Recruitment is easy. Employers want to hire the best and candidates need right opportunity. It’s that simple.
But wait! Then, why would recruiters take so long to close jobs and take multiple hits on applicants for a single open position?
It’s all about technology that acts as a buffer on both the sides: Recruiters and Applicants. ATS (Applicant Tracking System) is the most common tool used for hiring in 80 percent of businesses of all sizes and nature.
ATS with the aid of resume parser extracts useful information from resumes and makes them searchable on any database. Now, ATS has to bank upon resume parser to accurately identify the information and put it under relevant fields in the database.
In short, both should complement each other.
It is not always obvious, stuffing your cv with keywords will dodge the ATS. Today, ATS’s with the help of parsing semantic capabilities quickly detects overuse and ignore the hyped resumes.
A lot depends on the resume parser when ATS is put to test or evaluation. An agile parser should be able to sort keywords written the wrong way even. The ingredient of a high quality parsing engine is to understand both the words/phrase and context in which word is used.
People often say, resume parser is a thing of past but even today, the parser sits on the fence of an ATS and captures the info. Usually, resume parsing is of three types:
- Keyword-based parser to identify words, phrases and patterns. Parser uses its own algorithm to find text around those words.
- Grammar-based parser captures meaning of sentences on a resume.
- Statistical parsers to find structure on a resume and deduce a numerical model.
CV parser is the only tool in ATS that automates the resume reading and entry process of all different formats. An efficient parser follows the industry standards and gives the output in HR-XML which makes it feasible for custom ERP, HRMS and Enterprise applications, other than CSV or Excel format.
And here comes the biggest lie of parsing vendors who hails their solutions as superior and claim 100% accuracy, only after applicant correct the errors. It isn’t a fair game anymore, and ATS’s must listen to client requirements before tall claims.
ATS with a strong resume parser at the core can help companies reduce overheads in managing talent by abandoning manual entries and wrong information being put into the database.
Growing ATS’s should pool resources with performing cv parsers of the market and take the baton from where parser leaves the process, not rather initiating the run from the beginning. This would ultimately help candidates reduce the time to fill applications and on the other hand endow recruiters with ample amount of time for engagement activities.
Resume being whisked into Recruiters ATS and candidates not able to jump-shift the next step, owing to a poor cv or less matching keywords.