By Christopher Surdak

The concept of Big Data has rapidly emerged as web and telecoms-based networking has expanded on a global scale. Christopher Surdak explores how this could affect the job market in terms of the population’s talent, skill and expertise, and the impact this could have on our society and economy.

Two or three decades into the globalisation revolution, you may have noticed that the world feels smaller and smaller as the days pass. In 2014, at least five billion people have daily access to the internet. Indeed, network connectivity has become so important for survival in today’s world that many people forego other basic necessities such as food, shelter or clothing, in order to pay for and use mobile devices. Access to telecommunications allows people to obtain basic services, connect with their community and respond to emergencies when they occur. Connectivity can, however, be much more than a means of sharing one’s voice.

For many people in emerging nations, being connected to the internet is not only a means of participating in the world economy; it is their primary means of improving their living standard and lifting themselves out of poverty. According to a study by the Brookings Institute,1 the global economy may absorb over a billion new entrants into the global middle class over the coming decade; the vast majority of these people coming from underdeveloped regions of Africa, South and Central America, and Asia. These billion people will seek to lift themselves out of poverty on a wave of consumerism that is likely to stretch the global economy’s ability to grow, resulting in a wide range of consequences.

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A Glut of Genius and Drive?
One result of this growth is an ever-expanding pool of not just labour, but talent. If a billion people are looking for middle-class jobs in the coming decade, then there are millions of people who are in the top 1% of the population, in terms of intelligence, who will be competing for the best jobs out there.  Not only will these people be exceedingly bright and talented; they’ll be motivated.  This is because with all of their skills, abilities, and education, they will nonetheless be living in a hut or shanty, subsisting upon a low-quality diet, and wearing rags.  These people will see the brass ring of the middle class within their reach through the Internet and they will work tirelessly to reach the prize of a better life.

Conversely, the existing middle class in the established economies of Europe and the Americas has been shrinking over the last two decades. Many of the middle-class jobs have been replaced by technology, and many people across these continents have fallen out of the middle class due to declining educational standards, complacency, or both.  Over this same timeframe a vast number of jobs in the manufacturing and commodity services have shifted from these economies into the third world, further driving the shift in jobs and opportunities away from Western populations.

 

Human Capital in the Age of Smart Machines
The growth of the global resource and talent pool is occurring concurrently with (and, in some ways, because of) the explosion of information created by our society. People’s pervasive connectedness through their mobile devices leads to the daily generation of exabytes of data, and vast economic opportunity. Data is rapidly overtaking capital as the source of wealth and power in the world, leading to tremendous disruptions to society and business. While capital assets may be literally set in stone, data is weightless, moveable and changes hands at, or nearly at, the speed of light. In the Internet age, those who have data, and know how to use it, are the new elite of our society.

It is the combination of huge quantities of data and asking new questions that is at the heart of the Big Data revolution.

I’ve recently read several articles suggesting that Big Data is going to make talent and expertise irrelevant.  The argument goes that if getting the right answer to any particular question is only a matter of analysing a sufficiently large volume of data, then there is little need for experience or talent. People will continue to be replaced by increasingly more sophisticated software tools, which consume enormous quantities of data, extract insights, and act upon these insights almost instantaneously.  

The volumes of data that these systems can consume is far beyond a human’s ability to consume, and the speed with which these systems can make decisions and act will be dramatically beyond the abilities of mere mortals. As a result, more and more people will be marginalised by technology in the near future, exacerbating the problem of competition in the global labour market precisely at the time that a billion people are looking for value-added jobs.

 

Keeping the (Hu)Man in the Machine
While I can understand the rationale behind the perspective that smart systems will increasingly replace human intelligence in business, I believe that it is rather shortsighted and ultimately incorrect.  In fact, I would argue that in the future, talent and experience will be at a greater premium and even more highly valued than at present, which may lead to some interesting and unintended consequences.

For an analytic system to add value to a business it requires two things: data; and a question to answer.  Feed a question to a Big Data analysis tool, load it with a slew of data – and hours, minutes or seconds later, the system will present you with an answer. The more data you provide the tool and the more powerful your algorithms, the better the results will be.  Many organisations already have robust data warehousing and analytics platforms, and expanding their capability to digest petabytes of data is not a terribly difficult proposition.  

However, if all one is doing with these systems is asking the same old questions of larger quantities of the same old data, then the gains in business insights will naturally be quite limited. Your results might be slightly more accurate than before, but if a consumer’s favorite colour is “red”, or favourite flavour is “apple,” how much more “red” or “apple” can their answer become? The value derived from merely increasing the volume of data being analysed rapidly rises to a maximum, after which very little additional value can be derived regardless of how much more data you add to the analysis.

To truly transform how a business operates, you need not only more data; you need new questions. The tools will continue to become more and more powerful, and will consume more data more and more quickly – of this there is no doubt.  But, if you’re not asking new questions, eventually there are no new insights to be gained and the value of business analytics falls off quickly. It is the combination of huge quantities of data and asking new questions that is at the heart of the Big Data revolution; and it is this combination that will drive economic growth and prosperity in the foreseeable future.

