As companies look to the future of talent acquisition, they must re-examine talent analytics. Organisations need a more robust approach that harnesses the power of provable, scientific data. According to a new study by Aptitude Research, only 1 in 3 companies use performance data in their recruitment decisions, and 1 in 2 companies do not trust their data sources. 

TA managers are familiar with collecting data, tracking metrics and key performance indicators (KPIs), but they often fail to turn that data into actionable insights. Analytics is the practice of using metrics to make better decisions. If metrics help answer the “what?” then analytics answers the “so what?”

To shift from a “what” to a “so what” TA strategy, companies must better understand the data they are using, its quality, and how they are sourced. 

The new study, Redefining Success: Talent Analytics for the Future, looks at how companies rethink their analytics approach. Here are some of the top findings from the report:

Companies are not satisfied with their data quality: Over the past few years, many TA teams have struggled to manage disparate systems and an influx of data. The primary challenge that they face is not necessarily the quantity of data but rather the accuracy and consistency of that data. We found that less than one-third of companies are very satisfied with their data’s accuracy, quality, and integrity. 

Companies are not always starting with the correct data: They often start with a resume or social-profile information, ignoring specific candidates and including biases. 55% of companies rely solely on resume data to make talent decisions. This information is not necessarily an indicator of performance or quality of hire. Consequently, by relying exclusively on the resume to make hiring decisions, employers can erode candidate trust and confidence in the hiring process.

Transparency leads to trust: Data transparency is the ability to access and work with data regardless of a location quickly, and having confidence that the information is accurate, all of which is critical because it creates trust. If a vendor cannot explain its AI, its methods may not be legally defensible. The right vendor should explain how its AI works and validate that its tool is not replicating human biases or otherwise harming protected groups. When data is transparent, we found that it increases TA leaders’ trust, hiring managers, and executives.

Collect unbiased assessment data to inform decisions: Assessments provide the science and insights to inform decisions better. Companies that leverage assessment providers are three times more likely to improve the quality of hire. The data used to drive decisions must incorporate performance and post-hire data. Organisations looking to define the quality of hire must look at their existing employees. This data (which includes first-year retention, performance, and productivity) should help inform TA processes. 

To understand how EVA.ai can help you solve data quality, fresh profile information, transparency, and bias problems, start a conversation clicking here