HR departments used to focus on achieving quantifiable outcomes such as the number of training or new hires during a specific period. However, decades of extensive research into HR operations have revealed that intangible assets like employees’ knowledge, experience, cognitive abilities, engagement, and loyalty constitute the core of the company’s business value.
By continuously reiterating advanced statistical models, the world’s brightest minds found a way to measure human capital. In other words, it became possible to measure, for example, employee engagement and understand how it relates to fluctuations in performance. This, in turn, allowed HR departments to see how certain HR variables impact business outcomes.
Besides analyzing past performance, it is now possible to make intelligent predictions regarding HR strategies. With the help of predictive analytics in human resources, companies can make more informed decisions about their HR strategies and investments that will help them realize the most from their workforces. In this article, we will discuss what predictive analytics in HR means and outline the top benefits of implementation.
What is predictive analytics in HR?
Predictive analytics is a form of data analysis that uses statistics and machine learning to predict future trends, behaviors, and outcomes. Predictive analytics allows HR professionals to make sense of growing amounts of employees and market data to identify potential challenges associated with employee recruitment, retention, performance management, and other key areas of HR management. Importantly, predictive analytics-based tools are much less biased about a candidate’s competencies and make decisions solely on quantifiable information.
Top 5 benefits of predictive analytics in HR
Predictive analytics can provide HR professionals with powerful insights into their organization’s workforce data. Let’s discuss the top 5 benefits of predictive analytics in HR:
Improved recruiting
Predictive analytics is revolutionizing the way HR departments recruit and manage talent. By leveraging data and powerful algorithms, predictive analytics can help identify specific skills and traits essential for particular roles and uncover hidden talent in large pools of applicants. For example, by analyzing prospects’ social media data, predictive analytics systems can detect if a candidate has critical social traits to fit into the company’s culture. This means organizations can more accurately match candidate qualifications to job requirements and find culture-fit candidates faster.
Improved employee retention and engagement
Predictive analytics can help HR teams better understand and anticipate employee behaviors that could lead to turnover. By analyzing historical data, predictive analytics can identify patterns in how employees interact with their colleagues, engage with the work, and transition through job roles. This helps HR departments gain insights into which factors are most influential in driving retention and engagement.
With this data, managers can understand which areas of the employee experience need improvement and develop targeted interventions to foster greater engagement and loyalty. For example, predictive analytics can help HR professionals to understand what drives engagement in a particular employee or groups of employees to reimagine the reward system.
Improved talent management
Given that high leadership potential is defined by intangible factors rather than flawless role performance, finding future leaders within the current workforce is a complicated task. Machine learning-based techniques can determine certain behavior linked to leadership potential, allowing HR departments to identify the employees with the most significant value for the company. Additionally, predictive analytics can help organizations better recognize employees for their hard work and accomplishments, creating an environment where employees feel valued and appreciated.
Improved skill development
Predictive analytics has the potential to boost skill development by providing HR departments with detailed insights into the performance of their employees over time. With this information, HR teams can better understand which skills individuals need to develop in order to excel in their particular roles and identify if additional training or coaching may be beneficial. This makes upskilling targeted and contextual, maximizing the ROI of such initiatives.
Enhanced demand forecasting
Predictive analytics can be a powerful tool for talent demand forecasting, enabling HR professionals to make more informed decisions when planning their hiring pipeline. ML-based models can analyze numerous employee characteristics, including age, performance over time, time spent in the role, and project success rate, to detect employees most likely planning to find a new job. Besides, predictive analytics can analyze external factors like economic and technological trends to anticipate what skills will be in high demand in the coming years, allowing HR departments to be prepared and plan accordingly.
Predictive analytics has a wide range of applications in the HR domain, from helping organizations find and retain top talent to enhancing skill development and forecasting demand for new roles. By leveraging data-driven insights, HR departments can better understand employees and develop more effective strategies to improve their operations. In the long run, these initiatives will contribute to the success of organizations by creating robust, engaged workforces and helping them stay ahead of the competition.
