I saw an article recently in HRD magazine about how the ATS is a dying system. The author had some valid points, but unfortunately none of those points were actually about applicant tracking systems. His beef was really with unreliable parsing technology.
Let’s set the record straight: applicant tracking software is separate from parsing software. The two frequently work hand in hand with each other, but they are separate systems, almost always designed by different companies.
Parsing is here to stay
Resume parsing software is incredibly complex: it scans the document, converts the text and finds meaning in words to categorize the different resume sections. All while trying to maximize speed and minimize errors. What makes this task particularly difficult is that each resume is unique, using that person’s terminology, formatting and industry jargon. What’s more, word processing software brings its own distinct code into the mix. Not only does parsing technology have to make meaning of what the author has written, but it must sift through Microsoft Word’s language as well.
Technology this complex is always evolving, progressing and innovating. Parsing has not yet been perfected, and therefore we can only expect these systems to improve as our own knowledge and resources grow.
What can parsing do for me?
The reasons why applicant tracking providers are embracing parsing, and basing a lot of functionality on parsing technology are because the benefits far outweigh the occasional inconsistency. Here are a few examples:
- Searchable data: When resume information is parsed it is indexed, meaning different sections are categorized in the ATS. Instead of a simple Boolean or keyword search, you can search within specific sections and for more specific details, faster. An example is searching through everyone in the database who has a Masters degree and experience in chemical engineering in Alberta.
- Keeps everything in one system: For ATS providers like HireGround, one of the main reasons we use parsing technology is to keep resumes within our system. Instead of switching between Word, Acrobat and your ATS, parsing allows you to read through resumes within the system, making it easier to write notes and share with a hiring team.
- Easier to compare between candidates: Recruiters spend an average of six seconds scanning a resume before determining whether to go ahead with an applicant or move on. In such a short time frame, it can be difficult to compare between uniquely formatted resumes. Perhaps one applicant has their skills listed at the top, while another inserts them below their work experience. One applicant may use a chronological format, and another a functional resume. Parsing can help by grouping information together into consistent categories. Within an ATS, recruiters can easily switch between profiles, viewing the sections that are most relevant without sorting through the entire resume.
- Ranking opportunities: Parsing gives a system the opportunity to rank candidates based on their resume. With parsed information from a high quality provider, an ATS system will be able to see which candidate has the most years of relevant experience, the highest level of education, and the most applicable skills. These are items that used to have to be done manually, by someone who understands the industry, but as parsing and semantic technologies become more robust, software will be able to make meaning out of resumes and determine who’s to give more weight.
Looking ahead at big data and recruiting
I’ve given some concrete examples of how parsed data can benefit ATS users today – but this is only a thin slice of the possible uses, now and in upcoming years. Applicant data can be tracked, stored and measured in ways we haven’t even thought of yet. Assessment companies are looking at social media and gps data, while other teams are researching and predicting job and applicant patterns across the country and the world. What will all this data reveal next?