Learn how to improve business outcomes by leveraging analytics to make evidence-based decisions.
As the volume of available business data expands, the winners in tomorrow’s marketplace will be those who can generate insight from information. Yet, many leaders feel daunted by the sheer amount of data out there. Many others make the critical mistake of looking for patterns in the data they have, instead of framing productive questions to shape the data they need. Competency in this area is so lacking, a recent Gartner study predicted that by 2020, 80% of organizations will initiate deliberate development programs in data literacy.
Many of the ideas, methods and principles that describe the best business data and analytics practices were pioneered by faculty at the University of Chicago Booth School of Business. In this six-week program taught by Chicago Booth professors, participants learn how to “think data” the Booth way. They develop the critical and creative reasoning skills needed to frame a data analytics project, collaborate with data specialists, and ultimately make evidenced-based decisions that drive results — without sacrificing speed and agility.
By attending this program, you will:
This program is designed for busy leaders—managers, directors, VPs, and C-suite—with the drive and desire to solve their organization’s critical business challenges. This short, focused program allows you to develop solutions for both near- and long-term challenges—without disrupting your day-to-day responsibilities. Job titles include senior leaders, mid-level & team leaders, project managers, and directors.
Sanjog Misra is the Charles H. Kellstadt Professor of Marketing at the University of Chicago Booth School of Business. His research focuses on the use of machine learning, deep learning and structural econometric methods to study consumer and firm decisions. In particular, his research involves building data-driven models aimed at understanding how consumers make choices and investigating firm decisions pertaining to pricing, targeting and salesforce management issues. More broadly, Professor Misra is interested in the development of scalable algorithms, calibrated on large-scale data, and the implementation of such algorithms in real world decision environments.
Professor Misra currently serves as Co-Editor of Quantitative Marketing and Economics and as Associate Editor at Management Science and the Journal of Business and Economic Statistics. He has also served as an Associate Editor at Marketing Science, Quantitative Marketing and Economics, the International Journal of Research in Marketing and the Journal of Marketing Research. Professor Misra is actively involved in partnering with firms in his research and has worked on various projects with companies such as Oath, Verizon, Eli Lilly, Adventis, Mercer Consulting, Sprint, MGM, Bausch & Lomb, Xerox Corporation, Ziprecruiter and Lucent Technologies with the aim of helping them design efficient, analytics-based, management systems that result in better decisions. He currently serves as an advisor to several startups in the marketing technology, measurement and AI space. At Booth Professor Misra teaches courses on Algorithmic Marketing. These courses bring his practical and research expertise in the algorithmic marketing domain into the classroom. He is hopeful that these classes will get students ready for the next evolution of marketing that he believes is already underway.
Prior to joining Booth, Misra was Professor of Marketing at UCLA Anderson School of Management and Professor at the Simon School of Business at the University of Rochester. In addition he has been visiting faculty at the Johnson School of Management at Cornell University and the Graduate School of Business at Stanford University.
Günter J. Hitsch studies quantitative marketing and industrial organization. His research interests include dynamic models of firm and consumer decision-making with a specific focus on dynamic advertising, pricing, sequential experimentation, and consumer discount factor estimation. His recent research focuses on the application and development of ideas from the machine learning and causal inference literatures in marketing and industrial organization, including customer-targeting and optimal pricing. His research also focuses on understanding the structure of the U.S. retail industry, with a specific focus on pricing and promotion setting.
Hitsch's research has been widely published and he has been invited to give talks at the University of California at Berkeley, Harvard University, Stanford University, Columbia University, Yale University, Northwestern University, and the Massachusetts Institute of Technology.
He is the recipient of two Kilts Center Fellowships, a True North Communications Inc. Scholarship, and a Fellowship from the Ministry of Science in Austria. Hitsch is a member of the American Economic Association, American Marketing Association, the Econometric Society, and INFORMS.
He earned an undergraduate degree from the University of Vienna in 1995. Hitsch received a master's degree in economics in 1997 and a master's degree in economics in 1998, as well as a PhD in economics in 2001 from Yale. He joined the Chicago Booth faculty in 2001.
Hitsch enjoys skiing, cooking, and classical music. He wants his students to learn that "good marketing isn't fluffy."
Using primarily observational data, Pope studies how psychological biases play out in field settings and economic markets. Examples include left-digit bias and projection bias in car markets and time inconsistency in housing markets.
Prior to joining the Chicago Booth faculty in 2010, Pope was on the faculty at the Wharton School at the University of Pennsylvania. He earned a PhD in economics from UC Berkeley in 2007 and a BA in economics from Brigham Young University in 2002.
This program is taught by Chicago Booth professors in partnership with ExecOnline.
Please note: Registration for this program closes one week before the start date.
The program fee is $4,500-5,700; please ask us about individual and group pricing packages.