Predictive Talent Analytics Lives up to the Hype

 In Interviewing, Recruiting

Using predictive analytics early in the recruitment process to identify performance and tenure potential has significant implications for the talent acquisition industry. The recent Bloomberg Business piece, citing research conducted by the National Bureau of Economic Research (NEBR) has lent some independent validation regarding the effectiveness of this software, making it easier for talent acquisition professionals to embrace these applications. They significantly raise the recruiting team’s organizational value by facilitating better hiring decisions and, consequently, improving the bottom-line performance of the company.

As the leading provider of contact center predictive talent analytics, HireIQ conducted a survey of talent acquisition and recruiting professionals to discover how they used predictive analytics in the hiring process. Specifically, we sought to understand how these applications are used to inform the hiring decision and whether they have a positive impact on key performance indicators such as employee tenure, first call resolution, and customer satisfaction.

We found that over 90% of respondents always or almost always use predictive talent analytics results when making their hiring decisions. This is a strong indicator of the value it brings to the selection of high-performance employees, the confidence that users have in its results, and how deeply instantiated it is in the process.

Further analyzing post-hire performance data shows that heeding its recommendations yielded significant gains in key contact center operational performance. Companies that hired candidates who were predicted to be excellent performers enjoyed a 60% improvement in critical 90-day retention; 56% increase in first call resolution attainment; and a 37% lift in customer satisfaction. This is a substantial endorsement of the real world benefit brought by using predictive analytics in the hiring process.

In addition to showing a causal link between candidate selection recommendations and observed performance on the job, the survey uncovered an interesting relationship between recruiting and its stakeholders. Of those who responded, 90% indicated that “quality-of-hire” is a key recruiting metric, yet only 30% said that stakeholder satisfaction was important. This suggests a very process-centric view of QOH that ignores the long-term productivity potential or quality of the new hire.

Our research corroborates that of the NEBR study in that predictive analytics helps inform the recruiting team regarding which candidates exhibit the traits of long-tenured, high-performance employees.  As such, it is a powerful tool available to recruiters to help them provide superior service to their stakeholders.

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