Innovative Education: Analytics and the MBA program core

Why it is essential for every future manager to have an understanding of analytics and data.

By Peter C. Bell

Peter Bell

All photos courtesy of Ivey School of Business.

I recently attended the EURO conference in Glasgow, Scotland, and found the atmosphere to be very upbeat, reflecting my own perception of the current state of MS/OR/analytics (hereafter “analytics”). Researchers, practitioners and many academics believe that their work is being appreciated and that the future of analytics looks brighter than it has for many years. However, amongst this general sense of well-being, I heard that two major business schools have eliminated analytics from the core requirements for their MBA degree. One (Warwick) has switched analytics from required to elective in the full-time MBA program, while a second (Lausanne) has restructured their MBA core so that students can elect out of some former core courses, with the result that many elect out of analytics. Business schools have been dropping analytics from their MBA core for decades, and this data shows that despite the increasing buzz about analytics in the press and in business, this trend may be continuing.

At the same time we have seen an explosion in the appearance of master’s degree programs in analytics (usually M.Sc. degrees), with many of the 200-plus new programs that have appeared in the last decade being offered through business schools. It appears that many business schools believe that analytics represents a growth opportunity but are unconvinced that analytics should be a required part of an MBA or business program. In my view, graduates of business programs are important to the future of analytics; those who understand the value of analytics and know enough analytics to spot opportunities where analytics can add value will either hire analytics professionals or outsource analytical work.

Essential Skills

I, and many of my colleagues in analytics, strongly believe that it is essential for every future manager to have an understanding of analytics and data. Decision-makers will increasingly be exposed to recommendations and results derived from data and models, and they need to be able to assess the credibility of the assumptions and analysis as they decide what weight they will give to the analytics in their decision-making. However, while we in analytics think that the world has come to accept and value our skill set, many outside our field do not agree with us or are resisting this change. If we believe that every business student needs a basic understanding of analytics, how do we make this case to our academic colleagues?

Many business school faculty believe (and teach) that experience, intuition and leadership skills are the most important qualities for managers and may not attach great value to data and models as aids to business decision-making. These same colleagues may control program budgets and program design, and, if we are successful at teaching our students to be more analytical, these colleagues may have to change the way they deliver their own courses. For example, MBA students taking an operations management course following my analytics course complained that the instructor ignored an obvious opportunity to build an optimization model when discussing a case that required simultaneous decisions. In addition, a colleague teaching marketing happily told me that he refused to allow Excel models to be used in his classroom because when students had the model the decisions were obvious, and he could not have the kind of discussion he wanted. Given that increasing the analytical content of a business program is potentially disruptive for our colleagues and is likely to meet resistance, how can we make the case that we belong as a required component of every business program?

Peter Bell is a recipient of the INFORMS Prize for the Teaching of OR/MS Practice.

Hard data to support the importance of analytics core courses in business programs is scarce. We can cite the frequent surveys that show large numbers of jobs open for analytics professionals although this plays directly into the hands of those planning or offering master’s degrees in analytics where the objective is to train people to actually do advanced analytics. Perhaps more relevant data is the explosive growth in outsourcing and offshoring analytics (as illustrated by GENPACT, Mu Sigma, Cognizant, Dell Global Analytics and recently Walmart in India), suggesting that increasing numbers of businesses are buying analytics and facing the kinds of complex business decision issues surrounding outsourcing and offshoring analytics [1]. Finally, we can talk about analytical CEOs such as Jeff Bezos (Amazon) or analytical powerhouses (IBM, Walmart) where analytics is a major component of business strategy and has a direct impact on the ways these firms are managed. All this, however, is indirect evidence; ultimately we need to do a better job in marketing a basic understanding of analytics as an essential component of the future manager’s skill set.

CEO’s Analytical Model of Life

“Teaching future managers about the importance of analytics” or “surviving as an MBA core course” are noble objectives, but these are tough to operationalize. A former student, who has been a very successful CEO at several companies, visited my class for a guest lecture. He was asked what is the first thing he does when he becomes CEO of a new firm. His surprising (at least to the class!) reply was that he builds an Excel model of the firm and highlights the cells whose future values will determine his success or failure, then backtracks through the model to find those things that he can change that will positively affect the highlighted cells. With this understanding, he starts work. This “analytical” model of life as a CEO applies equally well to our teaching.

Business schools have many different market positions, and so there will be many different highlighted cells (“objectives”) across schools. A first step for all faculty is to understand your school’s positioning and to be sure that your activities support that position. Three objectives that seem to be important for most business schools are the “rankings,” student satisfaction (an important contributor to the rankings) and opinions from recruiters who hire your students. Analytics faculty who are looking to prosper in a business school may find it helpful to examine how their activities can be directed towards these objectives.

Ivey logo

There are many business school rankings published annually, and the differences in the ranking of a school are often huge. For example, the Ivey Business School at Western University in Ontario, Canada, where I teach is a globally recognized general management school with a strong focus on leadership. The recent Bloomberg Business Week [2] rankings rated Ivey’s MBA at the top of 209 international MBA programs, while the 2015 Financial Times ranking has Ivey at number 97 [3]. How can the rankings be so different and how does this impact our objectives? First, not all schools contribute to all the rankings; it is just too much effort. Second, schools pay more attention to those rankings that support their market position. Again using the Ivey example, we do very well in rankings that emphasize student (or alumni) and recruiter opinions, job placement statistics and starting salaries.

