable too. Without a unique brand experience, Sears bricks-and-mortar stores cannot compete on price point and convenience with online retailers such as Amazon. Sears failed to utilize its vast inventory, cataloging and corporate resources for a first-mover advantage in online retailing before Alibaba and Amazon.

Conversely, when brand experience is successful, a premium can be charged for that success. For example, Apple is famed for its achievement in developing its brand and its ensuing customer experience. Walk into any Apple store and compare first-hand this experience with another technology retailer. One of Apples star products, the iPhone at its most basic functional level is no different from similar products, but the Apple experience always commands a price premium.

Being cognizant of the trade-off between automation and brand experience not only benefits corporate shareholders but our broader society as well. Two futures can exist in the relationship between corporations and their workers: one where corporations have higher profits and less employment or one where employment and corporate profits rise in tandem. A company can boost innovation, profits and employment by combining risk-taking with empathy for consumers and workers.

It can be argued that a companys present stock price captures the markets perceptions of automation benefiting a company this is a standard assumption of modern stock pricing in which the current price is based on all available information. However, it can also be argued that market perceptions can and have been significantly wrong e.g., the dot-com bubble, the recent subprime crisis and behavioural finance research. Therefore, current financial markets may be overvaluing automation.

With regard to strategic planning, its no secret that investors and financiers are short-term rather than long-term oriented. Wall Streets culture, as well as the high speed of Internet communication, promote bonuses reflecting short-term performance demarcated by quarterly or annual time frames. The recent incident involving a United Airlines (UA) flight and the forceful removal of one of its passengers demonstrates how quickly capital markets react to perceived company performance: immediately after this story broke, UA stock was down 4 per cent in the next mornings trading reflecting the speed of capital markets and also consumers swift negative judgment on UAs brand experience.

Perhaps it is time for a novel approach: link corporate bonuses to a long-term performance horizon. Specifically, CEOs shouldnt leave with a golden parachute or be able to cash out stock at current prices. Instead, there should be a time delay of five to 10 years before cashing out a significant portion of their stock thereby aligning their incentive with long-term corporate (and incidentally societal) good.

This trend is already beginning: the number of IPOs in America has fallen significantly over time. Private capital markets are seen as longer-term oriented than their public counterparts. Company founders and stakeholders are beginning to express their preference for this type of governance and financing. They are recognizing that automation can be a substitute or a complement, and with proper planning the latter is quite profitable.

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Companies must strike a balance between automation and brand experience - The Globe and Mail

The bankers are not yet ready to buy into dystopian visions in which robots render humans superfluous. But they are seriously discussing the risk that artificial intelligence could eliminate jobs on a scale that would dwarf previous waves of technological change.

SINTRA, Portugal The rise of robots has long been a topic for sci-fi best-sellers and video games and, as of last week, a threat officially taken seriously by central bankers.

The bankers are not yet ready to buy into dystopian visions in which robots render humans superfluous. But, at an exclusive gathering at a golf resort near Lisbon, the big minds of monetary policy were seriously discussing the risk that artificial intelligence could eliminate jobs on a scale that would dwarf previous waves of technological change.

There is no question we are in an era of people asking, Is the Robocalpyse upon us? David Autor, a professor of economics at the Massachusetts Institute of Technology, told an audience Tuesday that included Mario Draghi, the president of the European Central Bank, James Bullard, president of the Federal Reserve Bank of St. Louis, and dozens of other top central bankers and economists.

The discussion occurred as economists were more optimistic than they had been for a decade about growth. Draghi used the occasion to signal that the European Central Bank is edging closer to the day when it will begin paring measures intended to keep interest rates very low and bolster the economy.

All the signs now point to a strengthening and broadening recovery in the euro area, Draghi said. His comments pushed the euro to almost its highest level in a year, though it later gave up some of the gains.

But along with the optimism is a fear that the economic expansion might bypass large swaths of the population, in part because a growing number of jobs could be replaced by computers capable of learning artificial intelligence.

Policymakers and economists conceded that they have not paid enough attention to how much technology has hurt the earning power of some segments of society, or planned to address the concerns of those who have lost out. That has, in part, nourished the political populism that contributed to Britains vote a year ago to leave the European Union, and the election of President Donald Trump.

Generally speaking, economic growth is a good thing, Ben Bernanke, a former chairman of the Federal Reserve, said at the forum. But, as recent political developments have brought home, growth is not always enough.

