2019 Best 40 Under 40 Professors: Eric Schwartz, University of Michigan (Ross)

Eric Schwartz

Assistant Professor of Marketing

University of Michigan, Stephen M. Ross School of Business

At just 32, Eric Schwartz has already published some prolific research, including what drives word-of-mouth support from customers, a topic Schwartz was researching prior to 2011. For the past six years, Schwartz has taught undergraduate and graduate students in marketing at the University of Michigan Ross School of Business. His research looking into the water crisis in Flint, Michigan led to media coverage as well as U.S. District Court filings in lawsuits surrounding the contaminated water.

In his spare time, Schwartz enjoys watching and playing soccer as well as binging some of his favorite TV shows. “Eric Schwartz has a tremendous impact both inside and out of the classroom,” one nomination said. “His students speak of his enthusiasm; his obvious love for teaching; and his approachable, helpful demeanor.”

Current Age: 32

At current institution since what year? 2013

Education: Ph.D., University of Pennsylvania, Wharton School; BA, University of Pennsylvania, College of Arts and Sciences, Mathematics and Hispanic Studies

List of current MBA courses you currently teach:

-Marketing Management (MBA Core Introduction to Marketing)

-Living Business Leadership Experience (action-based learning course working with companies)


I knew I wanted to be a business school professor when … I was way too young to know I wanted to be a business school professor. During undergrad, I took a course, “Applied Probability Models in Marketing” with Professor Pete Fader (my undergrad mentor who later became my doctoral co-advisor). I asked him, “How can I do more of that?” To my surprise, it meant being a marketing professor. And 13 years later, here I am.

What are you currently researching and what is the most significant discovery you’ve made from it?

I study how firms and organizations can better run useful marketing experiments, like A/B tests. In practice, decision makers need to collect data sequentially to simultaneously balance learning and earning to achieve their objective. I apply and develop statistical machine learning and optimization methods in typical customer settings (e.g., online advertising, e-commerce pricing, market research surveys) and have worked with companies to do implement them. But, in the most interesting work I’ve been doing lately, I applied these ideas to public health policy, in particular, the Flint Water Crisis.  My colleagues and I have collaborated with officials in Flint, Michigan, using that machine learning and sequential data collection technology to identify which homes still have lead water service pipes in Flint, to get the lead out of Flint more quickly. It has been the focus of some recent litigation involving the ACLU and NRDC, and a court order recently required the use of our predictive model to finish replacing the lead pipes in Flint. This has attracted attention from other cities and water utility companies, as others are seeking to build inventories of their and their consumers’ lead pipes. So, we are working with several partners — including community members, municipal utilities, and University of Michigan students, staff, and faculty — to figure out how to best scale this effort up to maximize its impact elsewhere in the country.

If I weren’t a business school professor… I’d be working in sports analytics … doing data science for a professional soccer/football team.

What do you think makes you stand out as a professor?

Students say I bring a lot of energy to the classroom, and I try my best to bring the most current examples into class, discussing brands, products, and services that students actually use today.

One word that describes my first-time teaching: Excited.

Here’s what I wish someone would’ve told me about being a business school professor: Write, write, and write! Better writing communicates complex ideas simply. It improves research productivity and teaching quality. So, I am always trying to be a better writer and communicator. But I certainly didn’t appreciate the extent to which those skills are critical.

Professor you most admire and why:

My two advisors, Pete Fader and Eric Bradlow, because of their devotion to their families. Their priorities are clear. And they are also extraordinary mentors to students, leaders (in business and academia), teachers, and researchers.


What do you enjoy most about teaching business students?

I enjoy the range of experiences that students bring to the classroom and their willingness to share those perspectives with their fellow students and us. I think it is a distinctive feature of business education.

What is most challenging?

I think that range of experiences can also be challenging. Students come to business school with very different goals. And it can be a challenge working with such a mix that is quite heterogeneous (to use one of my favorite words in marketing modeling).

Using just one word, describe your favorite type of student: Curious.

Using just one word, describe your least favorite type of student: Apathetic.

When it comes to grading, I think students would describe me as… Fair.


What are your hobbies?

I play soccer, as much as I can, and I watch it too. I’m also an avid binge watcher of great TV.

How will you spend your summer?

Research, naturally, and traveling for conferences.

Favorite place(s) to vacation: Beach. Anywhere with a beautiful beach.

Favorite book(s): Breakfast of Champions, by Kurt Vonnegut

What is your favorite movie and/or television show and what is it about the film or program that you enjoy so much?

It’s tough for me not to say classic comedies, anything by Mel Brooks or the Zucker Brothers, because sometimes slapstick laughs and silly puns are just enough.

Favorite type of music and/or favorite artist: 1990s hip hop.


If I had my way, the business school of the future would have much more of this… Real-world data science and analytics experiences for students. Students, faculty, and employers are excited about analytics, but we have a lot more work to do in this area. I think there are opportunities to innovate pedagogically with analytics education too. For instance, merging data science with the model of action-based learning is promising, so students work with a mix of students that reflect the real teams that students will find themselves joining in the workplace.

In your opinion, companies and organizations today need to do a better job at doing what?

Experiments. Planning, implementing, and analyzing experiments to draw insights. This has been revolutionary in the past 10 to 15 years for many tech companies, but there is still a massive skills and knowledge gap to work on.

Faculty and administrators say:

“Eric has been successful in teaching marketing core (Intro to Marketing) at both undergraduate and graduate levels. He is committed to his students both inside and outside the classrooms. He has been good mentors to some of these students for their research projects and business ideas. Eric’s research has also contributed to Flint water problem. He and his coauthors use a machine learning algorithm to predict lead contaminated pipes in Flint. Michigan takes pride in their action-based learning, especially the new initiative of Living Business Learning Education. Eric has been advisors for 1-2 projects in the program as well. Finally, Eric’s paper based on his dissertation won John DC Little award which is a prestigious award given out by INFORMS.”

“Eric Schwartz has a tremendous impact both inside and out of the classroom. His students speak of his enthusiasm; his obvious love for teaching; and his approachable, helpful demeanor. An expert in the field of machine learning, he won the most recent John D.C. Little Award from the Institute For Operations Research and the Management Sciences, given to the year’s best marketing paper. He’s in high demand as a speaker at conferences and research seminars. We are especially proud of the work he’s done to use “big data” and algorithms to accurately predict the location of lead water pipes in Flint, Michigan — information currently being used to guide ongoing pipe replacement in that city.”

“I write as Marketing Department Chair to strongly recommend Prof. Eric Schwartz. Eric joined Ross after his Wharton PhD, since amassing a perfect record in undergraduate Core Marketing and teaching our notoriously demanding MBA core to student raves. Eric’s already a research star, leveraging cutting-edge statistical and machine learning methods helping managers be “earning while learning” with experiments that adapt to incoming data. He’s applied his work broadly, from industry titans like P&G and CapitalOne to non-profit arts organizations and Detroit’s Police Department. Notable is his helming a team to help city officials remediate the Flint Water Crisis, garnering national media attention and a Federal Court ruling mandating the use of his algorithms. Scholars in our field have noticed, citing his work over 600 times and awarding him its most prestigious research prize: the John Little Best Paper Award. Eric’s truly the whole package: stellar instructor, superb researcher, great colleague.”


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