Reviewing resumes can be the hardest and most demanding part of the entire hiring process. It’s extremely time consuming and is the first of many steps in a lengthy process. Unfortunately, it’s entirely necessary because job boards aren’t dead yet and resumes remain the primary way that candidates present themselves to companies. Social recruiting has its advantages but collecting resumes is still the most effective way to start the hiring process.
If resumes continue to be the way forward, we need to figure out how to address some of the issues surrounding the review process. We’ve had countless conversations with industry experts about this and come up with the following list.
Why reviewing resumes is broken:
- Resumes can create false pretenses about candidates (good or bad) due to the pattern recognition practices required to evaluate large volumes of resumes.
- Resumes offer so much information about a person that it can take hours to properly dissect and understand everything. (Company backgrounds, awards, technologies, employment patterns etc.)
- Smart people can be terrible at writing resumes and “less productive” people can be great at embellishing their accomplishments.
- Unconscious bias towards, companies, titles, names, age, and race can prevent quality candidates from being considered.
With so many potential issues in the review process, it’s amazing that recruiters only spend an average of 6 seconds per resume. It would take so much time and mental capacity to completely evaluate a resume that it is not a practical approach for many recruiters under serious time restrictions. Often times, it’s easier to find candidates in the ballpark, then let the managers decide. This leads to even bigger problems because managers lack the time to fully understand a candidate’s foundation. Hello, bad hires.
Our approach to combat this is to help recruiters and managers ensure that resumes are evaluated with more depth than the 6 second, simple pattern recognition in place today. Vettd highlights the most relevant candidates based on millions of attributes while removing potential bias. This creates an opportunity to focus energy on getting to know the right candidates.