Abstract
Published in El Mercurio, this column explores the conceptual trap of modern “data-driven” organizations that rely solely on historical data and predictive models. I argue that predicting the future without a decision framework is like driving a car while only looking in the rearview mirror. To truly connect data with effective action, organizations must embrace Operations Research (OR). By combining data science with mathematical modeling and optimization, OR provides prescriptive analytics that dictate the best course of action under real-world constraints. The column highlights practical applications in energy management, public healthcare waiting lists, and industrial maintenance. Ultimately, it proposes that the challenge for modern leaders is not to become data scientists, but to become architects of decisions.
