Editor's note: The Harbert College of Business is committed to developing a vibrant entrepreneurial ecosystem for students, faculty, industry, and alumni that will fuel new venture creation. The story that follows is one of eight in a series entitled, "Inspired Entrepreneurship." Showcasing the experience and expertise of Harbert alums who have created successful business enterprises of their own will help equip our students for entrepreneurial success.

“Entrepreneurs exist in startups and in large organizations. They’re the people who aren’t afraid to try something new and different ... there's no better place to start than in the world of business analytics where big data and advanced analytical techniques are opening new possibilities every day."”

For Richard Hale, whose career spans senior leadership positions at such industry giants as AT&T, NCR/Teradata and IBM, commitment to Auburn and the Harbert College of Business is truly a family affair.

He met his wife, Melinda – also an Auburn grad – at Auburn. His two sons, Kyle and Brent, are Harbert grads as well – Kyle in Marketing and Brent in Supply Chain Management. In true Auburn fashion, Hale and his wife established the Richard and Melinda Hale Endowed Fund for Excellence for Business Analytics to further match Harbert’s Business Analytics curriculum with the emerging needs of today’s data-rich business environment.

The Harbert College of Business sat down with Richard as part of its Harbert Entrepreneur Spotlight initiative to hear how he sees the professional and entrepreneurial value of business analytics evolving today and how Harbert is leading the way in the melding of Big Data Analytics and Business Intelligence.

HCOB: You received your B.S. in Business Administration and your M.S. in Economics from the College of Business, but you originally came to Auburn as an engineering student. Can you tell us a little about why you made that switch?

Hale: I chose Auburn because I knew I wanted to have a technical career and began my studies in Engineering. I soon realized that business was my passion and I transferred to the College of Business. Because I was technical by nature, I focused on statistics and econometrics and was a member of the College of Business’ fourth graduating class. I left for military duty and upon return I went back to Auburn to get advice from professors on what I should take as next steps. They offered me a graduate teaching assistant position at the College of Business, and I enrolled in the Master of Science program. My mentor and major professor in that program was Dr. Wayne Lacy. 

I was inspired by Dr. Lacy to learn analytics and predictive modeling, which at that time primarily involved in working with government data. In what was, essentially, an early prediction of the current rise of Big Data, Dr. Lacy told me all areas of business would one day rely heavily on data analytics. He required my thesis – which was based on predictive models – to be not simply a survey of scholarly literature, but one that would contribute to the current stock of knowledge. That drove me to think "out of the box." It also built my confidence to try something new – an important lesson for all entrepreneurs today.

HCOB: Can you tell us a little about your early career at the Federal Reserve and then AT&T?

Hale: The skills I learned while at Auburn enabled me to begin a career in information technology at the Federal Reserve. Like most businesses, the Fed was more interested in my programming skills than my analytical skills. I wrote programs to solve requirements of operational departments – “the business.” During my time at the Fed I rose to lead IT planning for the 6th District and began their initiatives to implement data management systems and decentralize computer processing.

My passion for business led me to AT&T Computer Systems where I became Director of Sales in the southeast for their largest computer system platforms. When AT&T purchased NCR, I moved to the new company and became responsible for marketing the Teradata data warehouse in the southeast. Teradata was a big data pioneer and was the base technology of the largest commercial data warehouses in the world. Business was storing massive amounts of data – retailers, for instance, were storing every transaction they executed. The internet was producing information and clickstream data at incredible rates. From an analytical standpoint the information available and its growth rate were mind blowing.

HCOB: And that’s when you took the plunge into entrepreneurship, right?

Hale: That’s correct. My passion for analyzing data and solving business problems led me to join a start-up focused on data mining tools and solutions, Neovista. The technologies we called "data mining" are the underpinnings of modern-day machine learning and artificial intelligence.  Big data was growing quickly, and we soon saw large companies stepping forward into leadership roles.

