“For an MBA student, it’s very important to understand how you will encounter a problem in the real world,” says Arnie Greenland, a professor at the University of Maryland’s Robert H. Smith School of Business.
“You have to excel at more than the technical side of optimization to succeed in business—you have to understand the human side and change management,” he says. “Often, the hardest part is getting the client to understand the value of a solution and use the results properly.”
Professor Greenland uses my book, The Optimization Edge: Reinventing Decision Making to Maximize All Your Company’s Assets (McGraw Hill), to present realistic experiences in applied optimization, challenges to implement solutions, and tips to overcome them.
For nearly 40 years, he worked on massive models for a wide variety of organizations as a consultant at IBM, PwC and other firms. His expertise is in stochastic work such as simulation, queueing theory and statistics of regression. Two years ago, Professor Greenland retired from IBM and joined the faculty at Maryland. His title is “Professor of the Practice,” which he says is akin to a clinical professor at a medical school.
He teaches “Decision Analytics” and “Data Mining,” two classes in a program designed by his colleague, Professor S. Raghu Raghavan, who received the INFORMS 2016 Prize for the Teaching of the Operations Research/Management Science Practice.
“Decision Analytics” entails five weeks of optimization study, followed by two weeks of simulation. The students read a book chapter each week and discuss it for 30 minutes at the end of each class. Professor Greenland first addresses the types of models one can build, relying on Kenneth Baker’s book, Optimization Modeling with Spreadsheets. Then he addresses the realistic business and human elements with The Optimization Edge.
“You have to maintain the model for the end user—you can’t just deliver it and get out of there,” notes Professor Greenland. “Successful optimization is a long-term commitment.”
Professor Greenland’s students, two sections of 40 students each, also take the core survey class, “Data Models & Decisions.” The program has helped make Analytics a popular area of study. “These are ‘must take’ classes for MBA students, especially those with engineering or technical interests,” Professor Greenland says. “They know they have to understand analytics.”