Big Data in Big Companies - Baylor Business Review

by Beth Schultz

Big data and big company seems an obvious pairing — I mean, if large enterprises don’t have lots of data on their hands, and all different sorts of it, then what type of organization does? But big data, we know, doesn’t add up to big-data analytics.

In fact, when business analytics author Tom Davenport sat down early this year and contemplated research he intended on big data’s use within big companies, he wasn’t even sure he could easily find 20 or so companies that had big-data initiatives. But, as evidenced in “Big Data in Big Companies,” a May report he co-authored with Jill Dyche, vice president of best-practices at SAS, he did. For that report, he and Dyche interviewed 20 large organizations about how big-data played into their corporate data and analytics environments.

I met with Davenport for a one-on-one conversation just prior to the report’s publication. He recounted being “pleasantly surprised” about the level of big-data activity within big companies and said that he was “impressed by the commitment and investment levels” that he’d uncovered.

Yes, he admitted, some companies are still only dabbling in big-data. “But it’s quite striking to see those who are into [it] and how committed they are to make it happen.”

For big companies, “making big data happen” is, make no mistake about it, a big endeavor. Anybody who has ever grappled with integrating new technology and a legacy environment will no doubt know the type of big I’m talking about — big technology challenges, big egos, big budgets. Yet, Davenport and Dyche said in the report, big companies are well aware of the importance of integrating big data and big-data analytics with traditional data and traditional analytics.

“Overall, we found the expected co-existence; in not a single one of these large organizations was big data being managed separately from other types of data and analytics,” they wrote. The opportunities awaiting in the ability to garner insight and move decision making by combining the new (“voice or text or log files or images or video”) with the old are simply too great to ignore.

A retail bank, for example, is getting a handle on its multi-channel customer interactions for the first time by analyzing log files. A hotel firm is analyzing customer lines with video analytics. A health insurer is able to better predict customer dissatisfaction by analyzing speech-to-text data from call center recordings. In short, these companies can have a much more complete picture of their customers and operations by combining unstructured and structured data.

That’s even aside from continued use of more structured data streaming into a company via sensors and other operational data-gathering devices, they said.

All said, the integration of big-data and its analysis has been prompting companies to adopt an “Analytics 3.0” perspective on analytics. As we’ve written about previously, and as the authors also write about in this report, the rise of the Analytics 3.0 era is about companies enabling themselves to participate in the data-driven economy. “Banks, industrial manufacturers, health care providers, retailers — any compan[ies] in any industry that [are] willing to exploit the possibilities — can all develop data-based offerings for customers, as well as [support] internal decisions with big data.”

Beth Schultz is Editor in Chief of AllAnalytics.com.

She has more than two decades of experience as an IT writer and editor. She focuses on advanced IT technology and its impact on business users and is a thought leader on the revolutionary changes remaking the corporate datacenter and enterprise IT architecture.

Baylor Business Review, Fall 2013