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Meet Rob Carver, Business and Data Analytics Expert

"In my classroom, every problem we tackle is real. There are no answers in the back of the book."

Rob Carver, Senior Lecturer

Robert Carver, Senior Lecturer

Rob Carver has dedicated most of his professional career to data – mining it, managing it, analyzing it and deploying it to solve problems in business and society. Before receiving his PhD from the University of Michigan, Carver co-founded a company focused on creating software programs to help small businesses run their organizations more efficiently. His company was successful, but Carver missed being in the classroom. 

Today, Carver, a senior lecturer at Brandeis International Business School (IBS), teaches courses in business analytics, quantitative methods and statistics. Some of his latest research grapples with the ethical dimensions of Big Data.

You were early to spot the promise of business analytics. What attracted you to the field?

It was opportunism on my part rather than any great prescience. I’ve always had a dual interest in policymaking and mathematics. I enjoy informing arguments and making sensible strategies by looking at data rather than ideology. That said, I like to move back and forth between an analytical approach to solving problems and a philosophical approach.

What does the explosion in the availability of data mean for organizations?

The breadth of applications is diverse. Companies and organizations can use statistical analysis to do everything from serving customers better to discovering medical breakthroughs to honing their advertising strategies to advancing their security systems. It’s an exciting time. And it’s an exciting time for my students. If you can apply the tools of modern data science to solve problems, you have an edge in the job market.

In this age of Big Data, statistics is experiencing a renaissance. It must be gratifying.

It used to be that I’d go to a cocktail party and kill the conversation by saying, “I teach statistics.” Now when I tell people I do data analytics, they think I’m a rock star. Part of me wishes this had all happened 20 years earlier. I’m in my early 60s now, and there is so much going on in this field and so many changes to come. Still, it’s pretty great that even at my age, every day I come to work and learn new stuff.

What are your biggest ethical concerns about the expanding use of Big Data?

There are two things that trouble me. The first is the longevity of the digital data that’s being collected. Once that data is stored – whether it’s accurate or inaccurate, direct or indirect—it’s there forever. There’s no one curating the data; there’s no one checking it for errors. That’s very concerning, especially in relationship to privacy.

The second issue is the idea of informed consent. In the course of our daily internet browsing, most of us click “agree,” “agree,” “agree” whenever we’re asked, but we’re not bothering to understand what we’re agreeing to. The data we’re agreeing to make available may get used in ways that haven’t even been imagined yet. Constant innovation is a hallmark of this industry, after all. But giving permission to all future uses of our data doesn’t seem right. These are among the ethical wrinkles we need to be vigilant about.

What do you enjoy most about teaching at Brandeis?

Brandeis is a magical place. I’ve loved getting to know students from all over the world, and it’s challenged me as a teacher. I push my students hard, and we spend a lot of time on communication. Knowing how to run a complicated model that will give you a useful answer is one thing, but in order to sell your strategy or get buy-in for your business idea, you need to be able to explain how you came up with the answer and what it means.

Describe your best teaching moment.

In my Big Data course, every problem we tackle is real. There are no answers in the back of the book, and the students and I struggle together. I come up with what I think is a pretty good solution, and it’s always rewarding when a student team surpasses me and comes up with one that’s even better.