AI in Hiring, Use Case #5: Objectively Measure Quality of Hire for the First Time—and Continually Improve It Through a Virtuous Feedback Loop

February 21, 2024

min read


Bhargav Brahmbhatt

Hiring candidates who are culturally aligned to the company and possess the attitudes and behaviors essential for team harmony (and whose onboarding has been tailored to their personal strengths and gaps) leads to stronger engagement and on-the-job performance.

CEOs and boards of directors want to know that the business is maintaining employee quality for all the time and money it spends on hiring. For decades, talent acquisition leaders have been under pressure to report on a fundamentally-elusive KPI: there’s been no way to systematically quantify quality of hire. Without a representative metric to convey whether recruiting is bringing in great hires, C-levels and boards remain uncertain—and even suspicious—of talent acquisition’s business impact.

AI not only augments data that’s already in organizations’ ATS and HRIS with its own assessment that’s more consistent and accurate than interview feedback, it also measures employee outcomes more holistically and much earlier than a first-year performance review does. That’s because AI continually connects hiring data to post-hire outcome data. By the end of year one, the AI almost wholly understands, has conformed to, and is personalized to your organizational culture and its most qualified, best-fit candidates.

On-the-job performance of new hires provides unique insights back to the team about what successful hiring looks like, and delivers feedback to the Predictive Talent Model for recalibrating and fine-tuning future interviews and assessments. In other words, hiring outcomes are translated into actionable recommendations on what qualities to search for—and who to hire—when the next role opens. 

With AI, recruiting and hiring teams have access to a learning loop that continuously improves quality-of-hire. For the first time, talent leaders can:

  • Be confident when reporting on quality-of-hire (as a quantifiable OKR) to C-levels and boards of directors, or in QBRs
  • Provide specific, measured insights into each department’s quality-of-hire and what made quality lower in some teams and higher in others—and relay those insights back to teams to bring in more best-fit hires
  • Know exactly where to focus their quality interventions, and monitor those interventions over time
  • Raise the value and visibility of talent acquisition by demonstrating the business impact of investing in good recruiting practices

AI-powered outcomes:

  • Udemy increased first year retention by 20%
  • Snapdocs improved quality-of-hire and increased employee lifetime value by 1.5-4x 
  • Verana Health set a people and culture OKR for quality-first hiring, measured by having a quality of hire score above an 8
“Searchlight helps us get more nuanced when it comes to defining the behavioral preferences we want for the next hire, customized by each hiring manager. By using Searchlight as a repository of success profiles, hiring managers and recruiters stay disciplined in hiring against their success criteria.” 
- Supreet Hundal, former Recruiting Operations Lead @ Zapier
“Searchlight is my best partner: a comprehensive solution that operationalizes quality of hire and reduces employee attrition.” 
- Ann Watson, SVP of People and Culture @ Verana Health

Get started today

Folks, that’s the last of our AI use cases series. We hope you enjoyed it and now have a firm grasp on the superpower that is AI-powered recruiting.

If you liked the series, you can get your copy of the eBook now so it’s all in one neat little spot. Don’t forget to book your Searchlight demo today.

Bhargav Brahmbhatt

Head of Marketing

Bhargav, our Head of Marketing, blends storytelling and customer empathy to drive business growth. Special flair for bringing new products to market.

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