Could LeBron James’ recent 17-game inactive streak — the longest of his career — actually make the Los Angeles Lakers a better team?
Research co-authored by a strategy professor at Stevens Institute of Technology using NBA data suggests that a star’s temporary absence can improve the team’s overall performance when he returns (over and above pre-absence performance). And that should be true of teams beyond the basketball court — especially in business.
“Firms that organize themselves around a star can become overreliant on that star,” said Dr. Pranav Garg, assistant professor at the School of Business. “In the star’s absence, two effects kick in to improve teamwork: first, the non-stars, who until now were overshadowed by the star, have the opportunity to showcase their skills. Second, the team develops new routines or processes to compensate for the star’s loss. The firm can combine these routines with the pre-absence routines upon the star’s return.”
Dr. Garg, who joined Stevens in August 2018, focuses on the microfoundations of strategy in his research. He uses econometric techniques to process and analyze data on firms, all in an effort to understand how decisions at the level of individuals and teams impact firm performance.
“Until 15 years ago, most strategy research treated the firm as a black box,” Dr. Garg said. “It was a dot in a larger landscape. As data becomes more digitized, you’re getting more granular data at the team and individual levels. That kind of access allows you to ask new questions.”
Business tradeoffs and classroom lessons
By delving into this black box, Dr. Garg hopes to challenge existing assumptions and “highlight novel tradeoffs that managers must contend with,” such as the tradeoffs that pharmaceutical companies make in sourcing external knowledge. According to a paper co-authored by Dr. Garg in the December 2018 issue of Strategic Management Journal, these companies must weigh the short-term costs of keeping a low-performing division afloat against the high re-entry costs of shuttering, then reopening, such a division in response to a promising opportunity in the future.
“You can have the fanciest of strategies made at the top, but it's those people at the operational level who also have the power to determine the firm's overall performance.”
Compromises like these are inherent in business strategy across all industries, which is why Dr. Garg uses case studies in the classroom in order to prepare students to think — and make decisions — like managers.
“As a manager, you are always making tradeoffs,” he said. “Most options are never unambiguously good nor unambiguously bad. I push my students to think more comprehensively about each situation when making a choice.”
Dr. Garg’s own industry experience has given him insight into the different factors that lead to a company’s success. He worked as a manager at Hindustan Unilever Limited — often called the “CEO Factory of India” — which he said “left an indelible mark” on how he thinks about business strategy.
“You can have the fanciest of strategies made at the top, but at the end of the day, it’s those people at the operational level who have to execute it,” he said. “They also have the power to determine the firm’s overall performance.”
New tools for research
After three years at Unilever, Dr. Garg went on to get his Ph.D. at the University of Michigan’s Ross School of Business, pursuing a passion for academia that runs in his blood.
“Both of my parents were professors and one of my brothers pursued a Ph.D. as well,” he said. “When I decided to get my Ph.D., a friend joked that I was finally getting into the family business.”
Though some may have found the trappings of a corporate career more enticing, Dr. Garg said he “always loved the space of ideas and abstraction,” which keeps him motivated and engaged in his research. “Every project teaches you something new and can lead you somewhere you never expected to go,” he said.
Dr. Garg didn’t expect his research to lead him to the realm of machine learning, but now that he’s beginning to use it as a tool to better analyze granular data, he’s grateful to be at a place like Stevens.
“So many people at Stevens are using the latest techniques for working with data,” he said. “And there’s a community-like feel here, so if I have a question, another faculty member or researcher is just a phone call or a few steps away. I feel quite confident that I will find my answer somewhere on campus.”