Introducing Prescriptive and Predictive Analytics to MBA Students with Microsoft Excel

Abstract

Managers are increasingly being tasked with overseeing data-driven projects that incorporate prescriptive and predictive models. Furthermore, basic knowledge of the data analytics pipeline is a fundamental requirement in many modern organizations. Given the central importance of analytics in today’s business environment, there is a growing demand for educational pedagogies that give students the opportunity to learn the fundamentals while also familiarizing them with how such tools are applied. However, a tension exists between the introduction of real-world problems that students can analyze and extract insight from and the need for prerequisite knowledge of mathematical concepts and programming languages such as Python/R. As a consequence, this paper describes an application-focused course that uses Microsoft Excel and mathematical programming to introduce MBA students with nontechnical backgrounds to tools from both prescriptive and predictive analytics. While students’ gain proficiency in managing data and creating optimization and machine learning models, they are also exposed to broader business concepts. Teaching evaluations indicate that the course has helped students further develop their practical skills in Microsoft Excel, gain an appreciation of the real-world impact of data analytics, and has introduced them to a discipline they originally believed was best suited for more technically focused professionals. Supplemental Material: Supplemental materials are available at https://doi.org/10.1287/ited.2023.0286 .