Big data now has its turn in the barrel. According to The New York Times, big data is an economic no-show. To some pundits, it’s worthless outside consumer marketing. And to Harper Reed, former CTO of President Obama’s 2012 campaign team, big data is something succinct yet unprintable. This spirit has infiltrated CIO gatherings such as a recent New York City event where one attendee was overheard complaining, “I’m so sick of the big data conversation. Enough already.”
The CIO's remark is a testament to the "trough of disillusionment"—the term market researchers Gartner Inc. coined for the portion of the hype cycle which follows the peak of inflated expectations. But if it's normal, why worry? There are two reasons. The first is that backlashes inevitably lead to unintended consequences.
Take that 19th-century New York electricity shutdown. A few muggings on the darkened streets led one editor to declare the city “at the mercy of thugs” and the mayor had to call out extra police. The second and more significant reason is that muddy, reactionary thinking crowds out constructive criticism and holds back the real benefits of technological innovation.
Take the claim that big data has no measurable economic impact. The same accusation could have been hurled at electricity in the 1890s and was in fact directed at computers one hundred years later. The fact of the matter is that technological innovations take time for firms and people to adopt and, therefore, time to show up in macroeconomic numbers.
In the absence of data about big data’s value creation (a terrible, but temporary irony), consider the foundational rationale for big-data's importance: Data is more than just an asset. It’s now a factor of production, taking its place alongside capital and labor.
We can verify that this is true if we can point to new, data-driven products and services that would have previously been impossible. And, indeed, examples abound. Internet wunderkinds
The same goes for non-profit and government sectors. For example, Ushahidi’s service for visualizing crowd-sourced data in emergency relief efforts or the Durkheim Project’s detection of suicide risk among veterans through social media text analysis are only possible through new combinations and uses of data.
Most tellingly, data can be substituted for both capital and labor. Better data about suppliers’ prices and creditworthiness helps companies negotiate more favorable terms, thus cutting costs. Better data about manufacturing processes results in higher output and better quality without unsustainable labor costs. In short, if big data’s presence isn’t yet felt in the GDP numbers, that’s because it’s still getting dressed to come to the party.
Disruptive Influence
The arguments above should make it plain that the growing fashion in pockets of the business community to dismiss big data is particularly risky for individual firms, because it tempts managers to ignore disruptions lying in wait at their doors. The datafication of everything makes it possible for companies outside a given industry—but with troves of data—to become disruptive players by getting between established firms and their customers.
Witness what Google has done to advertising, forcing two of the biggest global ad agencies to merge. Or how Amazon and
The bottom line is that executives still saying, “I’m not sure we need big data,” are losing precious time because, while data is plentiful, the sources that generate it are limited. While it’s difficult to tell which activities today will produce tomorrow’s most valuable data, companies have little choice but to experiment.
So ignore the hype and skip over the trough of disillusionment, too. But get into the game. Because once your rivals get an edge applying big-data analytics, the resulting flywheel effect creates a competitive advantage that’s difficult—if not impossible—to catch.
