Table of Contents
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Table of Contents
What Is Resume Parsing?
Resume parsing helps you review resumes or cover letters. It uses smart software to efficiently sort and store data and key words from the applications. Think of it as a first look at the resume and cover letter to ensure the candidate has what you’re looking for and isn’t just applying to everything under the sun. Then all the resumes that make it to your desk meet the basic requirements.
Why Is Resume Parsing Beneficial?
Let’s look at a few ways this can be helpful for your company.
- Frees up time. The process of reviewing resume after resume can be tedious. A day of reviewing hundreds with no good candidates in sight can feel overwhelming. Resume parsing frees up your time by searching for keywords and qualifications in the resumes to lower the number you have to manually review.
- Keeps accurate records. When you’re reviewing resumes in bulk, things can get missed, but with resume parsing, you’re providing yourself with a second set of eyes. Your resume-parsing software stores the resumes for easy access while scanning for the necessary items so you don’t miss a great candidate.
- Saves money and resources. The amount of time you free up by utilizing resume parsing instead of manually reviewing every resume can be dedicated to reviewing candidates with applications that meet your company’s qualifications.
- Eliminates bias. No matter how hard you try, when you get a resume with a flashy font you would never use or one that doesn’t grab your attention quite like the others, you can be biased towards that applicant even before reviewing the application in full. Resume parsing takes away initial bias. By providing the ability to hide factors such as age, gender, university name, and even photos, it can help you avoid deeper biases you’re unaware of.
How Does Resume Parsing Work?
Without getting too far into the nitty gritty of the behind-the-scenes of the software, it’s important to have a basic understanding of how resume parsing works.
Step 1: Conversion
First, the resume parser searches for keywords that you have set. It takes the data from the cover letter or resume and converts the unstructured data into a structured usable form.
Step 2: Separation
Once it has all the information interpreted, it segregates that info into fields. The parser converts dates into qualified work experience and categorizes those accordingly. Things like skills, achievements, certifications, and education are analyzed.
Step 3: Structure the Data
After interpretation and categorization has taken place, the parser builds a structure for you to use. It provides a “parse tree,” displaying all the data and text in one place in an easy-to-review format.
Who Should Use Resume Parsing?
Now that the benefits are clearly defined, let’s see who in your organization should consider using resume parsing.
As the front line and often the first line of defense when it comes to reviewing the bulk of the applications that come to your company, resume parsing is an important resource for recruiters.
As recruiters pass off candidates to hiring managers, the hiring manager might want to narrow down their search even further, and therefore could also benefit from the use of resume parsing.
Whether you’re an HR department of one handling the entire hiring process from start to finish or have a robust department with many recruiters reviewing applications, resume parsing should be implemented for your HR department as a whole. It provides a consistent, efficient experience for yourself and your candidates.
Tips for Resume Parsing
Before you jump in with both feet, let’s review some tips that can set you up for success.
Tip 1: Thoroughly Evaluate Your Options
As you’re evaluating what resume parsing software you may want to use, remember to look at it from all angles. Take into account the types of parsing the software provides. Does it have statistical parsing to highlight work-history timelines? Keyword-based parsing to review cover letters and resumes to find words that match your job description? Grammar-based parsing to evaluate for accurate punctuation and spelling? All three parsing types could be beneficial at some point in your evaluation process.
Tip 2: Don’t Rely on the Software Alone
Once it’s up and running, take the time to double check that the software is doing the job right. To ensure it is performing according to the needs of your organization, scan resumes that were parsed and see which ones your software discarded. Give yourself the confidence boost that the software is doing work well by adding in this extra step of review.
Tip 3: Make Job Postings Specific
In order to make the most of your parsing software, be as specific as possible in your job postings. Include all the desired skills, even things like minimal lifting requirements or desired typing speed. Be as specific as possible for what the candidate should expect in the role and what the position entails. The more specific you are in the job posting, the better applicants you should receive and the better the software can work for you.
Tip 4: Notice Keyword-Heavy Resumes
Candidates are aware that organizations use resume parsing, so they use some tools of their own to get through your parser. While this shows diligence and someone who really wants to work for your organization, beware of resumes that are flooded with keywords but may not actually have the experience or necessary expertise that you’re looking for. Don’t discard the applicants immediately, but recognize you may have to spend more time on these keyword-filled resumes and dig a bit deeper into the applicant.
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Questions You’ve Asked Us About Resume Parsing
Shalie has over 4 years of experience working in a variety of HR positions and organizations including: working as an HR department “of one”, working with a start-up based in Europe, to working in a fully established robust USA based HR department. Shalie has experience in multiple states and countries with all aspects of the HR spectrum. She has a passion to share her knowledge and experience to benefit the HR profession!