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Big Data: Where the Money Is; Free-standing Big Data businesses can evolve from the expansion of data gathering and analysis within a single company

June 12, 2014

CFO.com | US

Big Data: Where the Money Is

Free-standing Big Data businesses can evolve from the expansion of data gathering and analysis within a single company.

As Big Data grows bigger, more complicated, and more difficult to deal with, the choice of which data get retained and which discarded becomes pivotal.

Before 2009, an app built by Anil Jain, an enterprising physician and IT chief, was used only to get queries by Cleveland Clinic researchers about drugs and medical devices answered much faster than they had been before.

Dubbed “MyResearch,” the application was a search engine that let authorized users get answers from a “vast data set” culled from electronic medical records, to identify patterns of patient diagnoses and health care, according to Charlie Lougheed, the president and chief strategy officer of Explorys Medical Systems, a big data firm spun off from the clinic six years ago.

Prior to Jain’s innovation, if a researcher asked, for example, how many patients were taking a particular drug, a group of systems analysts had to get together and verify what exactly was being asked and had to assess the time and cost of the project from an IT standpoint, according to Lougheed. After such a project was approved, the analysts would eventually come back with the answers.

But a few days later the researcher might say, “Wait a second, it was a different question I really wanted to ask,” thus sending the analysts back to the drawing board, Lougheed said. “Anil and his team were able to provide some self-service to [process] these questions at high speed.”

Meanwhile, Lougheed, who had data-management experience in telecoms and banking, along with two other eventual Explorys co-founders, were looking for an opportunity in the health care industry in Cleveland.  To them, he recalled, health care represented a “land of opportunity”: a mature industry representing a huge portion of the nation’s GDP that was crying out for efficiencies and cost cutting.

Further, the industry was ripe for innovation. “Bringing together data from disparate systems wasn’t the kind of thing that was being done en masse,” he said, noting that Jain’s work represented at the time an early stage in the development of data integration that has come to be known as big data.

Flash forward to 2014, and many of the capabilities Jain developed at Cleveland Clinic live on in Explorys’s current data platform, says Jain, who is now the software firm’s chief medical officer while continuing to practice medicine. Those capabilities, to be sure, are a good deal broader, buttressed by an incoming stream of clinical, operational and financial data for 19 big health care systems, including 310 hospitals. The system encompasses 226 billion “data facts” about such things as laboratory results, patient office visits, hospital stays and the costs of care.

To be sure, Explorys’s story is a good example of how free-standing big-data businesses can evolve from the expansion of data gathering and analysis within a single company. And prompted by a hard sell from entrepreneurs in Silicon Valley and elsewhere, companies are taking a hard look at what they can do with the data they have amassed over the years in the normal course of business.

Yet while many companies are likely to take advantage of the sales, marketing and operational opportunities in crunching and integrating large amounts of data, a much smaller number will actually turn those advantages into a separate business, experts say.

The Three V’s

For one thing, not all industries lend themselves to the quintessential big data business model. The model, Lougheed says, entails possession of the “the three v’s”: a high volume of data, a variety of data, and the potential to make that data move at high velocity.

That description would seem to fit FICO, which has been producing credit scores for companies and individuals since 1956. Having repositioned itself as a software analytics vendor, the company is now offering the FICO Analytic Cloud, a decision management analytics platform that helps companies do such things as manage debt and prevent fraud.

Now able to amass much larger amounts of data and store it for much longer periods than was previously possible, FICO can allow clients to upload their own data and combine it with the much broader data set that FICO collects. The company thus “has an opportunity, not merely to sell [its] credit scores, but come up with new data products that offer new insight and generate new revenue for the business,” says Mike Olson, chief strategy officer for Cloudera, a Palo Alto, Calif.-based data warehousing company that provides services for both FICO and Explorys.

Similar opportunities exist for companies that “get paid to collect data” to expand into big data analytics, Olson thinks, noting that software-as-a-service firms are particularly ripe for such growth. Each month, for instance, a typical client might pay SalesForce.com, a provider of customer relationship management software, “to let [its] salespeople answer every single detail about all of [its] customers in all of [its] deals,” he notes.

Because Salesforce.com hosts such data, it “is in a good position to analyze [the data and] benchmark a client’s performance against everybody else in [its industry] — and to sell the client that insight. Data insight is a big opportunity for those guys,” Olson observes.

Yet while big data may represent a big potential area of future growth for many companies, most need to walk before they can run, suggests Nicole Anasenes, the CFO of Infor, a New York-based provider of industry-specific business application software.

“The biggest challenge clients have today is that they’ve got all these disparate systems that produce lots of different data. So it’s a great asset, but the first step is harnessing that to better their own [businesses],” she says. “Most of the work we’ve been doing with clients has been about that internal transformation, rather than to extend to something new.”

 

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About bambooinnovator
KB Kee is the Managing Editor of the Moat Report Asia (www.moatreport.com), a research service focused exclusively on highlighting undervalued wide-moat businesses in Asia; subscribers from North America, Europe, the Oceania and Asia include professional value investors with over $20 billion in asset under management in equities, some of the world’s biggest secretive global hedge fund giants, and savvy private individual investors who are lifelong learners in the art of value investing. KB has been rooted in the principles of value investing for over a decade as an analyst in Asian capital markets. He was head of research and fund manager at a Singapore-based value investment firm. As a member of the investment committee, he helped the firm’s Asia-focused equity funds significantly outperform the benchmark index. He was previously the portfolio manager for Asia-Pacific equities at Korea’s largest mutual fund company. KB has trained CEOs, entrepreneurs, CFOs, management executives in business strategy, value investing, macroeconomic and industry trends, and detecting accounting frauds in Singapore, HK and China. KB was a faculty (accounting) at SMU teaching accounting courses. KB is currently the Chief Investment Officer at an ASX-listed investment holdings company since September 2015, helping to manage the listed Asian equities investments in the Hidden Champions Fund. Disclaimer: This article is for discussion purposes only and does not constitute an offer, recommendation or solicitation to buy or sell any investments, securities, futures or options. All articles in the website reflect the personal opinions of the writer.

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