Recruiting teams today know that using data to make decisions is more important than ever. Still, many recruiters and recruiting operations teams do not feel empowered to dive into their data, even if they have the analytics tools to do so. What’s going on? In this article, we explore this question and more. Read on to learn about:
- The importance of collecting quality recruiting data
- What recruiting operation teams need to be successful
- Why domain-specific tools help you better analyze recruiting data
It should come as no surprise that we here at CodeSignal are strong believers that recruiting processes should be data-driven. In fact, it’s at the core of our business. Using data to inform your recruitment decisions makes for better hires, eliminates bias, and reduces cost to hire, among other benefits.
Most recruiters today have access to a wealth of data about their recruiting processes. If they use an applicant tracking system (ATS), more data is being collected automatically than they may even realize! Having the data, however, is just the first step. Just as crucial is knowing how to interpret the data and translate it into actionable insights.
This post draws from a recent episode of Data-Driven Recruiting, where CodeSignal Co-Founder Sophia Baik speaks with Benji Encz, Founder and CEO of Ashby, a platform that helps recruiting ops teams with advanced analytics and automation modules. Baik and Encz discuss the importance of collecting quality data about your recruiting, what recruiting ops teams need, and why recruiting data is often under-utilized – as well as how to overcome this problem.
Collecting Quality Data
To really analyze and make the most of their data, recruiting teams need to first make sure they are collecting high-quality data. When Encz works with recruiting ops specialists, one of the first things he notices is challenges with the quality of the data itself: data that isn’t tracked or tracked inconsistently, and data that hasn’t been cleaned, for example. (What is clean data? It’s the gold standard for data analysis and means that the data are valid, accurate, complete, consistent, and uniform.)
The good news? If you use an applicant tracking system (ATS), lots of useful data are being collected consistently and automatically already. “If you think about recruiting and the tools that are used, a lot of structured data is captured,” says Encz. “By using an ATS, you’re already tracking all the structured data. You have a lot of data available.”
What Recruiting Ops Teams Need
Once you have the data, the next step is knowing how to make sense of it. Many recruiters these days have the benefit of being supported by a recruiting operations team: people focused entirely on supporting recruiters and hiring teams by managing their tech stack, measuring performance, and more.
What recruiting ops teams need to be successful, says Encz, are tools that allow them to automate many parts of the recruiting process (like scheduling, for instance) while also being highly customizable for their use case. They also need tools that give them more control over the data they collect and that make data analysis fast and easy – which includes integrating seamlessly with their ATS.
How to Make the Most of Your Recruiting Data
Truly understanding and drawing insights from your recruiting data can be a challenge, Baik and Encz agree. Even bringing in a business analyst or data scientist to interpret the data for your recruiters may not produce the best results.
“There’s a specialized way of analyzing data in recruiting,” says Baik. “You really have to understand the recruiting process inside and out to deliver useful insights that can actually make a difference.”
The trouble is that many recruiters do not feel empowered to analyze the data for themselves, either – even if they want to. A recent study found that 71 percent of recruiters say they need intelligent tools to process data for them. With tools like Ashby, recruiting ops teams and even recruiters themselves can easily access pre-canned reports and metrics to make sense of recruiting data. “It makes all of this data a lot more accessible,” says Encz.
Making the most of your recruiting data isn’t just about consistently capturing quality data. It also requires you to have the right tools to make sense of your data and translate it into business impact. One way to do this is to empower your recruiting ops teams and recruiters to explore recruiting data themselves with domain-specific analytics tools.
Combine quality data, great tools, and a recruiting team empowered to use their data, and you’re well on your way to optimizing all of your recruiting processes.
Want to learn more about how you can build a winning organization through data-driven recruiting? Visit CodeSignal to find out how you can measure technical skills effectively and objectively with its automated assessment and live interview solutions.