Big data in human resources (HR) is becoming more widely used for recruiting, hiring and retaining the best employees. Here are three reasons why more companies are adopting predictive analytics for improving the bottom line.
Big data helps uncover which candidates are best suited for open positions. Part of the data-mining process may include gathering information from resumes and social media profiles for more clearly identifying which potential hires may be more productive and add diversity to a workplace. Hiring managers may then narrow down their candidate pool and decide which areas of evaluation they should focus on during interviews. By implementing this strategy, the hiring process moves more quickly and the right people are hired more often.
For example, a bank in Asia previously recruited the top graduates from highly regarded universities for filling its 8,000 roles spread over 30 branches. After the bank underwent an organizational restructuring, the institution began data mining information covering 30 points in the categories of employee performance, professional history, demographics, tenure, and branch information from its current resources. The bank started using data analytics for identifying current employees most likely to excel in their positions, creating new roles within the organization and gaining additional insight into what motivates workers’ performance.
By using predictive analytics, the bank uncovered common traits among high and low performers and created profiles for workers with a stronger possibility of excelling in a specific role. The information also showed that how branches and teams are structured affects the institution’s financial growth. In addition, big data revealed that specific roles had the greatest influence on the bank’s success.
As a result, new organizational structures were created around specific teams and groups of workers. Because the bank began using data analytics for recruiting and measuring performance, branch productivity increased by 26%, the conversion rate of new recruits rose by 80% and net income went up by 14%.
Predictive analytics reduces the amount of bias that goes into making decisions affecting a company’s performance. For example, many hiring managers bring aboard candidates possessing characteristics similar to their top workers.