Tim O’Reilly once presciently described data as “the new Intel Inside,” the primary source of competitive differentiation in a world where technology has largely been commoditized. While he referenced Google and other web giants, today mainstream enterprises have embraced Big Data as they seek to stand out. But a danger lurks.
The more companies embrace data to differentiate, the less it does so. O’Reilly thought data might be humbled by free data movements, much as proprietary software was hit by open-source software, but the culprit may actually be something more overtly benign: data-friendly applications.
Intel’s Branding Coup
There was a time when consumers didn’t care what chips ran their computers, a fact painfully reflected in Intel’s stock price. But in 1991, Intel launched its famous “Intel Inside” branding campaign, and its stock took off. What had been considered commodity in 1990 suddenly became premium in 1991: the Girbaud jeans of their time. (Editor’s note: Yes, we have pictures of Matt wearing Girbaud. No, they’re not pretty.)
But O’Reilly wasn’t arguing that data is simply a marketing slogan that can trick people into paying a premium for an otherwise commodity product. Instead, he reasoned that the few who manage to harness specialized databases are best positioned to charge for access to their data: “In the internet era, one can already see a number of cases where control over the database has led to market control and outsized financial returns.” In turn, this control has enabled such firms to amass computing resources that, in turn, generate even more data (with subsequent lock-in).
But what happens when data goes mainstream?
Big Data Inside
This, after all, is what is happening within the enterprise. While we’re still years away from Big Data becoming omnipresent, companies like Cloudera and EMC believe in a future when every enterprise mines vast treasure troves of data to glean insight and competitive advantage. For now, however, tools like Hadoop remain complex for most enterprises, and the science of data analysis has many enterprises scrambling for data scientist panaceas.
Big Data, however, promises to become easier, as Workday co-founder and Cloudera board member Aneel Bhusri reports:
Bhusri is likely right. But if so – if Big Data becomes democratized (read: commoditized) through applications – how does it continue to set a data-driven company apart from its data-driven competitors?
A Nicholas Carr Haunting
This line of questioning will sound familiar to those who have read Nicholas Carr’s seminal “Does IT Matter?” As he wrote in 2007:
Behind the change in thinking lies a simple assumption: that as IT’s potency and ubiquity have increased, so too has its strategic value. It’s a reasonable assumption, even an intuitive one. But it’s mistaken. What makes a resource truly strategic – what gives it the capacity to be the basis for a sustained competitive advantage – is not ubiquity but scarcity. You only gain an edge over rivals by having or doing something that they can’t have or do. By now, the core functions of IT – data storage, data processing, and data transport – have become available and affordable to all. Their very power and presence have begun to transform them from potentially strategic resources into commodity factors of production. They are becoming costs of doing business that must be paid by all but provide distinction to none.
While a gaggle of enterprise IT vendors rushed to insist that IT does, in fact, matter, Carr’s primary point – that the more the benefits of IT are distributed the less differentiating they become for any particular firm – seems to be confirmed by the effect of SaaS, among other things. IT has been simplified through SaaS and other trends, but it hasn’t become more differentiating. If anything, it has become less so.
Is data any different?
“Big” Data Gets It Wrong
The answer is a qualified “maybe.” Any particular technology trend loses its competitive bite when the mainstream adopts it, but this doesn’t mean that there isn’t value in harnessing that technology. Data is no different.
As Redmonk analyst James Governor postulates, “The advantage is in how you use the tech, not the tech itself.” Just as owning Salesforce.com or the latest HP server won’t differentiate your business, neither will owning massive quantities of data. New survey data from Infochimps confirms this: the top-two reasons for failure in Big Data analytics projects are lack of expertise to connect the dots between data and lack of business context for one’s data.
The world has become fixated on the “big” in Big Data, but volume of data is not very interesting. In the (near) future, everyone will have data, and plenty of it. But asking the right questions at the right time, not merely asking “bigger” questions, will continue to drive serious competitive differentiation.
Big Data, in other words, is just the ante to get in the game. Going forward, real differentiation will inure to those businesses that know which data to use and how and when to query it.
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