Optimizing your Resume-filtering process to improve Quality-of-Hires


A day in the life of a Recruiter usually includes a large portion of reading and reviewing resumes. Since it is now much easier to mass-apply to job openings online, on average corporate job openings attract 250 resumes each! While the number of applicants are continuing to increase, the Quality-of-hire are still inefficiently low. The gap in quality long-term hires starts with the errors at the resume-reading stage. From spending too little time on each Resume, to mismatches between the candidates and the open positions, to the human error layered throughout the reading and matching process. Ask any professional Basketball player to make 100 shots in a row, even they make mistakes and they are the best in the world at what they do. Imagine you are required to read resumes all day long, even the best get tired, distracted, “hangry”, leading to decreased accuracy and even bad employee-position fits.

Here are three Pain Points that decrease accuracy of hires and increase the cost-per-hire:

  1. Latent Human Bias embedded in the resume-reading procedure
  2. Accents/capital letters/differences in language/document formats which are usually automatically disqualified in most Resume Parsers because the Parsers are only Keyword-based
  3. Showcasing why you chose the candidate, without gut-decisions, while ensuring compliance for the Diversity of hires

Machine Learning-powered Resume Parsers such as Talent Match solves these issues with its context-based analysis process. Through the analysis and categorizing of resumes in any format, Talent Match rates candidates based on their whole resume, compared to keyword-based searches. This ensures an accuracy rate of more than 85%, an increase of quality-of-hires, and a decrease in time-to-hire. When looking to integrate Parsers into your ATS or resume databases, make sure the parser can analyze different document formats, otherwise you will lose a large portion of candidates to incorrect digital formats.

Global Recruiting Trends show that the average time to hire is between 1-2 months, this can be greatly improved with a strategy that includes automating the assessing and classification of incoming resumes and organization’s
database of resume. If you are looking to increase your quality of hire while decreasing your time to hire, Talent Match will find you the right candidate faster than ever.

Contact us today for a demo showcasing the benefits of automating your talent matching, leading to higher quality of hires in less time than ever before!

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