Resume Screening — How to cut through the crap !
Written by Shivam Kaushik shivam@stratbeans.com
“Global IT industry is on pace to reach $5 trillion in 2019” (source: https://www.comptia.org/resources/it-industry-trends-analysis)
Economies, jobs, and personal lives are becoming more digital, more connected, and increasingly, more automated. With innovations and new technologies coming to fruition every day, there is an ever-increasing demand of a workforce capable of using those new technologies to their best capabilities. There is no industry without its employees, and the recruitment process of those employees if far from perfect.
With the continued increase in the growth of the IT industry, the challenges pertaining to recruitment have gone unsolved. The most common recruitment challenges as described by industry professionals are:
Engaging qualified candidates
For any given job profile, you need the candidates whose work experience and key skills are best suited for the role. You need to know the amount of experience that the candidate has had with the kind of work that will be assigned to them.
Data-driven recruitment
Companies often try to implement hiring metrics to get a KPI (Key Performance Index) of each candidate to improve the recruitment process. But collecting and processing data can be a hassle. They require manual labor, are prone to human error and are often insufficient to rely completely on for recruitment.
Recruiting fairly
Many companies struggle to attract and hire diverse candidates and unconscious biases are often the reason. Apart from legal obligations to provide equal opportunities, hiring objectively is good for business because it helps you hire the best person for the job without stereotypes interfering.
Hiring FAST!
Hiring teams want to hire as fast as possible because vacant positions cost money and delay operations. Yet, depending on the industry, making a hire can take several months putting pressure on recruiters and frustrating hiring teams.
As a recruiter, you may have to go through hundreds of resumes just fill a single job opening. Imagine yourself in the shoes of a recruiter with a week’s deadline to select the best candidate out of the hundred applicants. With more than 4 million jobs in the IT-BPM industry in 2018 alone, there is wide diversity in the formats of resumes you may encounter. Statistics go on to show that it is virtually impossible to study all of those resumes with the required efficiency and fairness. You might find yourself picking a manageable number of resumes from the collection or you may be inclined to pick the ones that more aesthetically pleasing. You might find yourself wishing that you could hire all of them.
If only there was a tool to help you generalize those resumes into a uniform format which can be easily interpreted. If only one look at a resume could be sufficient to know if a closer look is required or not. If only we could eliminate the need for the manual labor of filling out spreadsheets with hiring metrics for each resume.
Balancing speed of hire with quality of hire
Now, we have established the requirements and the problems of the recruiting process. Since a preacher must also provide a solution, we create Resumely.
Resumely is an AI-based tool that we have created for the purpose of deriving insights from resumes. You just need to upload a PDF of the resume and Resumely will analyze the entire document to give you a summarized version of the resume in a visually accessible way.
Resumely uses a trained entity recognition algorithm to identify the technology stack mentioned in the document and assembles them into a categorical view. These categories are chosen based on the factors representing broad areas of expertise. (example: Front-end developer, back-end developer, full-stack developer, data scientist, etc.)
If you feel that reading from a table is still too much of a hassle, you can always refer to the graphical representation that Resumely generates representing the top areas of expertise mentioned in the resume. Resumely assigns a score to each of the recognized entities in the document based on several factors like work experience and plots them on a Radar Plot.
A quick look at the analytics produced by Resumely can often be sufficient to know if a resume needs to be studied in more detail at which point you can manually open up the resume.
Precious time can be saved by this approach of deriving generalized, uniform views for resumes. This excludes the impact of factors like aesthetics and human errors on the shortlisting process, not to mention the automation of the most tedious part of the recruitment process.
Currently, Resumely only knows Software developers. No need to feel left out though, we can always expand this approach of generalized analysis and adapt to virtually any kind of job profile and skill set requirements.