In the past, technical advances caused temporary disruptions but ultimately improved living standards, creating new categories of employment along the way. Farm machinery displaced farmworkers but eventually they found better paying jobs, and today their great-grandchildren may design video games.

But artificial intelligence threatens broad categories of jobs previously seen as safe from automation, such as legal assistants, corporate auditors and investment managers. Large groups of people could become obsolete, suffering the same fate as plow horses after the invention of the tractor.

More and more, we are seeing economists saying, This time could be different, said Autor, who presented a paper on the subject that he wrote with Anna Salomons, an associate professor at the Utrecht University School of Economics in the Netherlands.

Central bankers have begun examining the effect of technology on employment because it might help solve several economic quandaries.

Why is workers share of total earnings declining, even though unemployment is at record lows and corporate profits at record highs? Why is productivity the amount that a given worker produces stuck in neutral?

The mere fact that we are organizing this conference here in Sintra testifies to our interest in that discussion, Benot Coeur, a member of the European Central Banks executive board, said in an interview, referring to the Robocalpyse debate.

Of particular interest to the European Central Bank is why faster economic growth has not caused wages and prices to rise. The central bank has pulled out all the stops to stimulate the eurozone economy, cutting interest rates to zero and even below, while printing money. Four years of growth have led to the creation of 6.4 million jobs. Yet inflation remains well below the banks official target of below, but close to, 2 percent.

One explanation is that more work is being done by advanced computers, with the rewards flowing to the narrow elite that owns them.

Still, among the economists in Sintra there was plenty of skepticism about whether the Robocalpyse is nigh.

Since the beginning of the industrial age, almost every major technological innovation has led to dire predictions that humans were being permanently replaced by machines.

While some kinds of jobs were lost forever, greater efficiency led to more affordable goods and other industries soaked up the excess workers. Few people alive today would want to return to the late 1800s, when 40 percent of Americans worked on farms.

Robocalpyse advocates underestimate the power of scientific advances to beget more scientific advances, said Joel Mokyr, a professor at Northwestern University who studies the history of economics.

Think about what computers are doing to our ability to discover science, Mokyr said during a panel discussion, citing computers that can solve equations that have baffled mathematicians for decades. There may be breakthroughs that we cant even begin to imagine.

There are other explanations for stagnant wages besides technology.

Companies in Japan, the United States and Europe are sitting on hoards of cash, doling out the money to shareholders rather than investing in new buildings, equipment or innovative products. Just why is another topic of debate.

Hal Varian, the chief economist at Google whose self-driving technology may someday make taxi drivers unnecessary said that the plunging cost of information technology has virtually eliminated the fixed cost of entering a business. Companies can rent software and computing power over the internet.

And flat wages reflect the large number of women who have entered the workforce in recent decades as well as the post-World War II baby boom, Varian said, adding that those trends have run their course. We are going to see a higher share going to labor, he said.

Yet already, disruptions caused by technology help account for rampant pessimism among working-class and middle-class people across the developed world.

Bernanke referred to polls showing that about twice as many Americans say the United States is on the wrong track than say the country is moving in the right direction.

As a result, last November Americans elected as president a candidate with a dystopian view of the economy, Bernanke said.

Autor concluded that it was too early to say that robots are coming for peoples jobs. But it could still happen in the future.

I say not Robocalpyse now, Autor said, perhaps Robocalpyse later.

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Robocalpyse now? Central bankers argue whether automation will kill jobs - The Seattle Times

USA TODAY

Automation saved this American manufacturer USA TODAY Marlin Steel in Baltimore, Maryland, was able to stay in business by automating its processes to stay competitive when many other manufacturing jobs went overseas. Video by Jasper Colt, USA TODAY ...

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Automation saved this American manufacturer - USA TODAY

We are still in the tail of the third industrial or digital revolution where investment in digitalisation could drive significant productivity gains, noted analysts from investment bank Morgan Stanley in a September 2016 report entitled Disruptions and productivity growth in the next decade of the digital revolution.

The digital revolution represents the move towards data-driven business. The computerisation of business is continually generating vast quantities of data. That information is fuelling the use of automated decision-making systems withinfinance.

I am very optimistic about where we are going, says John Lowrey, global head of electronic markets in equities at Citi, the banking giant. Training artificial intelligence systems requires large datasets. Those who have the most data are the most able to adapt to the new environment and of course the banks and investment banks have reams of data. By 2020 we will really see radical change in the environment.

