Where’s the Money in Big Data?

So asks NY Times writer James Glanz in his recent article, “Is Big Data an Economic Big Dud?”

The short answer to his question is no. Now for the slightly longer answer.
What’s So Great About Big Data?
It may not strike you as immediately obvious why more data should be a good thing. Does the world need more YouTube videos of cats, or Facebook posts, or tracking data of your web clicks? How does that create economic value?

Simplistically, of course, the companies collecting the data, and convincing users to generate it, are doing pretty well. Facebook stock has risen back to its already phenomenal IPO valuation. YouTube turns out to have been a bargain for Google at only a $1 billion price tag. And online advertising continues to grow at double digits.

Looking deeper, the data craze builds on a more fundamental observation, brought into the ranks of corporations by the likes of Peter Drucker in the 1940s and 50s: business decisions ought to be based on data. Or at least not to contradict the data.

In the sciences, the turn to data and quantification and mathematics has been on a centuries long march that has recently penetrated into the social sciences, including psychology and marketing. One way to look at the Big Data hoopla is simply as the logical extension of this: if you have data, and you can improve business decisions — like the choice of advertising to show to users — you can make more money.

The premise is simple enough, and the results are indisputable in fields like advertising.

What’s Not So Great
Small businesses can’t benefit from data in the same way that larger ones can, because they don’t have enough customers of their own to extract trends, and improving their decisions on average may not help if they only have one store location to average across.

Big Data will benefit big businesses first. From big box stores to Big Data to mega-airline mergers, the trend is toward bigger. That’s not so great if you care about the idiosyncrasy of the small, if you like the autonomy of the mom and pop store.

As a result, small businesses have little choice but to rely on big companies to provide the data they can use. They must advertise using the aggregators, play the game of rankings and search engines and social media, and find a way to stand out in the noise.

They depend on the Amazons and Apples of the world to be their distribution channel, knowing that larger companies can copy their ideas and produce them at larger scale and lower cost if they’re successful.

Drowning in Data
Data has become too easy to collect and store. Our memories are fallible and impermanent. Our photos on Instagram reveal more than we can recall.

With inventions like Google Glass, a future where every human’s every waking moment is recorded in high fidelity 3D video is not so far-fetched.

Companies, too, can collect more data than ever before, and they can actually search through it for trends, and adjust their product strategies, advertising, and pricing based on what they find.

It’s pretty obvious that there’s money to be made from not just collecting the data, but analyzing it and acting on it as close to instantaneously as possible. In economic terms, more accurate data can lead to greater efficiency, by detecting mis-pricing and missed opportunities.

The Big Data industry has risen up to provide the technology tools so that every company, in every industry, can harness, store, search, mine, learn from, and act on the data that can help it to perform better.

Why Big Data Might Not Pan Out
With such clear benefits, why would anyone doubt the economic contribution? Here are a few legitimate concerns.

Maybe Big Data will not primarily create new value, but mainly shift the value to those who collect and use the data better than the competition, in the process enriching the companies that develop the tools.

Maybe more data will face diminishing returns very quickly, rather than creating new sources of value. Smoothing out some suboptimal pricing, and luring in a few extra shoppers with better targeted offers, could provide a marginal benefit, not a transformative and sustainable one.

Big Data could turn into an arms race, similar to high frequency trading. Or, well, literal arms races. Big Data could be a more powerful weapon, and the best armed companies will destroy the competition. Free market zealots will hail the Schumpeterian “creative destruction”.

In the past, the destruction has tended to create more opportunities than it has lost, over the long term, despite the undeniably negative effects on those immediately impacted, like the mill workers unemployed, or the auto workers whose salaries have halved.

With the rise in income inequality to levels last seen at in the gilded age, and with the “hollowing out” of the global workforce, the past may not be as reliable a guide.

Even if one of these skeptical scenarios come to pass, Big Data will not be a Big Dud, at least not for all.

Conclusion
In a more optimistic outcome, which I consider to be more likely, Big Data will be a net win, keeping the energy of economic growth thrumming at a pace to lift hundreds of millions more around the world out of poverty in the coming decades, bringing a higher standard of living, longer lives, and less misery to the world than at any time in history. Big Data can hardly take credit as the only or even the main cause. It will be but one minor contributing factor. But I believe it will contribute positively.

Ignore the data — like ignoring the facts — at your own peril.

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