One of the founders of Teradata called me while I was a VP at AT&T and said that he was starting a new company that was going to go help customers get more value out of those warehouses.  Our goal was to lead our customers into the world of machine learning. There were about 20 people at Neovista when I got there, growing to about 35 when I left. I came to realize that the size and nature of the opportunities I was seeing in big data were best addressed by companies with the requisite scale and expertise required to execute on a larger scale. Given that, I accepted a new opportunity at IBM to run what was essentially a skunkworks operation about big data. It was a great little team focused exclusively on leveraging business intelligence and advanced analytics worldwide – you might call it a start-up within a very large operation – right up my ally.

“I decided that, to meet the needs of predictive modeling in the world of machine learning and big data, we would have to use something other than the traditional techniques. I took the opposite tack of most researchers and started working with simplifying the analysis and relying on the massive amount of data available to improve accuracy." ”

HCOB: That’s where you developed your patent for creating predictive modeling, right?

Hale: That’s right. It’s called “Process and Heuristic Statistic for Prospect Selection Through Data Mining” – quite a mouthful, but what it provides is a way to create predictive models allowing computers to provide insights without human intervention.

Traditional predictive technology was based on a complex, iterative, manual process that takes place in off-line platforms. It required expert analysts and usually took a significant amount of time, and the results of that process could be obtuse and hard for an untrained business user to understand.  The patent provides a way for computers to create and implement models "on the fly" in an accessible platform without human intervention.

HCOB: Why is that important?

Hale: To begin with, artificial intelligence must take place at the point of execution, meaning that offline model creation presents significant obstacles. We simply didn’t have time to create models in one platform and move them to another to be used. In business today, models become obsolete very quickly as tastes, demographics, products, and other factors change rapidly. This new process creates new models during every time it is used so they never go stale. Moreover, with this new process, the user doesn't have to be an expert because the expertise is in the computer.

HCOB: Can you tell us how this process is used to provide real business value?

Hale: Our first implementation was for merchandising analysts who thought they were just pulling reports when they were actually using machine learning. I met with the VP of Marketing for a large retailer to discuss his most important problems. His most pressing issue was that he couldn't keep up with his requirements to provide targets for promotions being offered by his vendors. He had large amounts of data including massive transaction data and loyalty information on tens of thousands of customers, but no way to create predictive models to identify the correct targets in a timely fashion. 

There had been lots of attempts to do hands-free predictive model creation by automating the processes around traditional techniques, but I wasn't aware of any that had been widely deployed.  I decided that to meet the needs of predictive modeling in the world of machine learning and big data we would have to use something other than the traditional techniques. I took the opposite tack of most research and started working with simplifying the analysis and relying on the massive amount of data available to improve accuracy. It not only worked, but it offered results similar to those provided by more traditional techniques. The relatively simple techniques used produced significantly less processor overhead enabling model development and deployment to be accomplished within the data warehouse, and not in a special-purpose processor.

The patented process has been deployed around the world and used for solutions other than promotion targeting. Several of the world's largest mass merchandisers use it for replenishment prediction and have enjoyed reduced out-of-stocks and increased turn. It's also been used in healthcare applications, and its automatic operation has also given it a home in e-commerce. 

HCOB: It’s fairly unusual, isn’t it, for a businessman to create what is essentially a very technical, engineering-based process patent?

Hale: Well, yes, I suppose it is. I held titles of Director and VP in sales and marketing and yet I was awarded a patent for a predictive modeling technology, which one would think would come from a research or engineering background. That's because I had training in general business and predictive analytics at Auburn and a developed a deep understanding of marketing needs from my business career. That’s one of our goals in the Harbert Business Analytics curriculum – to produce graduates with a strong understanding of both business analytics and business processes. Graduates with an understanding of both worlds have a distinct advantage in today’s increasingly technical business environment.

HCOB: What advice can you give to today’s business students looking to leverage the experience and entrepreneurial spirit you’ve embodied throughout your career in their own professional development?

Hale: Entrepreneurs are driven creators who take chances and try new things in virtually everything they do. Entrepreneurs exist in startups and in large organizations. They’re the people who aren’t afraid to try something new and different. And there's no better place to start than in the world of business analytics where big data and advanced analytical techniques are opening new possibilities every day. That’s why Melinda and I are so committed to the work David Paradice and his team are doing at Harbert in Business Analytics. I can’t think of a better way to help give back to the institution that gave me such a great head start in my own career.