The nature of software engineering is ever-changing and needs smart, intelligent, and innovation-enhancing solutions for talent management. In this paper, we describe our statistically validated dynamic Talented Innovative ecosystem (DTIE) that aims to improve innovation scaling in software engineering through AI-enabled analytics, data-driven recruitment, and continuous learning systems. The DTIE deploys real-time data collection, proficiency gap assessments, and predictive analytics to align and deploy the most suitable workforce to the most appropriate task. The implementation of DTIE caused statistically significant changes in the company employee productivity, innovation project success rate, and employee attrition rates (+33.8, +46.1, and -20.3, respectively). In addition, it reduced the bias index and critical fill time by 72% and 35.6% respectively which is a direct indication of the DTIE validity and operational effectiveness. There is a robust correlation (r=0.87) that shows the changes were a function of AI-driven talent management, directly impacting innovation outcomes. The DTIE talent management framework is statistically validated and provides a growing organization with the ability to shape an innovative workforce, improve productivity, and ensure continual viability in an environment of high volatility in software engineering.
Montero Guerra JM, Danvila-del-Valle I, Méndez-Suárez M. The impact of digital transformation on talent management. Technological Forecasting and Social Change. 2023;188:122291.
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