Mismatches Between Talent Identification and Development Models: Why Their Distinct Natures Must Be Nurtured

The identification and development of talent are top priorities across education, sports, business, and the arts. A major challenge lies in developing and applying appropriate models in both science and practice. Talent-identification models should center around predicting future excellence, whereas talent-development models should focus on how skills, resources, and their interactions change over time on the path to excellence. After providing an overview of the literature on talent-identification and talent-development models, I will argue that these models are often misapplied across domains: Talent-identification models are frequently used for talent development, and vice versa, which hampers progress in both scientific research and practical application. To address this issue, I propose a dual-path approach to nurture the distinct natures of talent-identification and talent-development models. For talent development, longitudinal processes involving relevant variables (e.g., psychosocial, cognitive, and physical) should be studied and evaluated at the individual level. For talent identification, predictive models incorporating relevant variables need to be tested, and their optimal and consistent application in real-world settings should be evaluated. This dual-path approach offers opportunities to advance psychological science and practice in identifying and developing talent across diverse domains of achievement.