The term data analytics encompasses scientific techniques for analyzing raw data to develop useful insights and solutions. As raw and accumulating data can be found in any sizeable business setting, data analytics has a near-infinite number of applications across the world’s industries. In the field of HR, resume parsing uses AI-enabled data analytics for a more efficient and engaging hiring process.
Use of Data in Resume Parsers
In a nutshell, resume parsing is the use of AI algorithms to organize, cluster, and analyze resume data. It is the use of AI-enabled automation for analyzing recruitment data, specifically for more efficient candidate processing.
The key challenge in resume parsing is how the free-form and unique templates of candidate resumes can be converted into structured information. As any HR manager will tell you, virtually every candidate uses their own unique resume format, resulting in a chaotic but data-rich collection of graphs, tables, images, and other random data. As the templates and resume data becomes more complex, the more intelligent the classification system needs to be. This is why here at Skillate we saw the need to create a new classification system that can pull meaningful data out of this chaos. And in order to do that, it combines open-source optical character recognition (OCR) technology with deep learning AI algorithms.
The Science Behind Resume Parser
While OCR ensures that not a single word of important data is lost in the search, the AI algorithms on top of it glean the context of each word based on the entire text. The result is a resume parser that can make sense out of the chaos when analyzing larger and larger data sets. And the more data goes through the system, the more intelligent the deep learning AI on top of it becomes. If your company’s having trouble parsing through thousands of viable job candidates, Skillate can help you to customize this process from the ground up. From fine-tuning your data parsing format and clustering parameters to the way the resulting insights are visually displayed, data analytics are crucial to the process.
The most obvious value of leveraging data analytics for recruitment is helping your HR department to more accurately and efficiently match candidates with open job positions. Apart from that, this also arms them with an AI-enabled tool that could not only fine-tune recruitment but also contribute to other HR-related tasks. This includes improving employee engagement, satisfaction, and developing company culture. And if this is your company’s first foray into AI-enabled data analytics, it can also give you a purview of how you can leverage the valuable business data found in every other facet of your organization.
In short, resume parsing not only puts you in touch with the best possible talents, it can also ensure that your HR and recruitment staff, data, and resources are being maximized. And as for those whom you don’t end up hiring, you can rest assured that they walk away with a positive impression of your efficient and expedited hiring process, which helps your brand image in the long run. By leveraging data analytics for recruitment, you can improve your company in a variety of ways.
Why Data is becoming increasingly important in recruitment
Considering its potential business benefits, it’s no surprise that the demand for data analytics experts continues to grow. In a survey of workforce trends involving 240 tech industry leaders, 57% identified data analytics as an in-demand technical skill in their company. Meanwhile, software development and project management were also considered to be in-demand skills for 56% of the surveyed tech companies – both of which are skill sets that not only intersect with data analytics, but are also integral to its current rapid growth.
"As it becomes more difficult to find candidates with the right skills and the competition for qualified applicants heats up, companies will need to expand their recruitment pipelines and offer more training for employees to help close the skills gap," explains U.S. Jobs director of strategic alliances Jacqueline Black. And as data analytics and its related fields introduce improvements in the recruitment process to encourage more candidates, this will have an impact on the number of students studying data analytics at higher education institutes.
In fact the demand is fast outweighing many institutes’ ability to teach the subject on campus. So much so that Forrester Research analyst Brandon Purcell notes how many students studying data at higher education are entering the “job market either from graduate programs or after getting "nano degrees" from massive open online courses”. One reason for this is that the course is perfectly suited for online study. For example, data visualization and presentation programs, as well as analytics learning modules can be easily applied to online platforms that can be accessed off-campus. And this is changing how recruiters target potential candidates, with many now looking at those with non-traditional degrees. This is a trend that is being reflected in the job market outlook for the next 8 years. Currently, graduates completing online master’s in business data analytics programs who work in market research and management consultancy can look forward to a career growth rate of 20% and 14% respectively until 2028. These are figures that could easily increase before the end year if the current demand is not met.
In short, data analytics and recruitment work perfectly together. And we can help you ride the disruptive waves of this massive and data-enabled digital transformation.