Predictive HR analytics is a tech tool that HR uses to analyze past and present data to forecast future outcomes. Predictive HR analytics digitally digs through data to extract, dissect, and categorize information and then identify patterns, irregularities, and correlations. These techniques then try to create a formula, or algorithm, that best mimics these historical outcomes. This algorithm then uses current data to predict outcomes in the future (AIHR, 2022).
One area HR is using predictive analytics is in the talent acquisition space. Analytics can be utilized to review resumes, job descriptions etc. and help to narrow in on desired skill sets. By utilizing analytics upfront, HR Practitioners can tailor their recruitment strategy to attract and engage a candidate that would be a great culture add and fit for the type of position they are recruiting for.
However, only a few organizations are capable of producing predictive models for HR. According to Deloitte’s 2018 People Analytics Maturity Model, only 17% of organizations worldwide had accessible and utilized HR data. This is up from 8% in 2015, and 4% in 2014. Of this 17% in 2018, only 2% qualified as having business-integrated data, meaning they use real-time, advanced AI-aided tools to collect, integrate, and analyze data. The other 15% is able to do predictive analytics on an ad-hoc basis (AIHR).
The results of applying predictive people analytics can be astonishing. HR departments can potentially save (or earn) their company millions of dollars. Additionally, HR can help their managers and executives make better decisions by applying predictive analytics and using the right HR metrics (AIHR).
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