Operations and Business Analytics PhD Program

The Lundquist College of Business Doctoral Program in Operations and Business Analytics prepares students seeking academic and research careers.

Operations and Business Analytics concerns how organizations should optimize business processes (e.g., production, distribution) and policies (e.g., staffing, pricing) both internally and within the broader supply chain. 

Researchers in the operations and business analytics area address these complex decisions using rigorous research methods that require a solid foundation in model building, theory development, and data analysis. These foundational skills reflect the strength of the Lundquist College's Department of Operations and Business Analytics, whose faculty work closely with students within the doctoral program. 

In addition to its faculty, the Department of Operations and Business Analytics spans the areas of information systems and statistics, allowing doctoral students to benefit from coursework and research opportunities in two areas complementary to the operations and business analytics area. Due to the quantitative orientation of this PhD option, students entering the program should have interests that lie at the intersection of applied mathematics and business research.

Operations and Business Analytics PhD Coordinator
Associate Professor Eren Çil



The required coursework for the Operations and Business Analytics doctoral program falls within three categories: supporting, core, and specialization. PhD students are expected to plan their course schedules after consulting with their faculty advisor, to help ensure that coursework is sequenced appropriately.

PhD students focus on the core classes during the first two years of their studies, in preparation for the qualifying exam. The supporting courses in microeconomics and linear algebra in particular are also useful background material for the exam and thus should be completed within the first two years. While the full set of supporting courses is a formal requirement for completing the PhD, incoming students with equivalent prior coursework may be able to obtain a written waiver from the PhD coordinator for some or all of those courses, as a result of having equivalent prior coursework.

In the second or third year of the PhD program and beyond, students choose a set of specialization courses to gain exposure to new methodologies and problem areas.

View Course Catalog

Core Courses

Completed prior to the qualifying exam.

  • Probability and Statistics (Math 561/562)
  • Regression (OBA 635)
  • Optimization methods (e.g., OSU IE 521)
  • Operations and Business Analytics research seminars* (typically 2 per year), covering the areas of operations management, information sciences, and statistics. Topics in each of these areas include:
    • Operations management: inventory management, supply chains, service operations, closed-loop operations, operations planning and control, and math programming.
    • Information systems: object-oriented design, databases, congestion management, and pricing.
    • Statistics: time series analysis, data mining, and advanced econometrics.

*Throughout the duration of the PhD program, all full-time PhD students must enroll in these Operations and Business Analytics research seminars.

Supporting Courses

  • First-year MBA courses or equivalent in: accounting, finance, marketing, statistics (and, if deemed necessary: operations management and information services).
  • Microeconomics (e.g., Econ 511)
  • Linear Algebra (e.g., Math 541)

Specialization Courses

Functional Area Focus (Choose at Least Three)

  • OBA 533: Information Analysis for Managerial Decisions
  • OBA 544: Business Database Management Systems
  • OBA 566: Project and Operations Management Models
  • OBA 577: Supply Chain Operations and Information
  • OBA 588: eBusiness

Research Methods Focus (Choose at Least Three)

  • OBA 610: Multivariate Methods
  • OSU IE 563: Advanced Production Planning & Control
  • OSU IE 521/522: Industrial Systems Optimization I/II
  • OSU ST 583: Non-Linear Optimization
  • OSU ST 515: Design of Experiments
  • OSU ST 543: Applied Stochastic Models
  • Math 513: Introduction to (Real) Analysis
  • Math 555: Mathematical Modeling
  • Math 556: Networks and Combinatorics
  • Math 564/565/566: Mathematical Statistics I / II / III
  • Econ 523/524/525: Econometrics
  • Econ 527: Games and Decisions

Note: the above courses with the OSU prefix are taught at nearby Oregon State University—typical OSU tuition fees are waived for full-time University of Oregon students.