Current Human Capital Management: Predictive Analysis

The business outlook has shifted to a global aspect, and competition has gotten more aggressive. As a result, quality and precision technology has become a key feature of business strategy. Using predictive analytics, the HR department can measure employees’ attributes and performance to gain a competitive edge over rivals by making better strategic decisions on the people’s side. According to Mishra & Momin (2015), with predictive analysis, organizations can understand what is going on, frame the action to take, track the performance of the action and predict the outcome. Companies are using predictive analysis to design recruitment plans by analyzing the right candidate to reduce unnecessary costs. Predictive analysis plays a crucial role in succession planning, performance management, and training and development.

As a manager, I could use predictive analysis to create strategic global competitiveness by relying on proven and data-driven predictive models in recruitment and talent management in general. It could help forecast the impact of people policies on employee performance while getting insight to prevent employee turnover. It could help me make better decisions based on past data, manage risk effectively, and stay ahead of my rivals. Hiring the best-suited candidates could raise productivity hence contributing to the overall growth and competitiveness of my organization.

For example, Hewlett-Packard (HP) has over 300,000 employees and has experienced massive employee turnover in some divisions over the years. High turnover leads to huge recruitment costs and loss of revenue. In 2011, HP embarked on using predictive models called the “Flight Risk” score to predict the possibility of leaving for each of its employees (Yuan, 2018). The model generated significant results, as the company identified likely causes of turnover, including lack of pay rise after promotions. Consequently, the managers acquired training to decipher these results and develop strategies to retain their staff. Ultimately, the model acted as a warning system and enabled the managers to intervene early, saving the company millions.

References

Mishra, K., & Momin, W. Y. (2015). HR Analytics as a Strategic Workforce Planning. International Journal of Applied Research1(4), 258-260.

Yuan, J. (2018). HR predictive data analytics in the era of big data. Proceedings of the 2018 International Conference on Economics, Business, Management and Corporate Social Responsibility (EBMCSR 2018)https://doi.org/10.2991/ebmcsr-18.2018.75