Innovative Education: Teaching the Professional Practitioner

VCU professor finds success by focusing on students’ learning rather than his teaching.

By Jason R. W. Merrick

Jason R. W. Merrick

I was honored to receive the 2014 INFORMS Prize for the Teaching of OR/MS Practice. Looking at the list of names that have received the prize before me was humbling, including the first awardee, Ron Howard, one of the founders of my field of decision analysis. The prize is awarded to the teacher, but it is really based on the impact that your students have had practicing operations research and management science in their careers. I was very pleased to pick up the award on their behalf.

The idea of being recognized for teaching and practice would not have been obvious if one looked at my early education and research. I went to Reigate Grammar School in the United Kingdom and did “A” levels in math, advanced math, physics and chemistry. For my undergraduate, I went through a very theoretical program at Oxford University in math and computation (they didn’t even call it computer science back then), followed by research in reliability theory and Bayesian statistics at George Washington University. My research used Bayesian semiparametric methods like mixtures of Dirichlet processes (and they are just as fun as they sound!).

Hooked on Practice

However, in the third year of my Ph.D. studies I was involved in a study looking at oil spill risk in Prince William Sound in Alaska, the site of the Exxon Valdez disaster in 1989. We worked for a large stakeholder group including oil company executives and representatives from environmental groups and state and federal government. It was my first experience practicing decision and risk analysis.

The requirements on rigor were at the same level as my more theoretical research, programming a simulation of the study area and its vessel traffic and weather, and building risk models that combined data and expert judgment. But I also had to worry about the decision-makers, their understanding and their objectives, working to support their thought processes. They were making multi-million dollar decisions based on our analysis, but only because we followed the right approach to handling the stakeholder process as well as doing sound and careful analysis.

I was hooked. I went on to do additional oil spill risk studies in Washington state, as well as studies of passenger risk on ferries in San Francisco Bay and Washington state, and to create models used by the U.S. Coast Guard to make safety investment decisions around the country. I have also done projects with Capital One, Deloitte Consulting and most recently Procter and Gamble.

After the Prince William Sound study, I also started teaching at Virginia Commonwealth University. I must admit that I started my teaching career by copying my previous professors. I spent 30 hours a week preparing PowerPoint slides for lectures and thoroughly abusing animations and special effects. Despite the fact that students in the United States enjoy my English accent (or what’s left of it), I found myself boring when I lectured, and my evaluations were not at the level I hoped in my first semester. So I started reading all the literature on teaching operations research.

At the time, there were numerous papers on active learning principles, setting up a business case and developing the techniques to solve the problem [1]. The case method is widely recognized as a breakthrough in teaching quantitative methodologies in business schools ([2], [3]). It provides relevance, the importance of which is well recognized among business school educators [4]. I devoured these papers and then decided it was time to talk to my mum; like everyone else in my family, she was a schoolteacher. My mum taught English and drama; my stepfather taught Latin and Greek; my sister taught law; and my stepsister still teaches in an elementary school. I came away from my conversations with my mother with a few simple principles:

  1. Show your students that you care about them and their learning.
  2. Don’t tell them everything you know; find out what they are struggling with and help them with that.
  3. Tell them why they need to know about a given topic; get them interested.

This last principle led me to start talking about my work in the real world. Discussing important decisions allowed students to understand the relevance of the material we cover. I found the students more motivated and engaged, allowing me to focus on the first two principles.

Jason Merrick (left) receives teaching award from INFORMS Past President Stephen Robinson (center) and committee chair Alexandra Newman (right).

Cooperative Learning

I encourage (and often require) that students read the relevant material from the excellent textbooks now available in the field prior to class. This frees class time for active modeling and problem-solving with me acting as a facilitator after only a brief review. As cooperative learning has been shown to improve the understanding of concepts and interest in the material [5], students are encouraged to work in teams on the problems and cases addressed in class, drawing assistance from the faculty when necessary, but largely from each other. This is, for many, the most enjoyable part of the class and also the most effective in achieving our objective of knowing how and when to use the techniques correctly [6]. I suppose the buzzword is a flipped classroom, but I am pretty sure many instructors were using this approach long before it had a name.

It is also important to think about the type of course you want to teach. Stephen Powell [7] proposed teaching students to be active modelers, able to build “quick and dirty” models to solve common business problems. The results of this transition and the development of powerful, yet intuitive, spreadsheet-based software have had a significant impact on the breadth of implementation of OR/MS techniques. Wayne Winston [8] entreats the instructors of quantitative majors to teach algorithms and theory, asking who else will create the next generation of OR/MS algorithms and techniques. I do not see the choice as either teaching active modelers or algorithm developers, however. Frederic Murphy [9] identifies another important role on this continuum: that of the professional practitioner. He states that practice led to the founding of our field, and it is the practitioner that gives operations research meaning today.

Making Effective O.R. Practitioners

What makes effective practitioners of operations research? First, they have to know the field of operations research. By this we do not mean that they should know all the latest theoretical developments in the research literature. Rather they should have a broad knowledge of the techniques in the field. They should know when these techniques can be applied to solve an organization’s business problems, and they should know how to apply them by constructing appropriate models. In all likelihood, these requirements would be fairly widely accepted by most people in OR/MS. However, these requirements only ensure that the individual is an operations research practitioner, not necessarily an effective one.

