- Richard Herschel
In a May 2011 report, the McKinsey Global Institute predicted that there will be a shortage in the coming years of the analytical talent necessary for organizations to take full advantage of “big data”—the growing pools of both structured and unstructured data that companies are collecting and looking to analyze.
By 2018, the report said, the U.S. could have an unanswered need for 140,000 to 190,000 workers with deep analytical skills, plus 1.5 million managers and business analysts who could put the results of big data analytics applications to good use in making effective business decisions. If it does come to pass, the lack of analytical and decision-making expertise could negatively affect the ability of organizations to derive business value from the information they’re capturing and then leverage data-driven strategies to innovate and increase their competitiveness.
To avoid such consequences, companies and educators should make a coordinated and concerted effort to do the following:
- Create awareness among high school and college students of the critical need for analytical talent in corporate enterprises.
- Develop more higher-education programs that can effectively train and prepare a talent pool of graduates with the skills required to evaluate and gain insight from information, especially big data.
The first point is much harder than anyone thinks. In my experience, most incoming college students have never heard of business intelligence (BI), business analytics or even big data. Moreover, most colleges and universities, especially those with liberal arts programs, don’t have any courses that even discuss those terms. As a result, many technologysavvy students with strong mathematical backgrounds might choose to major in something that is not necessarily in accord with market needs.
One potential solution to the problem would be to develop a concerted campaign to increase public awareness of BI and analytics. This could be done through the creation of something equivalent to the Ad Council. The council’s website states that it is “a private, non-profit organization that marshals volunteer talent from the advertising and communications industries, the facilities of the media and the resources of the business and non-profit communities to deliver critical messages to the American public.” A “BI/Analytics Council” with strong industry support could produce, distribute and promote public service campaigns to increase awareness of the need for analytical skills and encourage the addition of new educational programs focused on developing BI and analytics talent.
The second point is the urgent need to develop more comprehensive, integrated BI and analytics degree programs in our universities. Today there are only about 20 colleges and universities offering advanced degrees in business analytics, and even fewer offering such degrees in business intelligence. Recent research conducted by professors Barbara Wixom of the University of Virginia and Thilini Ariyachandra of Xavier University in Cincinnati found that much of the available BI curriculum is taught within the information systems discipline. Their research also found that most universities offering BI as a subject cover it in a few general classes instead of BI-specific courses.
Preparation Requires Integrated Education
Professors Ronald Klimberg and Virginia Miori of Saint Joseph’s University in Philadelphia argue that BI and analytics programs should integrate three disciplines: information systems, statistics and modeling. They assert that business analytics is a combination of business statistics intelligence and business modeling intelligence, and that BI adds the element of business information intel- ligence. Their model suggests that education in any one discipline alone offers students inadequate preparation for careers in BI and analytics. The upshot is many of the academic institutions that do offer BI courses and programs may not be doing so in a comprehensive and integrated manner.
To become qualified BI analysts or data scientists, students need coursework covering topics including but not limited to databases, enterprise data, data mining, statistics, decision modeling, predictive analytics, business process modeling, critical performance management, data visualization, risk analytics and Web analytics.
The problem for many universities is that the knowledge needed to support BI and analytics programs is spread across multiple departments, making the creation of an integrated degree program difficult. Ideally, all required course components would be housed in and taught by one department. But in business schools, for example, BI is not perceived as a traditional business discipline such as marketing, accounting or finance. Hence, statistics and modeling might be taught in one department and information systems in another, but they are not necessarily interrelated with one another or aligned with BI and analytic objectives.
In some cases, relevant content can be spread across different colleges at the same university (e.g., the business and the arts and sciences schools). As a result, unless university officials see the merit in restructuring departments to create a BI and analytics degree program or can effectively structure an interdisciplinary degree program, they will not be able to successfully prepare candidates with the type of integrated educational background that Klimberg and Miori propose.
To prevent a continued shortage in the available amount of skilled BI and analytics professionals, we need to be proactive in helping both students and universities understand the opportunities that this field presents. And we need to push academic institutions to develop more undergraduate and graduate degree programs that provide the relevant coursework their students will need in order to meet the ever-increasing demand for BI and analytics expertise.
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