Asking new questions is what human talent, insight and experience is all about.  If more and more of our synthesis of information will be performed by machines, then it is the posing of new, meaningful and insightful questions that will define a person’s economic value. Looking at the results of large-scale analytics and deriving meaning from these results is where humans will remain in the process.  Indeed they must – at least until such time as scientists and engineers create true artificial intelligence, at which point many more of us may be challenged to stay employed.

Big Data analytics are to data what levers, draft animals and wind were to the ancients, or steam power and steel were to the industrial revolution; a technical means to provide vast leverage to otherwise-limited human abilities. Horses, wind, and steam, for instance, all vastly increased our capacity to do physical work, multiplying each human input many times over in generating a valuable output. Similarly, Big Data can take a human intellectual input and multiply its leverage by hundreds, thousands or millions of times, providing dramatic leverage to a person’s productivity.

 

Better Be a Baller
This then takes us back to the question: where do people belong in a “data-fied” world? Where might those billion new middle-class workers find meaningful employment in a world powered by Big Data? For the ten million or so who are in the top 1%, they will certainly be employable and employed; they will have the talent, intelligence and skills necessary to produce dramatic results in a connected world.  

If each of these highly talented people can perform the work of thousands, and do it better than those thousands, then those other thousands suddenly become not only less valuable to organisations, they become counter-productive. If a bank presently has 10,000 loan officers reviewing and approving loans then this population represents a normal distribution for performing the task of loan review. Some percentage of these people are exceedingly good at what they do, some are exceedingly bad, and the vast majority are somewhere in the middle; the “normal” of the normal distribution.

The trouble for “normal” people arrives when we are able to leverage the ability of the top few and use their results to replace the work of the thousands in the middle of the distribution. If I were to be able to take the insight, experience, knowledge and ability of the top two, three or four loan officers (for variety’s sake not depending upon the perspective of only one person) and replicate their ability in technology, then the other 9,997 people would generate sub-optimal results. What they produce would actually create worse outcomes, and each of them would have an associated additional cost that must be met (their salary, for example). In a world of Big Data analytics, only those that create the best outcomes should be replicated in code, and this will likely be the outcome as businesses embrace these technologies over the coming decades.

This ruthless culling of those who are “less-than-the-best” among a population is nothing new to us. Indeed, our modern society is full of examples of such cases. Consider professional sports as an example: according to FIFA, the world’s football sanctioning body, there are approximately 270 million people in the world who actively play football.2 Among them, perhaps a few thousand earn any income from playing football.  Of those, only a few hundred can be the “best-of-the-best” of this population, and are rewarded for their skills and talent by earning exorbitant incomes, along with a great deal of fame and notoriety.  

Such professional “ballers” earn millions of euros per year, simply because they are at the pinnacle of a large population.  Each of these few hundred players has proven themselves to be better than millions of others, and hence they earn dramatically more income than those less talented then themselves.  Furthermore, those who fall outside of this exceedingly small percentage of “the best” earn little or nothing by way of playing football. In the cutthroat world of professional sports, those who rise to the very top of their game reap tremendous rewards; those who just miss the top end up making the same as those at the very bottom: nothing.

And this may well be the case in many other career fields as Big Data is embraced by more and more of our economy. If these technologies allow organisations to dramatically expand the thinking abilities of a handful of people, then a handful is all that they will require. They will also be compelled to hire and retain only the very best handful available. Hiring those with lesser abilities may be expedient and, in the short term, cheaper.  However, due to technical leverage, such practices will lead to such dramatically less competitive results that organisations will be forced to pay a premium for the best business minds available; precisely the same effect as we see in football or other high-
leverage professions such as acting and modeling, for instance.

 

Conclusion
This certainly bodes well for those who are at the top 1% of their given career field or expertise. Indeed, such people are likely to see their standard of living rise dramatically over the coming decade or two. Those who fall closer to the centre of their normal distribution, however, will find ever-greater competition from an ever-larger global population of knowledge workers, fighting for an ever-shrinking number of knowledge worker jobs.  And in a world where location is largely irrelevant, as long as you’re connected to the Internet, the competition for such jobs is likely to be fierce.

The upswing of all of this is that people who wish to remain relevant in an economy powered by Big Data must constantly refresh their skills, knowledge and abilities. They must strive to remain relevant and at the top of their game, in order to effectively compete with the millions of motivated, talented people entering the job market every year. For those who can maintain this frenetic pace, the rewards will be substantial.  For those who cannot, the future may be far less secure, and comfortable, than they ever expected.

About the Author

Chris Surdak cover photo-1Christopher Surdak, JD is a recognized expert in the impact of Big Data on our world, with over 25 years of professional experience. He consults with leaders from Fortune 1000 companies, national and local governments. Mr. Surdak is author of Data Crush:  How the Information Tidal Wave is Driving New Business Opportunities, by AMACOM Publishing, which is the nominee for GetAbstract’s International Book of the Year, 2014.

References
1.“The New Global Middle Class: A Cross-Over from West to East,” Homi Kharas and Geoffrey Gertz, The Wolfensohn Center for Development at Brookings, March, 2010
2. http://www.fifa.com/worldfootball/bigcount/, FIFA, 2014

 

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1 COMMENT

  1. Having just read this article today, I find it may be even more relevant than it was at its writing. Surdak is right on and so far his prediction not only remains relevant, but hugely insightful.

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