Many would think that positioning as a general management/leadership school was incompatible with a strong presence for analytics, but “The Bloomberg Recruiter Report” [4], “based on a survey to 1,320 recruiters at more than 600 companies around the globe to discover the skills that are in high demand by employers and which business schools are best at teaching those skills,” suggests otherwise. According to the report, the recruiters ranked Ivey first among 122 global MBA schools for the teaching of leadership skills, strategic thinking, ability to work collaboratively and communication skills – all skills closely aligned with “general management” and “leadership.” Surprisingly to many, Ivey was ranked second in teaching quantitative skills (first place went to the Tepper School at Carnegie-Mellon University) and in third place for teaching analytical thinking (after the Sloan School at MIT and Chicago-Booth.)

School Ranking Lessons

Important lessons from these rankings are that Bloomberg sees quantitative skills and analytical thinking as “skills that are in high demand by employers” and uses recruiter opinions to assess these skills. This provides two very specific objectives for business school analytics faculty: first, to improve the quantitative and analytical skills of our students as seen by recruiters, and second, to focus attention on those skills in demand by the job market so that graduates meet or exceed recruiters’ expectations.

Comparing the Ivey MBA program curriculum with that of the No. 1 ranked Tepper School for quantitative content, it is immediately apparent that there are multiple ways to attack these objectives. Tepper’s approach to analytics is to market analytics as a major part of Tepper’s masthead: “Leadership + Analytics = A Powerful Career Advantage.” “We are one of the few MBA programs able to deliver a high level of preparation and training in both leadership and strategic analytics.” The Tepper MBA curriculum is very analytical and includes three required “quant” courses (“probability and statistics,” “optimization” and “statistical decision-making”) plus a required “managerial economics” course and two required “operations” courses.

In contrast, you won’t find much about “analytics” in the publicity materials for the Ivey MBA: “The Ivey MBA is a transformational experience for ambitious leaders who want to hone their skill set, develop their leadership abilities and accelerate their career success.” If you looked hard, you would find a single core course “decision-making with analytics” and an optional pre-program “quantitative analysis primer” for those who feel the need to get up to speed in Excel or basic statistics.

My limited research suggests that Tepper and Ivey may occupy the extreme ends of the spectrum from “analytics heavy” to “analytics light,” yet both are (according to Bloomberg) successful, suggesting that there is more than one way for business students to acquire quantitative skills. It is also likely that the success both schools have achieved with recruiters is no accident. Certainly the success that Ivey has had has been driven by a determination to offer great business courses that use analytics, and we measure our success very directly through feedback from students and recruiters.

Bloomberg Business Week rated Ivey’s MBA at the top of international MBA programs.

Understanding student expectations and needs is the first step toward creating positive student feedback. Ivey students are interested in learning about business, so we believe that our courses should be about business first and analytics second. Our case teaching methodology supports this view; cases provide examples of real business problems and often include considerable details on real companies, industries and business people. A student-centric approach to delivering analytics requires balancing attention devoted to the business issue with the technical details of the analytics. Talking to colleagues teaching in programs where analytics is not flourishing leads me to believe that often the major reason for the lack of traction for analytics is a gap between the instructor’s desire to deliver technical content and the students’ desire to learn about business. Part of the issue appears to be that the supply chain for business school faculty does not include much exposure to business and management.

We have hired new analytics faculty almost every year for the last 10 or so years, and it can be a depressing process. We receive hundreds of applications from Ph.D.s in MS/OR/IE/analytics, and I first look for candidates with a degree in business or any evidence of any interest in business. This cut usually reduces the pile from hundreds to tens. I once suggested to a colleague that I thought that all faculty teaching business analytics should have an MBA and this was met with outrage. But you would not expect to be hired to teach university English without a degree in English or chemistry without a degree in chemistry. Why should business be any different? However, I can’t remember the last time I saw a job application from a strong candidate with a Ph.D. in “analytics” and an MBA so the issue is moot.

Fundamental Issue

The fundamental issue facing analytics instructors in business schools is that there are no “analytics” problems, but there are many marketing, finance, human resource, operations, etc. problems where analytics is really helpful in coming up with a solution. Teaching cases provides a convenient way to handle both business and analytical issues while encouraging student participation and interaction and developing other important skills such as communication and teamwork. While teaching cases requires a different mentality from lecturing and some cost in classroom setup and administrative overhead, a switch toward this reality-based way of teaching analytics might be helpful if your core course is not attracting rave reviews from your students or recruiters.

Finally, as faculty we are accountable for the courses we deliver. While exclusion from the business school core can occur suddenly, prospering and growth is a much slower process. We prosper as a teaching area based on student and recruiter feedback. If we teach a great core course and market our electives well, we will have full electives and be invited to add more. Adding more electives enables the group to add more faculty, enabling it to add more electives and so on. Having key recruiters commenting positively on the “quantitative skills” of your students almost guarantees a place for analytics in the MBA program core.

Peter C. Bell ( is a professor of management science at the Ivey School of Business at Western University in Ontario, Canada. He is a past recipient of the INFORMS Prize for the Teaching of OR/MS Practice, served as chair of the 2013 and 2014 INFORMS Franz Edelman Prize Competition and as 2014 and 2015 chair of CPMS: The Practice Section of INFORMS. He is a frequent invited contributor to OR/MS Today, particularly the special “Innovative Education” issue.


  1. Fogarty, David, and Peter C. Bell, 2014, “Structuring the analytic BPO relationship: Sending your analytics offshore can be a winning strategy, but only if it’s carefully managed,” MIT Sloan Management Review, Vol. 55, No. 2 (Winter 2014), pp. 40-45.