An Introduction to NLP and How it is Transforming Recruitment
According to research, making a poor hiring decision based on unconscious prejudices can cost a company up to 75% of that person’s annual income. Therefore, it’s critical to hire the appropriate personnel.
However, deciding what is “correct” and what truly matters is solely a human prerogative. In the recruitment and staffing process, natural language processing’s (NLP) role is to free up time for meaningful human-to-human contact.
Here the hiring processes are streamlined, valuable insights are revealed, and participants are engaged. NLP defends against information overload and inattention, allowing a high-touch hiring process to be transformed into an enjoyable virtual tour.
Natural language processing is a branch of artificial intelligence (AI) that’s still a relatively new idea in the HR industry. Let’s look at NLP and how HR teams use it today before we get into how it can alter the HR department.
The Importance of NLP in Recruitment
Even though jobs were available in the United States, according to an SHRM 2019 study, only 6.3 million people were looking for work. However, with the current market’s widening skill gap, it’s becoming increasingly difficult to maintain a pipeline of individuals ready to be hired whenever needed.
To help you eliminate prejudice from the hiring process, your hiring managers can leverage a built-in AI technology, such as NLP processing. There are a few game-changers among the many advances NLP brings to the table:
- The interviewing process is quick. Chatbots and intelligent resume-checking software are better at prescreening and sourcing (the most time-consuming chores). Instead, recruiters may pay greater attention to elite talent.
- Enhancement of the source is a bang. Consider all social media venues where you can advertise positions or recruit talent. Balancing it all is difficult for a human, but it is simple for a machine once the criteria are established.
- The struggle for talent is genuine because of limited resources and fierce competition. Recruiters want to seize the first best fit. NLP helps extend the hiring capacity improving agility and allowing top people to be engaged better and sooner.
- You can also automate the candidate prescreening process, making your overall recruiting process much more efficient.
5 Ways Integrating Natural Language Processing (NLP) Will Transform HR
1. NLP in the Recruitment Process
You know how difficult it can be to go through many resumes as a recruiter. As a result, while assessing resumes, most recruiters begin to concentrate on keywords. This is, in fact, one of the most inefficient and erroneous ways of candidate selection during recruitment procedures.
Human Resources departments and recruitment platforms can do the following by processing internal and external data:
- Detect abilities, professional backgrounds, and experiences represented in a CV, professional profile, or job to benefit from relevant matching.
- Find the best profile with the help of a robust semantic search engine that allows you to pre-select the top prospects/collaborators for a job offer or a position.
- Using an advanced filter and a multi-criteria search, tailor a candidate or job role search.
- When collecting or updating internal profiles, automate the entry of profiles.
- Internal skill mapping to identify talents and training needs.
- Utilize a single HR application or existing HRIS software to manage the entire recruitment and internal mobility process.
Therefore, NLP allows you to take a data-driven technique to resume screening, which not only saves you time but also allows you to make better decisions after the interview process.
For example, APEC purchased an NLP tool between 2012 and 2016 to classify job offers submitted on the platform, identify dubious offers, and provide candidates with a sophisticated search and ranking interface for requests.
You can also use NLP to score and categorize candidate profiles during the resume screening process, discover candidate characteristics, and minimize unnecessary biases.
2. Employee Voice and NLP
Companies increasingly focus on listening to employees after implementing major customer listening programs.
According to research, 67% of job seekers think a company is more trustworthy if they receive regular updates during the application process. If you fail to regularly connect with your prospect candidates or fail to make them feel valued, it will result in broken engagement and no retention.
Giving employees a voice and focusing on human language has become critical to retaining talent, maximizing employee engagement, uniting them around a single project, and enhancing operational operations.
This involves NLP-based AI for gathering employee feedback, such as regular satisfaction barometers or systems for assessing employees’ feelings at essential career stages.
3. Natural Language Processing as a Tool for Employee Engagement
Natural language processing algorithms use text analytics to provide sophisticated insights into employees’ attitudes, uncover conflict areas, and conduct extensive feedback analysis and statistical models.
You may measure and build an employee engagement plan that solves employee problem areas and fosters engagement based on these automated data.
According to a McKinsey study, recruitment automation might enhance worldwide productivity by 1.4%. Automation in recruiting helps recruiters save time by allowing them to do more tasks in a comparatively shorter period.
Hundreds of thousands of employee comments can be analyzed by AI-powered engagement tools to find the most relevant keywords and phrases in your organization, allowing you to summarize and swiftly present the essence of employee input.
Furthermore, you can use communication and interaction platforms with an NLP solution to give HR teams real-time insight into employee attitude and satisfaction.
4. Chatbot for Human Resources
Internal support departments face challenges in responding to all employee requests for data swiftly and efficiently, whether for administrative reasons (requests for pay stubs, leaves, expense reports, and so on) or for organizational reasons (who works with whom? Who’s in charge of this or that project?).
An HR chatbot assists candidates in swiftly obtaining knowledge of the company’s structure, operating rules, and internal procedures.
According to the Gartner study, chatbots have already saved $8 billion in costs each year.
It is frequently linked to a corporate chat system to relieve administrative personnel of repeating questions while also providing a centralized point of access to the company’s unstructured data.
4. Employee Social Media Analytics with Natural Language Processing
NLP is a powerful “listening” technique that HR teams may use to evaluate employee social media content to reveal areas of interest, identify employee potential and talent, determine competency, and track behavior trends.
According to research, during a job search, most candidates learn about potential employers through the companies’ content and media, such as blogs, news, and videos,
Employers can use social media analytics via these tools to attract and identify potential hires during the candidate prescreening process, know their interests, and eventually push retention through insights focused on social media analytics.
NLP in social media analysis can also be a helpful adjunct to your employee advocacy program, allowing you to justify the program’s return on investment. This can also significantly help in assessing candidate behavior at large in your hiring data.
NLP will become a must-have technology for forward-thinking enterprises as AI solutions evolve. Have you implemented NLP solutions in your company? If you want to know more about how NLP is transforming recruitment, contact Recruiter.com today!
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