ai for recruiting

Q&A With Teradata: Tips for Successful AI Recruiting Outcomes

Q&A With Teradata: Tips for Successful AI Recruiting Outcomes

GR8 People sat down with Teradata’s Brad Cook, global vice president of talent acquisition, and Debbie Amolsch, principal talent acquisition systems analyst, at HR Tech 2019 to discuss how they approach the integration of AI-driven and machine learning applications into their recruiting initiatives. Below is a summary of the advice they shared regarding what organizations should ask and assess prior to beginning their AI journey, as well as how to ensure successful adoption among all TA team members.

Teradata has implemented AI, specifically solutions that leverage machine learning, for recruiting—something many organizations want to do but they don’t know where to begin. How did you approach the early stages of AI at Teradata?

Brad: There were two major considerations that I knew would be essential from the outset. First, we made sure we had good data available because it all starts with data integrity. You need to trust in the integrity of your data before you can begin building the foundation of your house. If your metrics are questionable, then you’re setting yourself up with a weak foundation.

And the second consideration?

Brad: You need to ask yourself, “What is the problem that we’re trying to solve?” And the answer should be one that demonstrates that actual value is being delivered at different parts of the process. I think too many organizations jump in without a solid understanding of what it is they want AI to solve for them. They’re using AI so they can say they’re using it because there’s a lot of buzz surrounding it right now. Our team invested considerable time analyzing various metrics at different parts of the recruiting cycle to understand where our biggest talent acquisition problems were.

What did your analysis reveal?

Brad: We identified three specific challenges. First, speed to apply was too high, so we simplified Teradata’s apply process. Another problem we uncovered was that, once people are in our database, how do we ensure that their data is being updated? So, we integrated data enrichment capabilities.

And our third challenge had to do with time to slate. Now that we have talent in a centralized data lake, how do we make sure we’re getting qualified people in front of the recruiter and hiring manager faster? In working closely with the GR8 People team, we’ve been able to improve the speed and accuracy with which recruiters match candidates against the job with GR8 People’s AI solution, EUREKA! This allows Teradata recruiters to focus their efforts on qualified people who have already engaged with the brand as opposed to starting at ground zero with external talent who may, or may not, know us or even want to change jobs. When you focus on those who are already engaged with you, and this includes silver medalists, you’ll move the process forward far more quickly. Think about the effect of that, too. If you can shave an additional five or 10 days off time to slate, it’s huge because that impacts time to fill substantially, which affects productivity as a company and basically every other metric we have.

I think the other aspect organizations struggle with when it comes to AI is how to roll out new technology properly so that their recruiters make the most of these emerging tools. What did Teradata do?

Debbie: This is such an important aspect because user adoption is essential to success. It’s not just the tool itself—people are part of the equation. And the reality is that not every recruiter is tech-savvy, which can be a big barrier to adoption.

What we do is identify recruiters who can and really want to become a tech ambassador. These are the people who get in there and start “kicking the tires” and playing with the new applications. Essentially, they’re Teradata’s super-users. Once they’re comfortable with the technology, they guide other recruiters by sharing what they’ve learned, as well as the wins they’ve had using the technology. Our ambassadors work one-on-on with other team members, but they also communicate their results more broadly through all-hands calls and company meetings. We also make sure that our ambassador team has global representation so that there’s localized support for the recruiting teams.

Based on your experience, what makes for a good tech ambassador?

Debbie: Don’t assume that everyone wants to be an ambassador. It’s a balancing act because you need to identify people who are good with new technology but that also welcome the experience of coaching others on how to use technology. Not everyone is well-suited to doing that. So, make sure your ambassadors are tech-savvy and that they self-select to serve as coaches for the rest of the team.

What’s next for Teradata in terms of AI and machine learning for talent acquisition?

Brad: We’re focusing on the recruiter experience by integrating the different technologies we use into a seamless interconnected architecture. We want to give our recruiters single access to an infrastructure so they don’t have to go to multiple tools to do what they need to do every day. Making it simple for the recruiter also aids the hiring manager community and, thereby, leads to faster hiring. Teradata has learned a lot from the synchronizations we’ve already completed, so we’re applying those insights to this larger effort.

Download GR8 People’s recent E-Book—Autonomous Talent Delivery: Using AI to Amplify Recruiter Performance—to learn more about the benefits of AI-driven recruiting technology, as well as what to consider at the outset.

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