Harnessing Predictive Analytics for Workforce Optimization in a Transhuman Age

Abstract

Workforce management is another area where predictive analytics has proved to be a key technology as it changes the way organizations make decisions concerning their employees. This study examines the various ways in which predictive analytics is used in workforce management to increase employee loyalty, decrease employee turnover, increase employee performance, select the right candidates, and increase employee involvement. Thus, through using historical information and statistical models, there is a perfect vision of the trends and behavior patterns in the workforce, allowing the organization to act preventively and mindfully. Using AI in the collection and analysis of data produces real-time data and recommendations. Furthermore, predictive analytics can help to ham more diverse and an inclusive workforce by uncovering the issues in terms of gender, race, etc. regarding recruitment, turnover, and advancement. Overall, predictive analytics delivers realistic changes in the area of workforce management, as well as in employment effectiveness, employees' turnover, and levels of motivation. By adopting this strategy organizations have a chance to identify and plan for workforce issues before they become real problems and, therefore, create a motivated, productive, and long lasting work force.