AT&T: Big Data Hype Confuses Executives

ATLANTA -- Telecom Analytics World -- She may be at the heart of a major technical challenge, but AT&T's Dr. Rubina Ohanian spends most of her time getting different business units on the same page and keeping executives' expectations in check.

Ohanian, AT&T Inc. (NYSE: T) lead for big data, analytics and insight services for AT&T's Internet of Things (IoT) solutions division, explained that technology is the least of the challenges when it comes to big data and analytics. In fact, the technology is already commoditized and adequate, if a company can afford to invest. Rather, the challenge is in people, organizations and culture, starting at the very top and going all the way down to job applicants.

"How are you going to monetize that, Rubina?" It's the question Ohanian hears all the time, she said at the conference here. The carrier has so many vendors approaching it that it creates confusion at an executive level. They hear the hype and they want the results, but they are not always familiar with the challenges, she said, and it is the responsibility of big data and analytics groups to routinely meet with executives to share information.

"I have to decipher, clean, educate and say 'let's stay focused here,'" she said. "How successful we are as a company is to be able to take that success not from how many technical devices and lakes and ponds and clouds we have, but from how well our employees at all levels are at taking this data we're creating and use it as an asset to their advantage."

Figure 1: Data Doctor Dr. Rubina Ohanian, Big Data and Analytics, IoT, AT&T Mobility, is a PhD, tells the audience about the coming big data analytics revolution.

Unfortunately, creating tangible results is where most corporations struggle, she added. Vendor hype isn't helping and data scientists, or "unicorns" as she called them (because of their rare skill sets), are hard to find.

Ohanian wasn't putting down her bosses. Rather, she made it clear that these are "brilliant, educated executives that are passionate, involved, that read every day, learn and ask questions." But when they are constantly hearing vendors say they can make money from data, the questions they are asking are all about how, when and with what data.

"These executives listen, read, talk to vendors, get all hyped up, then their expectations go up, and I get a call," she said.

"If you ask product managers their strategy, they say, 'You tell me the value of the data, and I can figure out my strategy,'" she continued. "I can't do that without knowing their strategy."

That's the circuitous environment in which much of the industry is stuck. Ohanian, too, tries to get her bosses answers within a siloed environment, and one in which true experts are hard to find. She said that in a recent round of recruiting for her team, she had more than 120 applicants, but at least 110 of them had zero qualifications, because they didn't understand the meaning of big data and advanced analytics or have the qualifications needed.

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The big data boss continues to meet with at least two vendors per week to stay on top of what's already become a fast-moving, always-changing industry. Her mission now at AT&T -- and her advice to other companies in the industry -- is to get analytics involved in upfront discussions, so that it's not an afterthought. It's an evolution and maybe a revolution, she said, and it starts with internal changes.

"Big data projects don't have to be expensive; start small, prove your point and then begin to grow by gaining credibility," she advised. "Maintain visible executive sponsorship through routine top-down communications of priorities and objectives, and identify metrics for your own analytics organization and be accountable to derive performance."

At the same time, drive culture change throughout all levels of business units, not just the top, Ohanian said. Ensure that business units collaborate with each other, ask the right questions and deliver results. Demand fact-based decision-making, she said, adding, "This touchy-feely high level has got to go."

"Be realistic about the value and limitations of big data analytics," Ohanian concluded. "Ensure managers are able to work well with data scientists and analysts when the need arises. If you can't roll up your sleeves, you're at the mercy of your vendor."

— Sarah Reedy, Senior Editor, Light Reading