Modern Hire, the leading enterprise hiring platform for video interviewing and pre-hire assessments, announced the release of its Talent Analytics Maturity Model to help organizations revolutionize their hiring process through artificial intelligence and data analytics.
The free guide offers organizations a quick self-evaluation survey to comprehensively understand their talent analytics readiness, and a six-step model first introduced in Modern Hire’s book Decoding Talent: How AI and Big Data Can Solve Your Company’s People Puzzle, to get the maximum value from their talent data for more efficient, effective and ethical hiring. The Talent Analytics Maturity Model is the first framework of its kind that fundamentally integrates AI, empowering enterprises to grasp their level of talent analytics maturity and guide them on next steps for moving forward.
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“AI can be a confusing and complex technology, but it’s also providing amazing advances in talent acquisition, helping us to understand candidate and employee data in a significantly more cohesive and powerful way,” said Eric Sydell, Ph.D. and EVP Innovation at Modern Hire. “The Talent Analytics Maturity Model offers a strategic approach to talent management grounded in data and designed to guide HR teams toward more effective use of intelligent hiring technologies to better identify and quickly hire best fit candidates. As witnessed through our client work, leveraging talent analytics saves companies millions annually in new hire retention, and boosts business productivity and performance, while also helping to ensure fair and diverse hiring.”
Organizations are investing in HR technologies today to make more effective talent decisions, yet many still struggle with how to best capitalize on the value of their data. According to Aptitude Research, 78% of HR and talent acquisition leaders say hiring performance would improve if they had a more strategic approach to talent analytics. Recognizing this, Modern Hire developed the Maturity Model to provide organizations with a jump start on finding their way forward to more strategic and successful hiring.
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The six-step model includes:
- Audit – Understanding the different pre-hire and post-hire data sources available in an organization and standardizing the data sets (if needed) before connecting and analyzing them.
- Capture – Collecting the data needed to get started, including redefining hiring processes to fill gaps, and adding assessments, new-hire performance, and turnover data sets if they aren’t already there.
- Connect – Creating and linking relevant pre-hire and post-hire data through the right technologies. HR leaders often encounter barriers in this step because the post-hire data they need is not housed in HR and is not easily accessed.
- Analyze – Leveraging data analytics tools, find associations between variables in the two data sets. Success in finding meaningful relationships is broader, faster, and much more likely when using automated, AI-driven analytics.
- Build – Constructing and testing models to better understand which pre-hire candidate data predicts post-hire job performance and retention. AI-powered model-building far outpaces what humans can achieve on their own, which is why the sophistication of talent analytics has advanced so rapidly in recent years.
- Refine – Final assessment of talent analytics model to determine whether the associations identified with the power of AI make practical sense.
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