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What’s the Science Behind Quality of Hire? – 5 Radical Insights from The Crosschq Q (Quality of Hire) Report


It’s been an exciting week at Crosschq—we released our inaugural Quality of Hire report from the Crosschq Data Labs!

The purpose of this report was to educate and enlighten our Human Resources and Talent Acquisition community about the Quality of Hire in order to show the connection data plays in the hiring process on business outcomes to drive actionable talent intelligence.

We even got props from Tim Sackett!

Here’s a little preview of the report itself…


Quality of  Hire  (QoH)  has historically been one of the most elusive business concepts for talent teams to standardize and measure.  Due to complex and fragmented data systems that are siloed and lack critical inputs, most companies struggle to reliably connect pre-hire candidate intelligence directly with quantifiable post-hire business outcomes.

Through Crosschq’s Talent Intelligence Cloud™ we have finally solved this problem. By connecting millions of data points from dozens of sources and 

enriching that data with advanced surveys, we enable companies to connect the dots and get on-demand, actionable insights that are based on hiring outcomes.

To date, we have touched over 24 million hiring decisions enabling our machine learning (ML) and artificial intelligence (AI) to get smarter and ultimately more predictive.

The result is the industry’s most powerful recruiting analytics platform that is based on business outcomes.

Once activated by an organization, the Crosschq platform not only helps optimize core recruiting programs but ultimately establishes a framework for making Quality of Hire a reliable North Star Metric (NSM) for the entire talent team.

In this report, our industry experts and data scientists have highlighted five radical insights from our outcome data. We cover a range of topics from sourcing, interviewing, and assessments and hope that our findings are thought-provoking. Our goal is to share our unique perspective to help inform the industry about the importance of establishing a modern outcome-based approach to recruiting analytics.

Meet the Data Labs Team Behind the Report

5 Radical Insights Discovered to Help Retain, Recruit, and Develop Talent

The report examines five radical insights from the data collected from over 24M+ hiring decisions, outlining the data collected and explaining each point.

Here is an abbreviated list of what you’ll see covered in the report:

Radical Insight #1: Internal Referrals Are Not the Best Source for New Hires

Radical Insight #2: There’s a Huge Difference Between Companies That Get Quality of Hire Right and Those Who Don’t

Radical Insight #3: Many Popular Pre-Hire Candidate Assessments Are Unreliable for Predicting Quality of Hire

Radical Insight #4: Most Interviewers Are Not Very Good At Identifying Top Talent

Radical Insight #5: Companies Who Aren’t Using Data, Are Flying Blind And Could Be Letting Their Highest Quality Employees Go

What's the Science Behind Quality of Hire? - 5 Radical Insights from The Crosschq Q (Quality of Hire) Report

Some points may shock you, others may prove what you’ve suspected but never had the data to back up your theory. This report will be one you’ll want to hold on to, pass around to your team, discuss (or even debate) with your industry friends, and most importantly guide you as you hire, retain, and develop your talent. Read the full report here.

The Crosschq Data Labs Team is also hosting a report briefing on Wednesday, November 9, at 11am PT | 2pm ET. Join the conversation and register here.