Analytic tools are only as good as the people who use them.
In 2007, Jim Braun was CFO of OmniTrax, a regional railroad operator that was making a lot of money by leasing and selling the land and buildings it owned around its tracks. The real estate market was on the brink of an historic collapse that year, but “I’d be lying if I told you I knew it would get that bad,” he says.
Still, Braun, who is now a consultant in business information management at Capgemini, had kept a gimlet eye on industry trends, drawing on data that indicated an increase in inventory and a slowdown in development. When he modeled that information with business intelligence (BI) tools and saw red flags popping up, he urged the railroad’s board to slow its real estate purchasing.
That didn’t go over well. Real estate “was a good revenue stream,” says Braun. But OmniTrax did transfer its focus from property acquisition to its operating assets. That shift, he says, was a “real lifeline” for the company when the real estate market blew up.
Many financial executives had access to the same tools that Braun did, and the data was available to everyone. But his background in structured finance enabled him, he says, to see “what was happening in credit.” The moral: BI and analytics tools are only as good as their users.
And next-generation analytics, which Gartner has identified as a top-10 strategic technology for 2012, has the potential to be very good indeed. (Gartner defines analytics as being embedded in technology, as opposed to offline analysis done through Excel; forward rather than backward looking; and drawn from increasingly diverse sources of unstructured information, not just transactional systems.) David O’Connell, principal analyst at Nucleus Research, claims that the rate of return on analytics investments is $10.66 on every dollar invested.
“That means,” he says, “that if you’re gathering data and you haven’t deployed analytics, you’re crazy.”
And, really, who isn’t gathering data? According to a 2011 study conducted by IDC, the amount of data being stored by enterprises is doubling every two years. The usual suspects (IBM, SAP, Oracle, SAS, Microsoft) have developed enterprise-grade BI tools to make sense of all that data, much of it unstructured and streaming into the enterprise from the web, connected devices, and social-media feeds in the form of blogs, tweets, “likes,” video, and audio.
Just as there’s no lack of data, there’s no dearth of tools. A passel of smaller vendors (Lavastorm, Pentaho, Adaptive Planning, and others) offer a variety of database management and analytics tools to work independently of or in concert with the software giants, or (as is the case with Cloud9) with Salesforce to improve the accuracy of deal forecasting.
But it’s what people do with the data that ultimately counts. “It’s wrong to start with data,” says Jonathan L.S. Byrnes, senior lecturer at the Massachusetts Institute of Technology and author of Islands of Profit in a Sea of Red Ink. “Start by asking what the company should be doing, then reach into the data box, and then apply analytics.”