While I advocate the role of modeling in teaching students how to identify and implement operations research models in the workplace, successful practice also requires that you do it right. It is my belief that to model correctly, there must be an understanding of the models and algorithms that are being applied. To use a common driving analogy, the everyday driver might be fine with just knowing how to drive a car, but the racecar driver knows what is happening under the hood.

I demand, however, that all theory must pass a litmus test. Why is this theory necessary to ensure the correct application of these techniques? For instance, an understanding of the feasible region of an optimization model can help in choosing an appropriate algorithm to solve it and thus determine what software should be used to implement it. To correctly use an appropriate multiple attribute value model, one must understand the concepts of mutual preferential independence and, if there is uncertainty, utility independence. Theory necessary for delving into the research literature may not be included until a doctoral level course. In this manner, I integrate necessary methodology and algorithm development into the curriculum.

As recognized by Leon Lasdon and Judith Liebman [5], even this more theoretical material can be taught in an interesting and effective manner. Whether the first coverage of theory is by reading or lecture, a true understanding is only reached when the concepts are tested by problem-solving, and the problems are solved more effectively when done together. Thus, the principles of active and cooperative learning are applied as much to the theoretical coverage as to modeling. Moreover, as modeling and application are discussed first in my courses, it is natural for students to ask how the techniques work. If algorithms are approached by examining what may cause them to fail, then students become more interested in how and why they work. In this way, learning is improved.

Project-based Classes

Most of my classes are project-based. While I do set a traditional take-home mid-term, the final assessment of performance in the class is an individual or group project. This allows me to coach students on how to implement the various techniques and methods and how to use operations research and decision analysis in their own careers. Allowing the students to choose their own topics forces them to make the material relevant to themselves and each other. As I teach decision analysis and simulation, this leads to some very interesting projects. I have had students doing work projects to:

  • help a major bank implement new check scanning technology at the teller an average of nine months quicker than their competitors saving $30 million;
  • improve the process for removing counterfeit bank notes at the Federal Reserve;
  • build a simulation of a payment-processing center and use the model to help reduce operational costs by $5 million per year;
  • develop new methods for designing radiation treatments for cancer patients that take the patient’s preferences into account, not just the doctor’s; and
  • assess rehabilitation programs at a local jail to reduce the rate of recidivism.

Students have also done personal projects to:

  • determine whether a spouse should return to work after having a baby;
  • choose treatment and insurance options after learning they had a chronic and debilitating disorder;
  • choose where to live and work after retirement from the military including the challenges of a blended family; and
  • choose a house, apartment, job or car.

I have even used class projects to get the students help in designing a new Ph.D. program and re-design our master’s program.

I did have one reservation in writing this article: I do not believe that an instructor should copy the teaching approach used by another successful teacher. They have a different personality, and they have a different community of students. They also have different experiences in their own practice of operations research. I believe that it is important to leverage your own personality and your own experience, and you should consider the student community at your institution.

I found that my teaching really improved when I relaxed and concentrated on the students learning, not my teaching. I personally get a lot of energy from seeing my students do thorough and careful analysis that helps them in their careers and personal lives. Operations research and decision analysis can have a tremendous impact in our lives, and I enjoy seeing this happen in my own work and in the work my students do. Getting a prize for doing what I enjoy was really just a bonus.

Jason R. W. Merrick ( is a professor in the Department of Statistical Sciences & Operations Research at Virginia Commonwealth University and the 2014 recipient of the INFORMS Prize for the Teaching of OR/MS Practice.


  1. Kolb, D. A., 1984, “Experiential learning: experience as the source of learning and development,” Englewood Cliffs, N.J.: Prentice Hall.
  2. Böcker, F., 1987, “Is case teaching more effective than lecture teaching in business administration? An exploratory analysis,” Interfaces, Vol. 17, No. 5, pp.64-71.
  3. Bodily, S. E., 1986, “Spreadsheet Modeling as a Stepping Stone,” Interfaces, Vol. 16, No. 5, pp. 34-52.
  4. Carraway, R., and D. Clyman, 1997, “Managerial relevance: The key to survival for OR/MS,” Interfaces, Vol. 27, No. 6, pp.115–130.
  5. Lasdon, L., and J. S. Liebman, 1998, “Teaching Nonlinear Programming Using Cooperative Active Learning,” Interfaces, Vol.  28, No. 4, pp. 119-132.
  6. Masoner, M., 1988, “An Audit of the Case Study Method,” Praeger, New York.
  7. Powell, S. G., 1997, “The Teachers’ Forum: From Intelligent Consumer to Active Modeler, Two MBA Success Stories,” Interfaces, Vol. 27, No. 3, pp. 88-98.
  8. Winston, W. L., 1996, “Issues in Education: Software Decisions,” OR/MS Today, Vol. 23, Vol. 5 (October).
  9. Murphy, F. H., 2001, “The Practice of Operations Research and the Role of Practice and Practitioners in INFOR/MS,” Interfaces, Vol. 31, No. 6, pp. 98-111.