Data science. Machine learning. Optimization.

Data—namely, the generating of data—has exploded. All that data creates a great challenge. Businesses need better ways to get insights from the data. We help make that happen.

Here at Tippie, we’re a leader in business analytics research and education. In 2021 the Business Analytics Department won the prestigious UPS George D. Smith Prize that is awarded annually by INFORMS, the largest international association of analytics and operations research professionals.

For decades, we’ve been wrangling volumes of data, solving the most complex analytical puzzles. We did big data before big data was cool. And now that the world has caught up, we’re riding the front edge of an exciting wave.

Working hand-in-hand with our faculty, you’ll take your analytical and modeling skills to the next level through one of three specializations. Our grads are in high demand by academia, sure, but the private sector is also clamoring for business analytics PhDs. That means you can map out your own perfect-fit career path.

STEM designation

The PhD in business analytics carries a STEM designation, which is particularly good news for international PhD candidates. Typically, after completing the degree, those in the U.S. on a student F1 visa have 12 months to work without an employer-sponsored visa. This period is called Optional Practical Training (OPT). The STEM designation extends OPT from 12 to 36 months.

Three specialization areas

Thanks to Tippie’s rich faculty roster, the PhD program in business analytics provides multiple areas in which you can choose to concentrate:

Information systems

Identify patterns and insights in data, like user behavior in Twitter or Facebook posts; identifying business competitors by mining webpages; and using health data to diagnose medical issues.

Faculty researching in this area include Patrick Fan, Nick Street, Kang Zhao, Gautam Pant, Xun Zhou, and Tong Wang.

Quantitative methods

Develop tools to find optimal strategies to tackle mathematical problems, including "big data" problems. Quagmires like monitoring physician performance, identifying players to select in the NFL draft, and balancing cost and risk in trade.

Faculty in this area include Jeff Ohlmann, Johannes Ledolter, Sam Burer, Qihang Lin, Kurt Anstreicher, and Beste Basciftci.

Operations management

Use analytical tools to make data-driven business decisions, like routing vehicles to nail same-day delivery deadlines, strategizing a sugar cane harvest, or designing supply chains to mitigate risk.

Faculty studying operations include Ann Campbell, Barrett Thomas, Phil Jones, Jennifer Blackhurst, and Renato de Matta.

Big data, big market demand for analytics PhDs

Analytics expertise is in big demand at top universities and companies around the world.

Recent grads have joined as tenure-track assistant professor or post-doc at universities including:

  • University of Arkansas-Little Rock
  • University of Michigan
  • University of Minnesota
  • University of Tennessee
  • University of Wisconsin-Whitewater

Others have taken positions as analysts and data scientists at companies including:

  • FedEx
  • Microsoft
  • Delta Air Lines
  • Tastytrade
  • Bioware
“Being able to leverage data to make really informed decisions gives a company an edge on competition. Analytics is becoming very key in managing a world-class supply chain, and it touches all aspects of a business.”
Jennifer Blackhurst
Jen Blackhurst, Business Analytics Professor & Associate Dean for Graduate Management Programs Read Jen's story

Guided by great

When you come to a place like Tippie, full of faculty leading a fast-growing field, you might think they’re too busy to mentor students. Not so.

Iowa's PhD in business analytics maximizes mentorship and collaboration. Besides your designated advisor, you’ll meet with six more professors your first semester to talk about research interests you share. Leading thinkers and researchers—including INFORMS fellows and National Science Foundation award winners—will guide you from day one through graduation.

Thinkers like Ann Campbell, an international expert in vehicle routing. Or Kang Zhao, whose social network analysis has uncovered the secret to finding your perfect online date. Or Nick Street, a pioneer in using machine learning algorithms to make medical diagnoses. (Bonus: get more from our experts on our Twitter feed.)

Suffice to say, you’re in good hands. Correction: you’re in great hands.

See faculty research

Getting in

If you've got a technical background, like engineering, math, and computer science, and want to develop analytics skills and solve real-world business problems, this is your place. Our program is small—just two to four students start each year—and accordingly competitive. We give preference to those with strong GPAs, prior graduate work, and research experience in a relevant field.

First, you need to meet the minimum PhD admission requirements. Other criteria for admission include:

Academic record

The minimum GPA is 3.0 on a 4.0 scale. We also consider the rigor of your undergrad or master's institution(s) and grades you earned in quantitative courses.

GMAT or GRE score

There isn't a specific minimum score, but successful applicants typically have very strong quant and analytical scores.

Letters of recommendation

We're interested in their assessment of your strengths, weaknesses, motivation, and ability to succeed.

Statement of purpose

Content and overall seriousness are considered.

English proficiency

This requirement applies only to international applicants whose native language is not English. We follow the Graduate College's English proficiency requirements

Curriculum and sample plan of study

The PhD in business analytics requires 72 semester hours of credit, in addition to a dissertation. The typical time to complete the degree is five years.

The plan of study is very flexible. You can take elective coursework in any year of the program. The outline below is a sample for demonstration purposes; we'll work with you to outline a plan of study that aligns with your goals.

Year 1 and 2
  • Departmental core: Management Information Systems and Quantitative Methods/Operations Management
  • Interdepartmental core: Courses from departments such as Economics, Marketing, or Finance
  • Research methodology courses (four): Mathematical Statistics I and II plus two methodology courses (options include Linear Programming, Heuristic Search Methods, Discrete Optimization, Applied Stochastic Process, Applied Multivariate Analysis, and more)

 

Year 2 and 3
  • Courses in major area of study (4–5 courses) and minor area of study (4–5 courses)
  • Year three: Written comprehensive exam

 

Year 3
  • Elective coursework (3–4 courses)

 

Year 4
  • Fall semester: Thesis proposal defense
  • Spring semester: Progress toward thesis completion

 

Year 5
  • Submission of completed dissertation
  • Final oral dissertation defense