How Business Schools Can Integrate Data Analytics into the Accounting Curriculum

Norbert Tschakert, PhD, CPA, CFF, CITP, CFE, CIA, CMA, Julia Kokina, PhD, CPA, and Stephen Kozlowski, CPA, CGMA, and Miklos Vasarhelyi, PhD

The demand for accountants with data analytics skills is growing rapidly, providing for exceptional career opportunities. A recent McKinsey Global Institute study asserted that, even with additional university programs in data analytics becoming available, companies will need to train employees internally for many years to overcome the current skills shortage (“The Age of Analytics: Competing in a Data-Driven World,” December 2016, http://bit.ly/2fyfoVU). McKinsey also noted that, while the estimated number of data science programs graduates could increase by 7% per year, the high-case scenario indicates a 12% annual growth in demand, leading to a shortfall of some 250,000 data scientists. In addition, McKinsey described the equally important role of the business translator, who acts as the link between the analytical talent and the practical application of the analytical results to address business requirements. The requirements for these business translators include not only an in-depth understanding of the data, but also organizational knowledge and industry or functional expertise that enables them to ask the data scientists the correct questions and derive the appropriate insights from their findings. These requirements appear analogous to the traditional requirements that an accountant be able to understand and explain the accounting results, but in this case, that expertise includes numerous forms of data.