Using predictive analytics in human resource management (HRM) empowers human resource managers to recruit highly skilled candidates and even recognize disengaged employees, ensuring that the balance of the workforce is never disturbed.
In the movie 21, a group of young college students is trained by Kevin Spacey to become card-counting experts. Depending on the number of cards that are already drawn, the cards at the table, and the cards that are remaining to be drawn, the group is able to predict whether to ‘hit’ or ‘stand’ the next card in the game of Blackjack. The group goes on to get millions in winnings from Las Vegas casinos. To put it in simpler terms, they used historical data (cards already out on the table) for predictive analytics to determine the next cards that might be drawn from the pack and earned millions. Predictive analytics, in general, can help businesses make better decisions by providing a highly accurate future scenario based on historical data. It can help improve work efficiency, help with risk management, detect fraud, and help organizations stay ahead of their competitors. Similarly, predictive analytics in HRM can help human resource managers to predict which candidate to hire, which employee is likely to leave, and find suitable replacements beforehand to ensure that the organization has the most talented, highly suited, and highly productive workforce at hand. This ensures that your organization has the most output it is capable of, thus, guaranteeing high winnings (financial earnings) always.
Predictive analytics in HRM refers to the technology used for HR purposes, which uses statistics and learns from existing data in order to predict future outcomes. It serves as a decision-making tool. In recruiting predictive analytics are used to analyze data from resumes, job descriptions, ATS, and HRIS systems to predict various talent management outcomes.
Predictive analytics makes use of historical data such as resume, job skills, likes and dislikes, and current factors such as employee engagement, and employee productivity at the workplace to predict future outcomes of the candidate or employee at the organization. It helps determine whether the candidate is the right fit for the organization and helps recognize and stop the most skilled employees from leaving the organization.
The use of predictive analytics in HRM can streamline every operation involved in hiring and retaining staff at the organization. It can help choose the right talent depending on the organization’s culture, ethics, and work environment and provide them with a conducive environment to retain them for an extended period. Predictive analytics can be utilized for the following purposes:
It so often happens that the organization hires candidates with the right educational qualification only to realize later that the candidates lack the skills required for the job. Thus, a lot of time and resources are wasted in training the employee to get acquainted with the right set of skills. This creates a skills gap that is unfavorable and inefficient to the organization.
Leveraging predictive analytics in HRM can help close the skills gap. With the help of historical data, a predictive analytics algorithm can help determine the skills lacking in the organization. It can help business leaders decide whether to recruit new talent or upskill the existing ones. Business leaders can accurately determine the employees that need the most attention in improving their skill set and also identify areas that require improvement. The employee’s education, previous work experience, the projects the candidate has worked on, the skill set required for the projects, and the success of the projects need to be analyzed to get an overall understanding of skills possessed or lacked by candidates. Along with predictive analytics, organizations can also leverage technologies such as blockchain to bridge the skills gap at their organization.
Human resource managers always look to recruit candidates that have the right educational background and the right skill sets. However, one aspect they mostly overlook is whether the candidate can fit in the workplace culture. For that, HR managers also need to consider the candidate’s age group, behavior, or even social media activity to understand their likes and dislikes. This can help decide whether the candidate will be able to fit in the company’s jigsaw. Candidates usually have low productivity and eventually leave if they don’t find themselves fit in an organization. This increases the task of HR managers to find replacements every few months and also disbalances the team he is working with. Thus, HR managers should adhere to the above-mentioned procedures such as conducting advanced background checks and having personality evaluation to find the right candidates in the first instance. For example, a study revealed that an individual’s social media handle such as Facebook profile, can help predict their personality and their future work performance, if hired and thus reduce employee attrition.
Once the right candidate is selected, organizations should ensure that the candidate works with the highest productivity. Predictive analytics can be utilized to maximize the role of the candidate at the organization. Data can be analyzed to measure employee’s performance by monitoring tasks, especially the ones that were difficult for the employee to handle. This can help improve the areas in which the employee faces shortcomings. Training and counseling sessions can then be organized that can help improve the performance of the employee and, ultimately, their productivity.
Employee retention is a big challenge faced by many organizations. Employees tend to leave the organization if they don’t find growth opportunities at the organization or have issues with the salary package. Predictive analytics can help analyze factors such as salary, promotions, and employee behavior and satisfaction levels to determine if the employee is disengaged. If an employee is disinterested in his work and has low productivity, it is an early sign that the employee might quit. Similarly, factors such as work environment, relationships with colleagues and higher authorities, too, can help predict if an employee is likely to quit. The appropriate measures can thus be taken to identify such employees and improve their experience at the organization. For example, according to a finding using predictive analytics by Google, new salespersons are likely to quit their job who don’t get a promotion within four years. Thus, with such data at hand, organizations can take better measures to retain employees.
Organizations should ensure that they retain their top employees for continued growth and success. But how can they identify their top performers? Human resources managers need to analyze the contribution of employees to the organization during their tenure. They should evaluate things employees excel at, the instances of low performances, and the business value they have brought to the organization. Once the top performers are identified, human resources managers should look for potential reasons that might compel these star performers to leave. Factors such as pay packages in other organizations for similar job profiles, additional incentives offered, and growth opportunities at other organizations need to be evaluated. Thus, human resources managers can come up with a contingency plan that might prevent the top employees from leaving the workplace. For example, HP’s flight risk score helps them to foretell which employees might leave the organization, and therefore, the human resources team can focus on retaining such employees. The Flight Risk program also has the potential to save around USD 300 million with regard to staff replacement and other losses.
Using predictive analytics in HRM will help organizations hire the best-suited talent. This will lead to a good work environment, high team bonding, and ultimately result in high productivity of employees. This will not only help in the personal growth of employees but will contribute largely to the growth of your organization as well. A number of leading businesses such as Nielsen have already benefited from using predictive analytics in HRM. Thus, other businesses too should opt for it at their workplace if they want to be successful and grow tremendously.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.