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Unfortunately the lack of a standardised format hasn’t stopped technology from being developed which automatically reviews CVs before they hit a human. The tech

Unfortunately the lack of a standardised format hasn’t stopped technology from being developed which automatically reviews CVs before they hit a human. The tech is already out there. The problem we have currently is that some CVs fail that review because they’re in a format that the tools cannot parse. If you’re CV is strong but you’re seeing fewer responses despite having a prettier CV compared to your peers, then that might be the reason. So from your stance standardisation might actually help the industry rather than harm it.

indymike 5y ago
> The problem we have currently is that some CVs fail that review because they’re in a format that the tools cannot parse. My company (we have software for responding to applicants in real time... think apply... instant conversation with a human recruiter) did a study of about 1,200 resumes and found that 14% of resumes had inaccuracies that would cause them to be screened out... and about 9% of resumes were in a unparsable format. A lot of the screening we see out there is really bad - mostly text search looking for key phrases like specific colleges, specific employers or specific skills. If you are imagining indexing resumes with elastic search and making queries, that may actually be better than state of the art which is usually something that turns into a SQL query.
- laumars 5y ago
  Given a lot of these tools cannot even parse CVs with inlined tables, the tools I’m imagining aren’t sophisticated in the slightest. But they are depressingly common.
- mcenedella 5y ago
  10 - 15% are typically unparsable, typically PDFs encoded as graphics, and to a lesser extent, Linkedin exports. 14% with incomplete information also sounds right. And I also concur with you on the screening being pretty basic, not ES level of sophistication at all.
  - indymike 5y ago
    The unparsable numbers are really close to what we see. Lots of work to be done to make hiring better.

indymike 5y ago

> The problem we have currently is that some CVs fail that review because they’re in a format that the tools cannot parse. My company (we have software for responding to applicants in real time... think apply... instant conversation with a human recruiter) did a study of about 1,200 resumes and found that 14% of resumes had inaccuracies that would cause them to be screened out... and about 9% of resumes were in a unparsable format. A lot of the screening we see out there is really bad - mostly text search looking for key phrases like specific colleges, specific employers or specific skills. If you are imagining indexing resumes with elastic search and making queries, that may actually be better than state of the art which is usually something that turns into a SQL query.

laumars 5y ago
Given a lot of these tools cannot even parse CVs with inlined tables, the tools I’m imagining aren’t sophisticated in the slightest. But they are depressingly common.
mcenedella 5y ago
10 - 15% are typically unparsable, typically PDFs encoded as graphics, and to a lesser extent, Linkedin exports. 14% with incomplete information also sounds right. And I also concur with you on the screening being pretty basic, not ES level of sophistication at all.
- indymike 5y ago
  The unparsable numbers are really close to what we see. Lots of work to be done to make hiring better.