“Big data” is a term that occurs regularly in discussions of corporate strategy and analytics, but what is it? “I hate the term ‘big data,’” said Tom Nealand, MBA ’87, Executive Vice President of Strategy & Innovation at Southwest Airlines. “You have to get clarity around what those words really mean if you want to develop a successful organizational structure that can take advantage of the information you’re generating.” Nealand spoke recently as part of the University of Dallas’ TIE expert panel series.
The panel discussion, held on March 18, 2016 and entitled “Executive Decision Making: Analyzing Big Data,” drew a large crowd at the University of Dallas’ Satish and Yasmin Gupta School of Business, due in no small part to the credentials of the panel, which also included Aaron Miri, MBA ’10, Chief Information Officer of Walnut Medical Center; Ellen Barker, MBA ’94, Vice President and Chief Information Officer, Texas Instruments; and Rhonda Levene, MBA ’89, Former Chief Operating Officer and Chief Financial Officer, Daymon Worldwide. Mark Ryland, Chief Architect, Worldwide Public Sector Team, Amazon Web Services, moderated the panel.
Ryland attributed the tremendous growth in the sheer amount of data available to analyze to a few “megatrends” that have emerged within the tech industry. “First, storage is basically free,” he said. “There’s never any real reason for a company to delete the data they have collected on their customers. Second, the growth of new tools to analyze data has made it possible to handle a lot of information cheaply. And third, these days, just about everything is instrumental and is throwing off data. This means we are accumulating unprecedented amounts of information.”
But how, exactly, could and should a company use these mountains of data to make decisions? Barker explained that three things about big data make the management of it especially complicated. “Because of the internet of things, we are receiving data from an amazing variety of sources,” she said. “The velocity of data has also increased. And data has volatility. Some data is more valuable in the stream and less valuable as time progresses. Because of all these factors, we have to ask, ‘How do we architect our environment to give our business units the data they need?’”
Levene said her previous experience with Coca Cola and Daymon Worldwide helped her see big data from a consumer, brand-building perspective. “Big data becomes really effective for retailers when it creates consumer pull demand versus retailer pushing demand,” she said. “If handled correctly, it helps retailers correlate their next steps.”
For Miri, careful data analysis can have even greater implications. “In healthcare, data analytics is about saving lives,” he said. “If I can analyze how long it takes a patient to get from the ambulance into triage and then shave minutes off of that time, I can have a great impact on patient care.” Miri said even social media platforms can have an impact on hospitals. “We look at every bit of data. For example, we might look at Twitter for news of how the flu is spreading in the DFW area. That helps us prepare for what might be coming,” he said.
The panel also addressed questions from the audience about the ethics of collecting large amounts of data and then correlating it in a way that could threaten an individual’s privacy. The panelists agreed that even so-called anonymous data can be “de-anonymized” if subjected to a fine-grain analysis. Miri explained that the sequencing of the human genome is an example of how detailed healthcare data can both help and harm a potential patient. “If your genome shows you are at risk for cancer, a health insurance company cannot deny you coverage because of provisions in the Affordable Care Act,” he said. “But life insurers are not part of those regulations. They can deny coverage based on your genomic risk of getting cancer.” While this may seem troubling to a healthcare consumer, Miri added that these ethical situations should not preclude data analysis within the healthcare industry. “We must use the data to push society to get better. That’s the purpose of technology in healthcare. The question is: will people be willing to give up some privacy in order to achieve the end-game of a healthier society?”
Several members of the audience were also interested in how the panelists view the future of data analytics in their roles as employers. One person asked how he could remain relevant as an employee in an industry that changes every day. Nealon emphasized that to be successful, data analysts must emphasize their business skills. “Your business skills, coupled with strong applied mathematics skills, will make you an asset to an employer,” he said. “You must bring up your business intellect. You want to be known as a business person with tech DNA.”
All panelists agreed that the collection, analysis and protection of data is now an integral part of corporate responsibility and is what they called a “board-level” issue. “Proper data governance is a priority for businesses,” Ryland said. “And these emerging questions about how to use the data have become ethical questions as well.”
TIE stands for Transformation, Innovation and Ethics. It is an expert panel series in which alumni leaders host a discussion on transitions and the future of business. The purpose of TIE is to bring together alumni, administration, students and faculty to discuss a rapidly transitioning world and how to innovate and manage that change in an ethical manner. Find out more by visiting UD’s Alumni website.