At its core, analytics has always been part of MBA programs. Managers in all industries need the skills to analyze information and develop actionable insights from it.
In recent years, though, demand for managers with analytics skills has really taken off. Companies have more data than ever, and they're looking for professionals with the ability to handle it. As a result, business schools are completely reimagining their analytics programs.
“The difference today is the volume of data,” says Elkafi Hassini, associate professor at McMaster University's DeGroote School of Business.
Indeed, Big Data is pervasive across many industries, and firms are struggling to find managers who can deal with huge volumes of ones and zeros.
DeGroote is one of many schools that offer a breadth of analytics classes in their MBA programs. The school also recently launched an Executive MBA program in Digital Transformation where they will focus on teaching students the skills to ask the right questions, especially in conjunction with data analytics.
DeGroote is not the only university growing their analytics courses, other schools include MIT’s Sloan School of Management, NYU’s Stern School of Business, the Cox School of Business at Southern Methodist University, Virginia Tech’s Pamplin College of Business and Wake Forest University.
The influx of data means not only new courses but also new technologies, skills, and teaching methods. Along with hard skills, like coding and statistics, students also need solid a foundation in soft skills like communication.
As a result, many universities are working to restructure their analytics concentrations from the ground up.
“Play” and practice as important as theory
Modern analytics programs demand a certain amount of tech savvy and software knowledge; however, there are simply too many new software programs for MBA students to learn them all. From software that helps with data mining to modeling, there are countless options available to choose from.
The sheer number of tools make it impossible for any MBA program to address them all. As a result, many business schools are focusing more on getting students comfortable with data and the tools in general. It is then up to students to decide which software programs they would like to master. It also means students must be ready to adapt to new companies and whatever their chosen toolset includes.
Companies don't need expert coders but rather “people who will adapt quickly,” explains Hassini. “People who would have the basics in terms of ability to learn new languages, to code. Familiarity with statistics and models and algorithms. People who could model whatever business problem is thrown at them.”
This means that many MBA programs in analytics allow students to simply play with data in the classroom. In fact, the idea of “play” is a deliberate part of these new programs. Students will be expected to take theoretical knowledge and regularly apply it in hands-on, active, and creative ways. Statistics or predictive analytics aren’t just about numbers but decision making.
“You want students to play with the data,” says Michael Trick, senior associate dean of faculty and research at Carnegie Mellon's Tepper School of Business. “You find large data sets to create activities, cases and so on, where they are really working with the data.”
Increase in demand means an increase in options
The Mendoza College of Business at the University of Notre Dame, which offers an MBA concentration in Business Analytics, is also betting that analytics is here to stay.
“Demand for the business analytics concentration here has exploded,” says Rob Easley, associate professor at Mendoza, adding that “many of the firms you talk to now are really only just getting started.”
Easley notes that beyond being able to understand data effectively, analytics-minded students must also be ready to communicate their findings effectively. “Courses on communicating effectively, writing about the analysis and presenting the results effectively,” he says, will prove invaluable.
Particularly, students must be ready to share their findings with managers and co-workers to create a more effective dialogue. While this includes an analytic and scientific mind, soft skills like leadership and creativity remain highly important for good execution.
Analytics not just "backroom" number crunching
Alongside new technology skills, MBA programs in analytics are also helping students learn to apply analytics to fields that have not traditionally been data-heavy. “This is not just a bit of backroom stuff providing a number that might go in the back of a report,” says Trick.
“Rather, a lot of analytics today is really defining company strategy.”
Since this need cuts across many industries, business schools have launched a burgeoning array of specialized MBA courses. From operations to healthcare and social media, analytics is being applied to different areas. While shorter or more direct programs may include a smaller, more specific set of basic courses, universities with specialized tracts in analytics are likely to offer several electives that could prepare student for very different fields. Students in Columbia Business School’s elective in Sports Analytics, for example, apply their analytical skills to issues in football, baseball, and other sports.
Business analytics programs still evolving
An unexpected, and perhaps often forgotten, development is the evolution of ethics in relation to data collection and usage. Modern regulation of data is murky to begin with and many universities are struggling to adequately prepare students for ethical—and legal—questions. Indeed, in 2015 Harvard Business Review said that “oversight for algorithms” and “data privacy” are among the top trends that business professionals cannot ignore. As a result, many specialized programs are adding entire courses on the ethics of data collection and ownership. For instance, as part of its Master of Science in Business Analytics program, students at NYU are required to take a class in “Data Privacy and Ethics” that looks at the complex ethical issues behind data collection.