A major upset unfolded in this year's Major League Baseball postseason. The Los Angeles Dodgers, who had assembled a roster of All-Star caliber players including Shohei Ohtani, Yoshinobu Yamamoto, Blake Snell and Tarik Skubal, were swept 4-0 by the Milwaukee Brewers in the National League Championship Series. In the American League Championship Series, the winner was the Tampa Bay Rays rather than wealthy clubs that pour in vast sums, such as the New York Yankees and the Boston Red Sox. Data-driven management is cited as the reason these "small market" clubs — whose total player payrolls rank in the lower half of MLB's 30 teams — performed so well.
In an interview with The Seoul Economic Daily on the 20th, Kim Hye-joo, former CEO of Lotte Members, said a wide range of players — sports clubs, governments and companies — are getting results by making decisions through the use of data rather than intuitive judgment. "Using data is a factor that determines the competitiveness of both organizations and individuals," she said. Kim is a data specialist who has handled data analysis and utilization at major companies across several industries, beginning at SAS Korea and continuing through SK Telecom, KT, Samsung Electronics and Shinhan Bank. From 2023 until early this year, she served as CEO of Lotte Members, the Lotte Group affiliate that runs the conglomerate's membership service, where she led efforts to improve services using customer data and to identify new businesses. Drawing on her long experience in the corporate field, she recently published "Clue," a book laying out methods and a philosophy for using data.
Sports is one of the areas where data use has produced the clearest results. The Oakland Athletics of the 1990s and 2000s, the subject of the film "Moneyball," reaped enormous gains from data-driven baseball. "Billy Beane, Oakland's general manager at the time, focused on on-base percentage — a metric other clubs were not paying attention to but one that actually translates into runs — and acquired players the market had undervalued," Kim said. "As a result, the team had one of the lowest payrolls but posted top-tier results, including the first 20-game winning streak in American League history in 2002." She added that "the one who read a different story out of the same data won," and said this requires an understanding of how data is generated and of the relevant background knowledge. "Data is a byproduct and a trace of actions that occur in various situations," she said. "Through the effort to interpret data more deeply, you can understand the process by which that action took place and the background behind it."
Kim identified rational decision-making as the biggest purpose of using data. "Intuitive judgment can be wrong if your condition is poor at the moment a decision has to be made, or if preconceptions formed on the basis of incorrect information come into play," she said. "Data, by contrast, can support rational judgment grounded in objective information."
Kim stressed that in the AI era, "storytelling" capability built on an understanding of data is becoming more important. "AI still cannot take over the role of defining a problem and judging what data is needed to solve it, or the role of conveying analytical findings in language a decision-maker can understand," she said. To become a "data storyteller" with those skills, she advised, one needs practice in connecting data to everyday life. "You can translate an abstract concept you are curious about in daily life into measurable data, and then think about how you might obtain that data," she said. As an example, she pointed to testing the folk saying that moving house on a rainy day brings wealth. "If you practice by defining the moving date as something like the date of a change-of-address registration, and then working through what data you would need — weather agency data for that date, average monthly spending after the move and so on — you can build storytelling capability," she said.
She also proposed easing regulations to further promote the use of data. "When consent procedures for the use of personal data are complicated, it is cumbersome for users, and companies have difficulty acquiring users and managing records," Kim said. "Rather than making consent procedures inconvenient, it is preferable to strengthen the security of personal data." She also called for regulatory improvements on combining data from different fields. "If financial and health data are combined and put to use, a variety of services could emerge, such as managing medical costs according to life expectancy," she said.
