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Big Data

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."

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.
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.


Need to know more about big data analytics and its impact on communications service providers? Then check out the Telecom Analytics World show site here on Light Reading.


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

Josephsmith 11/14/2014 | 4:45:44 AM
Re: Defining of Big-Data Another reason for Samsung's reduced profits, is thecostly IPR settlements with Ericsson, Apple and others cool spy gadgets, that Samsung had to put up with. Meanwhile, on a positive note, Samsung's chip division posted record earnings.
Ariella 11/12/2014 | 12:22:45 PM
Re: Defining of Big-Data @MordyK yes, making changes in order to optimize existing products and/or services would also be putting the data gleaned to good use.  Sometimes all they have to do is listen to what customers don't like or what reason they give for leaving to figure out what they need to do. 
MordyK 11/12/2014 | 12:17:28 PM
Re: Defining of Big-Data @Ariella I fully concur, your example would be half way between the two extremes, where your taking existing products and further optimizing them, which is just shy of an entirely new product offering.
Ariella 11/11/2014 | 8:19:16 PM
Re: Defining of Big-Data "For existing businesses getting their bearings treating big data as an upgraded BI tool might be the quickest way for management to get a grasp of its value, which can then lead the way to more creative and novel application uses once the larger meaning of big data is internalized and appreciated."

@MordyK yes, it seems to me that most businesses begin with big data just as way of gathering more intelligence, pulling in  data from more channels, and drawing correlations, etc. However, the real trick to extracting value from it is in finding the applications tha advance the business goals. 
MordyK 11/11/2014 | 3:12:51 PM
Defining of Big-Data Dr. Rubina hit the nail on the head with her description of the lack of understanding and appreciation for the meaning and value of big data.

This is really a failing derived from the successful marketing of the "big data" moniker, that encompasses everything but in a sense means nothing.

I like to break big data down into 2 components, with the first being BI on streroids and the second being new applications.

1. BI: every internal business process requires knowledge and data for it to have an impact. To date these have been achived by feedback silos like; focus groups, feedback, reporting metrics and BI. The tools of big data now allow for micro-targeting and continous improvement across all business processes within a company.

2. New Application: I like to use Foursquare's application as an example of big data in applications. Foursquare creates "real-time" custom responses based on its big data engine and knowledge.

For existing businesses getting their bearings treating big data as an upgraded BI tool might be the quickest way for management to get a grasp of its value, which can then lead the way to more creative and novel application uses once the larger meaning of big data is internalized and appreciated.
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