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What Is Resume Parsing?

Data is often the backbone of business decisions, and hiring is no exception. But how confident are you about getting candidate data into your ATS? If just thinking about that question leaves you looking around, hoping for an exit, let’s introduce you to resume parsing.

Contrary to some conversations that resumes are on their way out of the talent acquisition process, they are still the industry standard for learning about candidates; their skills, experience, capabilities, contact information, and more all in one neat PDF (hopefully) package. Rather than looking individually through each resume you have your hands on, resume parsing allows you to get all of those candidates and all of the coordinating information into your database automatically.

What Is Resume Parsing?

To put it simply, resume parsing is the process of pulling data from a resume into a database. While the definition is simple, the functionality is actually quite complicated to get right.

In an ideal world, the user defines the data that the parser pulls. Still, it’s often things like identifying information (name, email, phone number, etc.), skills, work experience, and more. After parsing a resume, that information becomes stored and visible within your database to ease the sourcing process through keyword search.

Why Is Resume Parsing Important?

Like any technology, when used and functioning correctly, resume parsing can significantly impact your workflow. Here are some of the positive changes you can expect:

Improved Searchability

Since resume parsing pulls out crucial keywords and data, you can search for those in your database. Improving search performance is key to success for staffing and recruiting teams, and we have lots of resources available about search. It may be because we’re a search and talent intelligence tool, but it’s also because we love seeing hiring teams be successful!

To learn more about search, start here:

The Power of Recruiting Data and Better Search

Introducing the Newest HiringSolved

Webinar: Data Health and Talent Acquisition with Shon Burton

Better Data-Backed Decision Making

When you have more visible data, you can use that data to make better decisions. We know that at this point, “data-backed” and “data-driven” sound more like buzzwords than strategies, but the reality is that data, the right data used in the right way, can be a major player in hiring decisions.

After all, understanding what a role needs is data. Understanding what skills a candidate has to meet those needs is data. Being able to answer when your client asks, “But why should I hire them?” is data.

Eliminated Manual Data Entry

Manual data entry can be fraught with errors and takes an incredible amount of time that teams need to focus on staffing, not data entry. In this day and age, resume parsing is incredibly accurate, with some suggesting they have achieved “near human accuracy.”

Improved Candidate, Applicant, Client, and Recruiter Experience

Seriously – the right resume parsing technology can improve the hiring process for everyone involved. Parsing allows you to search candidates and applicants faster, which helps you to find the right candidate and reach out to them more quickly, which will enable you to place them faster, which makes your client happier and allows you to end the cycle of never-ending admin cycle you’re typically stuck in.

Beyond that, adequately parsed resume data also means that the chance for candidate rediscovery goes through the roof.

Does Parsing Ever Fail?

Spoiler: any technology can fail. If your parser can’t pull from the file type you’re using, the resume isn’t formatted for a computer to read, the parser isn’t functioning as advertised, etc., parsing can fail. Making sure that you’re implementing the right technology is a great way to prevent any sort of failure. If anything goes wrong, data normalization can help.

Data normalization is the process of structuring a database to reduce data redundancy and improve data integrity and usability. Therefore, data normalization is applied to data already in your database, rather than parsing, which often pulls data from a new source.

We’ve got all you need to know about data normalization here.

Conclusion

Resume parsing automatically pulls data from a resume into a database to make sourcing, qualifying and hiring people effortless. It can improve searchability and search speeds, decrease the need for manual entry, increase data-driven decision making, and, most importantly, increase the candidate, recruiter, and client experience.