Talent-related data presents opportunities for HR departments to build high-performing workforces. Thanks to growing technology, it is possible for HR teams to effectively capture, track and measure data allowing them to leverage metrics. Using easily accessed analytics tools you can discover predictive insights to improve talent acquisition, employee performance and productivity, onboarding procedures and career development. Here we look at the benefits of predictive analytics for your HR team.
Recruitment is more competitive than ever thanks to historically low unemployment rates. This makes it difficult to find qualified talent that will fill roles effectively. However, you can use pre-hire assessment data to pre-qualify prospects to find the best candidates to suit your needs while fitting in with your culture. This helps decrease the risk of bad hires. Whether you want to apply routine criteria when screening applicants or are focused on specifics to help screen for the best fit, you can cover all the important qualifications using predictive analytics.
HR Predictive Analytics Examples of Pre-Qualifying Candidates: Google uses computer-generated, fully automated questions during their hiring process. The questions are designed to easily weed out unsuitable candidates using predictive analytics to compose their questionnaire. As well, according to a Cornerstone study, data from involuntarily terminated employees helped reveal characteristics of toxic people to avoid hiring employees who negatively impact their co-workers.
Perfecting the hiring process will help attract and retain top talent. This is because the best way to reduce turnover is to hire the right people for the job and company culture in the first place. You can use predictive analytics to reduce turnover using historical data to identify reasons you tend to lose your best hires. This requires a consistent exit strategy using an exit interview to collect crucial data that helps you avoid attrition. You can combine reasons for leaving with job roles and titles, look for patterns in employee performance scores in those who tend to leave and pinpoint the contributing factors that lead to flight risks for high performers.
HR Predictive Analytics Examples of Improved Retention: Google uses predictive analytics to identify flight risks based on factors such as salespeople not being promoted within four years. This allows them to track tenure and look for opportunities for their top performers before they leave.
HR also needs to focus on improving the productivity and efficiency of your workforce. High-performing employees can be nurtured using predictive analytics to measure employee progress and identify developmental needs. As a result, you can focus on upskilling to ensure employees succeed by providing the specific development required to make them more productive. You can also use development to identify those who have the potential to improve not just skills, but also their level of responsibility to fill leadership roles.
HR Predictive Analytics Examples of Improved Productivity
Best Buy, for instance, uses predictive analytics to measure employee engagement’s impact on store performance using data collected from quarterly surveys.
You face fewer recruitment challenges when you improve employee retention. The best way to reduce employee turnover is to ensure your employees are engaged. Improving employee satisfaction is easier when you can track and measure engagement. Predictive analytics allows you to track key employee engagement metrics from morale to motivational triggers and from career aspirations to response to company culture.
You can identify weaknesses in your corporate fabric to improve employee experience whether it is career nurturing, training, communication, wellness programs or commitment to promoting from within.
HR Predictive Analytics Examples of Engagement
Wikipedia, for example, uses metrics to determine how long an editor is expected to contribute so they can work on re-engaging them to avoid turnover.
As briefly mentioned above you can develop a more productive workforce by focusing more on employee development. Most organizations face skills gaps, often related to fast growth in digital advancements. A focus on upskilling and development programs becomes more strategic using predictive analytics in human resources to determine where development is needed as technology changes, automation is introduced, and job roles become more customized.
You can predict potential skills gaps based on operational planning, so you remain ahead of technological advancement and maximize employee performance. Talent assessments also identify skills gaps to help develop training programs based on the most critical skills your employees need to succeed.
HR departments can not only capture data but use it to predict potential outcomes to avoid common HR challenges. You can now combine both quantifiable and unquantifiable data to help change your recruitment process and improve retention and development to optimize performance and productivity.
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