Alumnus Adam Wright discusses the value of a math degree .

When you are an undergraduate student it is difficult to understand what lies beyond that looming graduation date. Juggling classes, homework, resume-building activities, clubs, friends, and lots of coffee – most students are just trying to stay afloat. That’s why we highlight interesting success stories of Ball State CSH alumni, to show the potential of your degree and experience at Ball State and provide a hopeful vision of life beyond the cap and gown.

Adam Wright is an alumnus of the Math Department with an MA in Mathematical Statistics. He is an Army veteran, a data scientist, and an analytics consultant, currently working as a consultant at Clarity Insights (Chicago, IL). We recently sat down to talk about the usefulness of a math degree, serving in the Army, and the importance of networking.

Can you describe your career journey?

When I started at Ball State in 1987 as a freshman, I was originally going to be an architecture major. However, after changing my major and spending some “less than focused” time, I found myself with a family and ended up leaving BSU and joining the Army before I graduated.

Through the Army I finished my undergraduate degree and a master’s, and I applied for Advanced Civil Schooling to be an Operations Research Analyst so I could get a degree in engineering or statistics. I found out that Ball State had a good statistics program and got accepted.

I graduated with an MA in Mathematical Statistics in 2007, and it was a nice way to finish what I started in 1987. I served for several years as an Operations Research Analyst, including as a Math Instructor at West Point, an Operational Assessment Analyst in Iraq, and a Data Scientist and Operations Research Team Chief at Fort Knox before retiring in 2013.

After I retired, I found a lot of employers don’t want to read an army resume because you haven’t done anything to generate revenue or a profit, making even marketable skills difficult to translate. Thankfully, I started doing some consulting work which led to working full time at USAA as a data and decision scientist, gaining some relevant private sector experience. I have come back to consulting just this year and have found myself well-positioned for success.

Can you elaborate on your statistics and data analyst work in Iraq?

Over in Iraq I did operational assessments. To break it down: we had an overarching strategy and the combination of military and civilian agencies working to achieve that strategy. One of the functions of the operations research community in the military is to do assessments to measure whether or not the various military and civilian agencies are functioning successfully. As an assessments analyst, I was tasked with measuring how well we were completing our operational objectives and whether those objectives were actually impacting our strategic goals.

“Look for a way to generate more value than what you’re costing”

So, if you say you are going to build seven bridges this year, and you do, but that doesn’t result in whatever strategic outcome you wanted, then you are doing things well but you’re not doing the right things. It was very esoteric, a lot of finding data, communicating with different agencies about how they find and measure data, understanding the operations orders, and then talking with leaders about how they made and informed decisions. I ended up working with seven general officers: Army, Air Force, Navy, etc. They all led or administered various agencies or operations, and I spent a lot time redesigning a measurement framework driven by available data and making it apply to the situation of Iraq in 2010.

How would you characterize your current consulting work?

I do machine learning, artificial intelligence, any type of applied stats. But it really all comes down to problem solving. A lot of what you have to do is understand what the client’s problem is and what they need from the solution to help them inform the decisions they need to make.

There is definitely a human element to it, for business problems are human problems and decision makers are human users. So, you need to understand how timely the information needs to be and what form it needs to take. Does it need to be ingested back into a system that automates the decision or does it need to draw pictures that help them strategize longer term? All of that is really very business-y, and you have to be able to make the leap from business objectives to using large quantities of data to produce those results; working from a mess of data to a clean solution for the client.

Is it fair to say that there is a significant human relations element to the mathematical work you do?

Definitely. There is a lot of coaching involved and getting companies to embrace a ‘test and learn’ strategy. What I’ve been doing lately is building high level strategies, working with companies that don’t know how to leverage analytics. There is a sort of ergonomics of analysis or ergonomics of data. You don’t want to try to boil the ocean, you want to scope the question so that it’s addressed with a research technique and is achievable, while still producing a useful solution on the back end.

What advice would you give Math students now?

Know that you’re valuable. I think that some individuals who are talented at math choose not to study mathematics or statistics because they don’t realize that there is a whole world open to them of interesting and lucrative jobs outside of pure academia or research. You may think that business is something other people do somewhere else, but the truth is that in business you’re just trying to solve problems. The language of mathematics, and especially statistics, grew out of that exact need.

Your skills are valuable solving problems that are not presented like a theorem or in an engineering context per se. Many of these big companies are data factories: producing massive amounts of all kinds of information about clients and customers, but unable to get use from it or even know where to start.

For example, there are tons of math related applications in marketing: how you measure sentiment, appeal, service, messages, and campaigns. Learning how to take polling data and consumer information and apply it to a marketing plan – there’s math behind all of that. I’ve been able to do a lot of fun and interesting work in marketing, fraud prevention, and customer journey analytics.

“Data scientists and problem solvers are expensive and hard to find. You have no idea how valuable you are.”

Spend time reading about industry challenges and the current hot solutions, and networking to find experienced people who can help you form a realistic view of the opportunities out there and how you can delineate yourself from the rest of the pack. It has never been easier or cheaper to get exposure to the latest software and techniques that the business world needs.