An intelligent recruitment application can help hiring managers carry out the recruitment processes quickly and efficiently, reducing the time and cost for recruitment and improving the quality of hire.
The traditional recruitment process faces two major challenges. The first challenge is that recruitment processes take a long time to complete. The average time to fill a position is about 42 days. This is a worrying number for candidates, hiring managers and organizational leaders alike. The second challenge is finding the right candidate. About 52% of talent acquisition leaders say the hardest part of recruitment is identifying the right candidates from a large applicant pool. To save time and effort, organizations usually start the recruitment process without first identifying a high-quality talent pool of candidates. This leads to enterprises hiring low-quality candidates and often having to relieve the onboarded candidates after a probationary period. They then have to start the recruitment process all over again for the same vacancy resulting in the wastage of time, resources, and money. To overcome these challenges, HR teams need an additional support system that can guarantee that enterprises end up hiring the best possible candidates and in the shortest possible time. So is there a solution to the recruitment challenges? Yes! An intelligent recruitment application can be the perfect companion to HR teams and can help reduce the hiring time while ensuring that organizations find the best candidates.
To understand how exactly an intelligent recruitment application can improve your recruitment process, we’ll have to look at some recruitment KPIs and how using recruitment intelligence improves them.
According to Glassdoor’s HR and Recruiting statistics, the average cost per hire in the USA is a whopping $4000. Enterprises also have to incur additional costs of posting listings on multiple job boards to attract a high volume of candidates. Additionally, in order to shorten the recruitment time for multiple simultaneous open vacancies, enterprises end up increasing their HR staff or hiring talented recruiters, which can cause an extra burden on their pockets. The recruitment costs are only expected to rise higher and higher in the future.
AI tools can help reduce expenses associated with recruitment and also improve the efficiency of the process, significantly reducing the cost per hire. Data-driven AI recruitment tools can help target the right candidates and deliver better quality candidates faster at lower costs with intelligent candidate screening capabilities. Similarly, an intelligent recruitment application can also help with your job advertisement budgeting. The tool can help identify the easy and hard-to-fill jobs, and thus, you can manage your advertisement budgets accordingly.
We have seen earlier that it takes more than a month to fill a vacancy. This usually happens because HR teams are constantly caught up in repetitive tasks. This leads to a shortage of time to carry out other tasks and can result in a communication gap between candidates and HR managers, delays in interview scheduling and candidate shortlisting, and even delays the candidate onboarding.
An intelligent recruitment application can automate most of the processes, freeing up the HR department’s time and allowing them to better focus on and manage more important tasks. This can help fill the open job vacancies faster. For example, an intelligent recruitment application can be used to automatically create an interview schedule for the shortlisted candidates based on the interviewer’s calendar data. It can also send automated emails regarding the interview schedules to multiple candidates at once, enabling recruiters to focus on other important tasks.
As seen earlier, enterprises aim to lower the cost and time per hire. This often leads to them hiring low-quality candidates. There is a visible gap between the candidate’s skill level and the skills required for the job position. Thus, enterprises are forced to either invest in training candidates to improve their skills or look for a replacement.
This problem can be easily solved by a thorough analysis of the candidates’ soft and hard skills in the recruitment process. One way to do this is through competency mapping, and an intelligent recruitment application can precisely help with that. The tool can be used to automate parts of the interview process. It can be programmed with the expected answers from the candidates verbally. The tool, armed with Natural Language Processing capabilities, can understand and analyze the answers given by the candidates by identifying certain keywords and the context in which they were used. It then creates a report based on the data collected. It ensures that candidates with the right skills and knowledge are selected and minimizes the need for a human interviewer.
An intelligent recruitment application can be utilized in almost every stage of the recruitment process, right from job creation to candidate onboarding. Some of the key milestones and the impact of an intelligent recruitment application are discussed below.
An intelligent recruitment application helps find passive candidates, significantly improving the talent pool available in quantity and quality. It uses AI to search for data that candidates leave online (previous applicants, data shared on networking sites) to find candidates that match the job requirements. It then sends automated notifications, in the form of emails and text messages, to the candidates, which reduces the time and cost of hire for such candidates.
AI can be used to remove the current hurdles in communication in the recruitment process. With NLP and NLU capabilities, intelligent recruitment applications can be used to respond to candidate queries automatically. This helps remove the communication delays that candidates usually experience as the human resources staff is occupied with a multitude of tasks. For example, the tool can analyze keywords in an email sent by the candidate, such as ‘interview date,’ ‘interview time’, and ‘application status’. Based on the information available, it can respond to such emails without the need for human intervention, significantly bridging the communication gap.
The recruitment intelligence application can be used in two ways in candidate interviews. First, it can be used to autonomously conduct interviews and determine the best possible candidate for the job. With NLP capabilities, the tool can analyze strings of keywords in the answer given by the candidates to determine how accurately the candidate has answered the question. It can then generate a scorecard for each candidate, helping save the time of the recruitment teams. The second way an AI-capable application can be used in interviews is for analyzing the candidate’s behavior. The tool leverages facial recognition technology to analyze changes in the facial expressions of candidates that can help determine whether a candidate is saying the truth, lying, or is nervous while answering questions. Similarly, it can also be used to analyze the candidate’s body posture and language to determine whether the candidate was interested, bored, or lacked confidence during the interview process. This helps analyze the soft skills of the candidates and helps in decision-making regarding candidate selection. Artificial intelligence will change the way organizations look at the hiring process. It will enable recruiters to become more proactive in the hiring process and ensure that the organization finds the best-suited talent in the shortest possible time. The intelligent recruitment application, however, should not be looked at as a complete replacement for human recruiters. Rather, it should be employed as the perfect companion to your existing human resources team.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.