That change is very apparent in capital markets. While many people still think of traders as brightly jacketed men shouting in a trading pit, and a few think of men and women staring at screens while shouting into telephones, very few people picture a computer server clicking away, making millions of decisions.

This move towards automated trading, which began in the late-1990s and early-2000s, across the banking and asset management environment was driven by two factors. Firstly, traders cost a lot of money and are fallible, and so reducing their number reduced costs. Secondly, many of their simpler tasks were time consuming and ate into their ability to tackle complicated problems.

However, the first stages of automation were rule-based decision-making systems, algorithms that took an input and triggered an automated response. Any change in market circumstances required a platform to have its parameters altered.

Now smarter systems are being developed, capable of learning, which can be trained across datasets and then adapt to changes in circumstance. These can be applied to a considerable range of processes by innovative financial servicesfirms.

Joseph Pinto, global chief operating officer at AXA Investment Managers, says: We are looking at automation on three levels. Firstly, how can we use big data and eventually artificial intelligence to provide new signals for our portfolio managers? Secondly, we are using machine-learning processes or automation to process a lot of data on customers, for example movement of inflows, outflows and trying to anticipate customer behaviour. The third layer is more traditional, sitting down with our providers and ensuring they can automate their process to lowerfees.

These automated trading systems are not only getting smarter, but as wider datasets become available, machine-learning systems can be used to understand a wide variety of inputs. The inclusion of internet-enabled sensors within devices ranging from cars to shipping containers to toasters is creating the internet of things, a vision of the physical world represented indata.

At the same time, the increased surveillance of every aspect of life, and the capacity of machines to search images and text as well as tables of figures, just as search engines do across the internet, creates the potential for running searches just as powerful across financially sensitive information.

Bartt Charles Kellerman, chief executive of hedge fund consulting firm Global Capital Acquisition, says: In the past there was a guy with a counting device standing outside a concrete manufacturer, or outside a housing project, counting the number of trucks going in and out. Thats grown by leaps and bounds, so everything that moves is going to be monitored and fed into some centralised cloud, which is then going to be examined and cross-examined as a reflection of whether or not that data is going to impact a potential marketmove.

These technologies are already much in evidence outside of the financial services environment. From search engines to shopping assistants they are becoming increasingly prevalent. However, applying these to the management of money requires a considerable level of trust. Even smart automation requires oversight and risk management. Nor can there be a lack of transparency as regulators and investors both require insight into the decision-making process.

These are complex ideas when you use automation just for the investment process, or deep-learning or machine-learning, says Mr Pinto. And you need a simple way to explain it to your customers; you cannot sell it as a black box for sure. Thats the big challenge. So we are investing time and effort in creating transparency for users and clients, including creating tools like data visualisation. We find it really makes a big difference. The past is littered with opaque technologies that, when difficult to diagnose, were quickly abandoned byclients.

Nex Group, formerly ICAP, has been looking at automation to further the post-trade and back-office services it provides to clients via NEX Optimisation division.

A lot of automation we are providing is to make things more efficient for our clients, says Chuck Ocheret, chief innovation officer at NEX Optimisation. Thats been our mainpurpose.

Ironically, the most interesting automation can sometimes involve the more day-to-day tasks. The development of computer code, particularly the testing process, can be automated. When the firm takes on data from its customers, NEX Optimisation can automate the mapping out of defined fields, to assess where they belong in its own dataset. Although lots of data formats are standardised, firms still manage to create unique interpretations of these standards.

Mr Ocheret says: If you can automate those processes, learn from training sets how data is sent in and some of the weird variations that occur, then you can automate a lot of that stuff with relatively straightforward machine-learning.

Where clients are sending data for a single specific service, automation can allow that data to be reused for multiple purposes. A client may provide all their trade data to generate reports to the relevant regulators. Through the use of smart automation this could be used to run an evaluation or a reconciliation. The broader the datasets, the more insight you can offer to the clients, Mr Ocheretsays.

This is reducing the need to throw people at a task, but is also creating situations in which people would not be able to perform due to the sheer volume ofdata.

David Thompson, chief operating officer at NEX Optimisation, says: A fear around this kind of automation is that its going to get rid of jobs or positions, but actually there is a huge amount of additional opportunity, which is going to be provided by ensuring resources are focused where they add the mostvalue.

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Algorithmic trading ushers in new era of market automation - Raconteur