Faculty
Emilio J. Castilla is the NTU Professor of Management and a Professor of Work and Organization Studies at the MIT Sloan School of Management.
Castilla is currently the co-director of the Institute for Work and Employment Research. He joined the MIT Sloan faculty in 2005, after being a faculty member in the Management Department of the Wharton School at the University of Pennsylvania. He is a member of the Institute for Work and Employment Research at MIT, as well as a Research Fellow at the Wharton Financial Institutions Center, and at the Center for Human Resources at the Wharton School.
His research primarily focuses on the sociological aspects of work and employment. Castilla is particularly interested in studying how social and organizational processes influence key organizational and employment processes and outcomes over time. He tackles his research questions by examining different empirical settings with longitudinal datasets, both at the individual and company levels. His focus is on the recruitment, hiring, development, and job mobility of employees within and across organizations and locations, as well as on the impact of teamwork and social relations on performance and innovation. His work has been published in top academic journals and edited volumes, including Administrative Science Quarterly, Organization Science, American Journal of Sociology, and American Sociological Review. He has also written a book on the use of longitudinal methods in social science research (Elsevier/Academic Press).
Castilla has taught in various degree programs at MIT Sloan, the Wharton School, and a number of other international universities. His teaching interests include Strategic Human Resource Management, Strategies for People Analytics, Leading Effective Organizations, Talent Management, Career Management, and Organizational Behavior. In addition to teaching full-time MBA and executive courses, he has taught several PhD-level courses.
Castilla, Emilio J. New York, NY: Columbia University Press, 2025.
Castilla, Emilio J. The European Business Review, May 17, 2025.
Castilla, Emilio J., and Hye Jin Rho. Management Science Vol. 69, No. 11 (2023): 6912-6939. Download Replication Files.
Ben A. Rissing and Emilio J. Castilla. In Sage Research Methods: Business, 2023.
Castilla, Emilio J. and Ethan J. Poskanzer. American Sociological Review Vol. 87, No. 5 (2022): 782–826.
Castilla, Emilio J. Organization Science Vol. 33, No. 6 (2022): 2364-2403.
“The Meritocracy Paradox” offers frameworks to help organizations make people-management decisions based on data and evidence rather than intuition.
A new book by MIT Sloan professor Emilio J. Castilla offers managers and leaders a practical, data-driven roadmap for building fairer and more effective talent management systems.
While probationary periods give workers and their employers a chance to assess fit, they also present some risks to workers, said professor Emilio J. Castilla. If an employer uses the trial period as a tool to maintain a temporary workforce, for example, rather than hire for the long term, that would be an "unintended consequence of a practice that initially was meant to reduce risks for both the employer and the employee," Castilla said.
Professor Emilio J. Castilla said: "True meritocracy isn't about adopting trendy best practices, but about doing the patient, and often uncomfortable, work of ensuring that every employee has a genuine and equal opportunity to succeed."
Professor Emilio Castilla wrote: "Pressure to act often leads companies to implement generic solutions without first diagnosing the organization's specific challenges or needs. The 'best practice' approach falls short because it fails to account for the specific context of an organization. I propose a more effective approach — a data-driven talent management strategy that actively addresses bias and inequity while ensuring efficient, fair, and meritocratic decision-making."
Two MIT Sloan academics have been named to the shortlist for the Thinkers50 Awards. Professor Emilio Castilla has been nominated for the Talent Award and principal research scientist Andrew McAfee for the Future Readiness Award.
People analytics is a data-driven approach to improving people-related decisions for the purpose of advancing both individual and organizational success. This new program explores a number of strategies used to attract and retain top talent and illustrates how these strategies are being designed and used at cutting-edge companies.
