Ben Shields is a Lecturer in Managerial Communication at MIT Sloan. His research focuses on the intersection of social media technologies, data analytics, and audience behavior in the sports, media, and entertainment industries. He is the coauthor of two books: The Sports Strategist: Developing Leaders for a High-Performance Industry (Oxford University Press, 2015) and The Elusive Fan: Reinventing Sports in a Crowded Marketplace (McGraw-Hill, 2006). Shields served previously as the Director of Social Media and Marketing at ESPN. Recently we asked him a few questions about the topic of sports analytics and his upcoming MIT Sloan Executive Education program, Analytics Management: Business Lessons from the Sports Data Revolution.
MIT: The MIT Sloan Sports Analytics conference is happening in the spring. Can you tell us a little about this conference?
Shields: The MIT Sloan Sports Analytics conference is the premier event in the industry. Founded in 2007 by MIT Sloan alum and Houston Rockets General Manager Daryl Morey and CEO of Kraft Analytics Group Jessica Gelman, the conference has grown from about 175 participants in its first year to more than 4,000 in 2016. A similar crowd will be on hand this year.
The conference is the nexus point for the most innovative researchers, executives, and students to share new analytics approaches, debate current trends, and network. It is an energetic, fun, and fascinating event that never fails to make you smarter.
MIT: Following the conference is the very first session of your new MIT Sloan Executive Education program, Sports Analytics Management. Is this program intended to pick up where the conference leaves off? What prompted you to design this course?
Shields: Through the influential conference, MIT Sloan has become a hub for sports analytics research and practice. However, the conference lasts only two days. With our Analytics Management course, we are expanding the dialogue and learning opportunities about this fast-growing and exciting field of sports analytics throughout the year.
Our course is designed to complement and extend key themes from the conference. Critically, we focus on helping students develop an analytics strategy and program that works for their organization or initiative. Whereas conference attendees will learn about new research methods and key trends, students in Sports Analytics Management will have the opportunity to synthesize this new knowledge into actionable plans going forward. Today, the biggest barrier to unlocking the potential of analytics is often not a technical one; it’s how leaders and organizations set up and manage an analytics program. We address the latter in our course.
The sports industry has been a pioneer in the analytics revolution, and there is so much we can learn about analytics management from studying it. I designed this course to help executives in all industries identify strategies and best practices in sports analytics and apply and refine them to their own efforts.
MIT: What lessons can the management community outside of sports take from this sports data revolution?
Shields: Sports are our petri dish to understand how analytics, if effectively deployed, can lead to better decisions and more successful organizations. Although analytics in sports may seem different from other industries, the similarities are stronger than they appear. Sports teams use analytics to achieve two overarching organizational goals: win games on the field and run profitable businesses off the field. They develop strategies in pursuit of these goals, and make a series of decisions along the way. To lead organizations to the best decision, executives and staff members will analyze a variety of information sources, including qualitative data, quantitative data, experience, and gut instinct. Importantly, this information must get to the right people, at the right time, and be communicated in a way that’s clear and with appropriate context. Then, once the decision is made, organizations need to be equipped to measure the results of those decisions and iterate on the strategy going forward.
This process of goal setting, strategy development, information gathering and synthesis, decision-making, implementation, measurement, and iteration is replayed consistently in the most advanced data-driven organizations. And for our work in Analytics Management, it will serve as a transferrable framework for organizations in other industries as well.
MIT: What are some of the main roadblocks organizations face when trying to establish an analytics program?
Shields: In my research, I've consistently seen that the most successful data-driven organizations have two essential types of talent: (1) analytics staff and (2) leaders that can manage an analytics transformation. Organizations need both to succeed. Teams can have savvy data scientists, but if their analytics program is not designed, organized, and implemented in a way that translates data into action, they will not realize their full potential.
MIT: What has made the NBA such an exemplar of the data-driven revolution?
Shields: It is important to note that many leagues and teams across the sports industry are now embracing analytics to make better decisions. Historically, teams in Major League Baseball are widely considered first movers in analytics, with Michael Lewis’s book-turned-movie Moneyball chronicling Oakland A’s general manager Billy Beane as the most famous example. But teams in other leagues have followed suit, and today many organizations across the global sports industry are embracing analytics in a variety of ways.
The NBA in particular has been at the forefront of analytics. The critical driver for the league has been its innovations in data collection technology on both the player personnel and business side. From a player personnel perspective, each arena is now equipped with six STATS SportVu cameras that catalogue 25 frames per second. This technology has enabled innovative applications of analytics, informing free agent decisions as well as game plans. From a business standpoint, the NBA’s teams are using their digital, mobile, and social platforms to better understand their fans and drive additional ticketing, media, and merchandise revenue.
Importantly, analytics-focused teams in the NBA and beyond are implementing a holistic data-driven approach to accelerating many functions of their business. We will delve deeper into these models in our course.
MIT: In your writing and research, you have said that sports organizations must be successful businesses without always winning on the field. Can you explain?
Shields: In sports, only one team wins a championship every year. And for that team, business usually could not be better for that season. But what about the other teams who do not reach the pinnacle? They must still run winning businesses. To do so, they must focus on elements of their business that they can shape and control, including their brand identity, digital content experience, and in-venue experience. Sports organizations that have built profitable businesses have expertly understood the variability in their on-the-field product and implemented strategies to withstand the inevitable periods of losing and maximize their moments of winning.