Big Data Was The Beginning: What Comes Next

Author

Michael Fertik, Contributor

June 16, 2015

When the boss looks to you first for your take on an issue – not just one time, but every time. When the concept of a “budget” is something you understand in theory but never need to put in practice. When companies court you for sponsorships because everyone knows your casually posed, perfectly presented Instagrams.

Clout, money, fame: these have always been the traditional markers of power. But guess what? We’re in the Reputation Economy now and in this new paradigm, the typical hallmarks of power are just data points – and merely a few at that. They’re among the thousands of pixels that make up both the frame and detail of you. Say goodbye to Big Data as a dominant concept – it’s time to recognize its evolutionary next leap: Big Analysis.

If Big Data is the oil well, full of potential, Big Analysis is the finished product: the fuel companies need and value. It exists for three reasons:

First, it’s now incredibly cheap – and by cheap, I mean very nearly costless – to store vast quantities of data. The amount of data in the world a year ago was just over 2.1 zettabytes and it’s predicted that we’ll see the first 60 terabyte desktop hard drive in just 6 years, though that may be a conservative estimate. Contrast that with the launch of the first Mac in 1984, boasting a whopping 128K of memory. It’s almost unimaginably rapid progress. Forget the tortoise and the hare – this is the tortoise and the Hennessy Venom GT.

Second, our ability to make sense of that data has also grown exponentially – and it’s substantially improving. For good and for worse, Big Analysis has transformed the promise of Big Data into reality. Those digital dossiers we’ve all heard of have always been real. But in the Big Data era, they were like the prehistoric drawings of cave-dwellers: fascinating but certainly primitive when compared with where we’re going. With Big Analysis, these dossiers are becoming more and more accurate. Why? Big Analysis is leveraging all sorts of data about you, me and pretty much everyone in the world – using demographic data, social media habits, purchasing power, job experience, political preferences, search history and more. The result is not just pinpoint precision about who we are right now – but powerful predictive capability on who and what we might become. Companies that want to remain competitive will need this intel – to better create products that suit their markets and target advertising where it will be best received.

Third, Big Analysis is both good and bad for individuals. Companies have traditionally spent millions each year to understand their customers through conventional market research methods. But large data sets, so inexpensive to acquire and store, are treasure troves that require only the golden key of Big Analysis to unlock their value. Today’s computing power means that in quite literally the blink of an eye, nearly one billion calculations take place. That can be good – think hotel upgrades on the basis of a person’s travel history, brand loyalty and social sharing habits. But the consequences can be negative too: an insurer that decides an individual is too risky to cover at the level she needs or an employer who notes an uptick in activity on LinkedIn and concludes their best employee is on the hunt for a new job. Depending on the evaluation of an impersonal machine, people may benefit from a benevolent invisible hand – for example, receiving special offers that aren’t clearly delineated as such but welcomed nonetheless. Or they may be crushed by an imperceptible fist: denied opportunities they never even knew existed.

Does the good of Big Analysis outweigh the bad? What’s your prediction for its future impact?

This article was written by Michael Fertik from Forbes and was legally licensed through the NewsCred publisher network.


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