The use of advanced analytics and data mining has permeated almost every department and industry across the world. Teams are increasingly finding uses for predictive analytics and business intelligence. The human resources industry is no exception. From the beginning of the recruitment process through new employee onboarding, hiring teams can take advantage of data mining for smarter decision making. Here are just a few ways advanced analytics play a role in HR teams.

Hiring managers can better schedule their interviewees.

Interviews can take up several hours of an HR manager’s day. Even if department heads and senior leaders want to meet with candidates on their own, human resource teams meet with prospects for pre-screening and basic onboarding questions. The interview process itself can take several hours, especially for candidates in advanced positions.

Advanced analytics systems can help people save time with strategic scheduling. For example, an interview scheduling tool can give candidates windows to sign up for. The HR team can then schedule interviews around the candidate’s availability that works for them. A hiring manager can save a few hours each week just with strategic scheduling.

Predictive analytics systems can identify turnover risks.

High turnover rates can have a significant impact on a company’s bottom line. Expert analysts estimate that turnover costs 33% of an employee’s annual salary. If you lose an employee that makes $75,000/year, then you are likely going to spend close to $25,000 in lost productivity, recruitment, hiring, and onboarding. In large organizations, these costs add up when hundreds of companies change roles each year.

Advanced analytics techniques can reduce turnover by identifying employees that are likely to leave or highlighting patterns in employee loss. For example, an employee that has a lower quarterly performance review than normal and a higher rate of absenteeism is more likely to quit. If five employees under one manager quit within a six month period, it may be time to intervene. Business intelligence can find these anomalies and help HR teams intervene.

Big data can highlight the most qualified candidates.

HR teams have to sort through dozens of applications in order to find qualified candidates. Whether they work through this process in-house or work with recruiters, hiring teams are often left filtering through unqualified resumes and hoping they find someone with the right candidate experience. In fact, some employers say that 75% of job applicants are unqualified for the role and only 2% of candidates even get an interview.

Big data systems can help with this process. Advanced analytics tools can sort through applications and identify resumes with target keywords and valuable phrases. This limits the amount of searching for hiring teams so they can focus on the interview process.

HR teams can identify training gaps.

One additional way human resource teams can use advanced analytics tools is to determine which employees need additional training and which departments could benefit from educational resources. Training makes employees more effective in their roles, increasing productivity, and reducing the number of errors on average. Training can also prepare lower-level workers for advancement — like a high-performing team member taking a management class before they are given a promotion.

Big data tools identify trends in employee work to catch problems and find opportunities. The use of data also makes this process less personal, so employees won’t feel singled out if they need additional training or learning resources. These tools can also track the before-and-after effects of training to show companies that their educational resources are effective.

Big data can’t solve all of your human resource problems, but the use of advanced analytics can at least alert your team to issues so they can better identify solutions and keep employees engaged.