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Redefining Success: 6 Takeaways from New Research on Talent Analytics

Few organizations were left untouched by the pandemic-related events of 2020. While hiring demands and the hiring process that follows may constantly be in flux, TA practitioners have realized that they need a more robust understanding of employee performance and success drivers for a rock-solid process foundation.

In 2020, Madeline Laurano’s Aptitude Research collected and analyzed data on ways companies are redefining success, rethinking talent analytics, and preparing for the post-pandemic future of hiring. Modern Hire industrial-organizational psychology (I-O) scientists contributed to the recently released report, Redefining Success: Talent Analytics for the Future.

Aptitude Research found that one in three companies use performance data in their recruitment decisions. There is progress toward data-driven rather than reactionary decision-making in talent acquisition. However, 50% of organizations participating in this research indicated they do not trust their data sources. In other words, though companies can see their goals up ahead, the road to get there isn’t so straightforward.

We’ve identified six exciting data points that illuminate the widespread use of analytics in talent acquisition today and where TA leaders believe the use of talent analytics is headed. Here are key takeaways about analytics practices in 400 organizations with 1000+ employees across industries and the globe.

1. 64% see an increase in quality of hire when they use scientific data to inform recruitment decisions. When asked where they see improvements when they leverage science for decision-making, TA leaders identified quality of hire most often, followed by improving overall decision-making (50%) and improving diversity, equity, and inclusion (DEI) initiatives (46%). The business case for using talent analytics is there.

2. 55% of companies often start their process with resumes, and 45% usually begin with social media data. This is a red flag since it has been proven that this information is not necessarily an indicator of performance or quality of hire. Additionally, using resumes and social media profiles can open the door to biased candidate selection and job offer decisions.

3. 67% of TA and HR professionals do not share the correct data for decision-making with hiring managers. This could occur for many reasons, from not having access to data indicative of future performance or quality of hire to not recognizing the kind of data needed for informed decision-making. This negatively impacts the subsequent stages of hiring and, ultimately, hiring outcomes.

The type of data hiring teams should be using is predictive job performance data generated by validated pre-employment assessments like Modern Hire’s Virtual Job Tryout™. The Virtual Job Tryout integrates decades of comprehensive selection science with advanced artificial intelligence (AI) techniques to predict candidates’ future performance in a specific role. The Virtual Job Tryout goes beyond conventional cognitive and behavioral assessment with innovative exercises that simulate the job, providing evidence of how candidates are likely to perform. Candidates are evaluated based on abilities, not words on a resume or other data, leading to bias. Modern Hire provides the data-driven insights hiring teams need to improve new-hire performance, reduce turnover, and increase efficiency.

4. The use of artificial intelligence (AI) solutions to reduce bias in talent acquisition rose by 125% from 2019 to 2020. That’s the positive news, but there is still much to be accomplished: Only one in four (27%) organizations uses AI to minimize bias.

Elimination of bias is one of the most exciting uses of AI in hiring today. Modern Hire continues to research and deploy AI capabilities in our enterprise platform that minimize bias, such as

  • Use of natural language processing to anonymize text and other information that might identify group membership could influence candidate selection and job offer decisions.
  • Predicting group membership status so it can be programmatically controlled.
  • Developing and deploying algorithms that can detect and control bias in large databases.

Progressive recruiting teams are finding that using AI talent analytics tools can be one of the most effective practices for improving diversity in the workforce.

5. Data transparency builds trust. According to the report, about 8 in 10 TA leaders, hiring managers, and executives say their trust increases when data is transparent. This is a crucial finding for TA leaders as they move toward more data-driven hiring. It is vital as they explore and recommend purchasing decisions on AI tools for talent acquisition. If a technology vendor cannot explain what data its AI tool is using and how AI is being applied, that solution will not promote trust in the talent analytics it produces. Also, it may pose a legal defensibility risk for the purchasing organization.

(Source: Redefining Success: The Future of Talent Analytics, Aptitude Research, 2021.)

6. 28% track quality of hire using first-year productivity. This is encouraging as it demonstrates organizations are using talent analytics to relate TA performance to bottom-line organizational goals. Using first-year productivity as a metric also helps TA leaders better understand and demonstrate the value of their hiring process.

The use of talent analytics in first-year productivity is an essential step in creating a data-driven hiring process. There’s certainly value in tracking more subjective measures (such as hiring manager satisfaction as a quality of hire measure). However, talent analytics can help recruit teams center candidate selection and hiring discussions and decisions around the objective and bias-free data to improve new hire performance and reduce turnover significantly.
Redefining Success contains many more insights into the power of talent analytics. To better understand how your peers are using talent analytics to compete for the most qualified candidates, download the report today.