Do companies need to use Data science in hiring new employees? Like most organizations activities, Big data changes the requirement process. Scientific analysis era touched the human resources sector too. Effective data science techniques can provide better quality, higher accuracy, cost-effective outcome for HR.
Let’s see how data science techniques can help at different fields and work phases of HR.
Internet technologies and increasing mobility of people make hiring process very competitive. Company spend 23.7 days in average to hire a new employee, while the best candidates stay on the market for only ten days. On the other hand, many companies avoid hiring from popular job’s websites. LinkedIn or Indeed posting may bring in thousands of resumes from candidates. Most of them are not qualified enough, especially for technical positions. So, HR teams have to solve a few problems on hiring phase: to make the hiring process faster, to attract more talents, and to analyze more resumes.
The predictive analytics technologies and natural language processing help HR teams to filter through thousands of resumes, to focus on the best channels for hiring and create a base of the most promising candidates on a market. The advantage of using data science in hiring is in decreasing of hiring time and increasing quality of candidates for the company. Predictive hiring in the recruitment process is successfully used by big companies. For example, the implementation of predictive hiring tool in Wells Fargo increased retention rates for teller by 15%.
Engagement and Performance
Predictive analysis can increase employee engagement and productivity. Even if the company gained good employee, it is not enough. The candidate should be introduced to their new duties and involved in professional training programs. A lot of companies realized that the cost of training is higher than the profit they receive from it.
Data science can examine employees learning and help to modify courses order in order to make them more productive. Using of the Big data analysis, companies can also detect potential mistakes and flaws in work. For example, JetBlue wanted to improve on training attrition with new members joining the team. JetBlue used data science methods in their analysis. As a result, training failure-based attrition fell by 75%, and overall training attrition fell by 25%.
One of the biggest problems of companies is retention. In general, companies invest money and resources to hire new people, then they invest 1-3 months to train new employees. This investment will be a loss if a person decided to leave in the first six months. Your employees can be dissatisfied because of different reasons: low salary, poor communication with superiors, and many other reasons. Employers can never be sure that all members of the “strong team” won’t leave the company soon. One third of employees at companies with 100 plus employees are currently looking for jobs. Predictive analysis could find hidden reasons of employee’s dissatisfaction and allows to HR management to find solutions before the problems occur. Machine learning techniques scan employees’ attributes to detect increasing or decreasing of resignations.
Besides retention, there is also employee turnover. It refers to the percentage of workers who leave an organization and are replaced by new employees. There are plenty of factors for turnover in a particular organization. Some of them could be solved easily, but some of them not. In the second case, predictive analytics uses historical data to predict how many and when employees will leave the company. Thus, the HR team can start looking for new candidates before the retention of old ones.
Finally, it could be mentioned that big data analytics became the new force for contemporary HR management. New data science approaches decrease time and resources on hiring better workers, increase employee engagement, their productivity, and retention rates. The human factor in HR work is very important but the implementation of machine learning techniques in HR teams increases their productivity and eliminates routine.