Resume parsing is a powerful tool that can help save recruiters hours of effort and significantly improve your hiring efficiency and quality. Read on to know more.
What is Resume Parsing?
As per Glassdoor, “On average, each corporate job offer attracts 250 resumes.”
It is easy to imagine the amount of time and effort that the HR and talent acquisition teams need to apply to simply go through each resume to check for fitment.
Resume parsing can be described as the process of converting resumes and CVs into an easily accessible set of information that can be properly assessed and evaluated. This technique enables recruiters to manage digital resumes more efficiently saving significantly on time and labour involved, thereby also reducing the overhead costs. These days, automated resume parsing tools and software are available that facilitate the conversion of information making it more readable. They also allow for the storage and archival of documents for future reference.
Why Is Resume Parsing So Important?
In the competitive economy of today, talent is what drives and differentiates the top companies from the rest of the crowd. However, attracting the right talent is easier said than achieved. According to a Recruiter Sentiment Study by MRI Network, “63% of recruiters say talent shortage is their biggest problem.” Hence, you need to identify the right candidate and quickly get them on your ranks, else you risk losing their services.
One of the foremost benefits that a resume parsing tool provides is the saving of human effort. This allows the HR practitioners to focus on other important business and recruitment activities. Furthermore, resume parsing also helps in making the application sorting and candidate screening processes streamlined. Considering the large volume of applications received for each job opportunity, this allows only the cream to rise to the top thereby making optimal use of the interviewer and other stakeholders’ time.
Since the tool is rule-based, it is quick and minimises the risk of errors. Not only does it improve the recruiter’s efficiency, it is also known to enhance the candidate experience which leads to a boost in the company’s brand name. Moreover, it nullifies any unconscious biases in the minds of the evaluator, which also increases your offer to acceptance ratio.
Application Tracking Software (ATS) is a suite of tools and processes aimed at significantly improving the end-to-end recruitment process. The top ATS providers have recognised the need of an efficient resume parser as the first step in the overall hiring process.
Can PDF Resumes Be Parsed?
The two most common formats of sharing resumes online are via MS Word and PDF. In principle, the underlying technology behind resume parsing remains the same. However, experts have noticed that the efficiency and results are far superior in MS Word based resumes as compared to PDF documents. Having said that, modern resume parsers have come a long way and are able to sift through the information even in PDF documents, which was harder for the previous generation of tools. There still may be the need for slight manual intervention though. Unlike PDF documents, Word resumes are editable; hence they allow the software to easily access the information fields and neatly segregate the requisite information for the evaluators to analyse and assess.
Resume Parsing Using Machine Learning
Technology is ever evolving, and the recruitment industry too has undergone revolutionary changes. Since people have been using newer and more creative templates of resumes, it has become difficult to interpret them in a consistent, homogeneous format. Moreover, people have also been finding new ways to ‘beat the system’ and build resumes that can override the parser’s check. This can lead to hiring of the wrong kind of people leading to a loss of opportunity as well as cost of onboarding and training resources that are not the right fit for the organisation.
This is where the advent of Artificial Intelligence and Machine Learning have come to the rescue of the HR industry. The two main areas where AI and ML have helped are in text and information extraction. The text extractor works like a plagiarism check and is able to effectively eliminate similarly worded resumes, as copies. The in-built algorithm also helps check for flow, themes and content that may have been copied from other sources, helping recruiters identify genuine candidates.
These rule-based engines can be customised to fit the hiring needs and characteristics of your organisation and also have different weightages assigned to different skills based on the nature of the job. ML based parsing is highly effective while assessing resumes across formats, including PDF.
Resume Parsing Online
Clearly, resume parsing can get things faster, better and more efficiently, the powerful engines that run these tools are ever-evolving and ever-learning. Thanks to cutting edge Machine Learning technology, the modern-day parser is far more advanced and able to optimise its performance based on daily usage. It also has the intuitive abilities to understand the trends and rules set by your recruiters to find the ideal talent to be ambassadors of your business.
If you’re excited to use this amazing technology in your recruitment setup, then look no further than Wisestep. Wisestep’s AI powered parsing engine is able to screen 100,00 resumes per day with information extracted from over 30 different relevant fields, getting you closer to your ideal candidate in no time
