HiringBranch Research Challenges Single-Skill Scoring in Frontline Hiring

New research from HiringBranch is questioning a common practice in pre-employment assessments: scoring soft skills like empathy and active listening individually. The company's findings, discussed on the "You Should Know" podcast, indicate that a combined approach yields more accurate hiring predictions for frontline roles.

Assaf Bar-Moshe, Chief of Research and Development at HiringBranch, explained that evaluating acknowledgment, reassurance, empathy, and active listening together produces stronger correlations with on-the-job performance than scoring each skill in isolation. The study, which used voice and writing assessments, found that single-skill scoring only moderately correlates with human annotators, while a combined proprietary model performs significantly better.

Bar-Moshe emphasized the practical importance of this approach. "If a candidate can express empathy, but is unable to solve the issue correctly or to comprehend the issue correctly or to reassure the customer, then this empathy is nice, but it's actually useless," he said. This perspective is critical for industries like retail, customer service, and sales, where employees must handle live interactions effectively.

The research is grounded in a linguistic analysis method, which Bar-Moshe describes as a "sociopragmatic analysis of the words that the candidate is actually saying." HiringBranch's team of IO psychologists and linguists builds machine learning models based on years of textual data to predict these skills, then validates them against performance months after hiring. Calibration varies by client, industry, and region, with differences in markets like Vancouver, Toronto, and Montreal affecting scoring weights for the same role.

The podcast also touched on a retail scenario involving a mispriced item, illustrating how soft skills like diplomacy are crucial in customer interactions. Bar-Moshe noted that job descriptions are translated into conversation flows and scenario-based assessments tailored to specific roles and regions.

Looking ahead, HiringBranch is developing a self-serve capability that would allow hiring managers to build assessments from a library of conversation flows and skills, potentially reducing reliance on weak or generic job descriptions. The full study will be available under the AI research tab on the HiringBranch website.

This research has significant implications for employers, as it suggests that a holistic evaluation of soft skills could lead to better hiring decisions and improved customer experiences. By focusing on how these skills work together, companies can identify candidates who are not only empathetic but also capable of solving problems and reassuring customers effectively.

As frontline roles increasingly define brand reputation, the ability to assess candidates accurately becomes paramount. HiringBranch's findings offer a data-driven path forward, moving beyond conventional single-skill scoring to a more integrated understanding of what makes a successful hire.