Introduction and Background
The progress of technology has changed the process of recruiting dramatically. Today, due to the rapid expansion of the web, people can apply for a job in just a few clicks, and large companies and recruitment agencies face the challenge of sorting through thousands of resumes in a search for a perfect candidate. In order to increase efficiency in hiring and streamline the recruitment process, companies can resort to automated software solutions to reduce the human involvement in the hiring process. Such systems can automate the process of hiring by using computer algorithms to select the best applicants according to the requirements specified.
We will write a custom Report on Job Applications Processing System: Pros and Cons specifically for you
301 certified writers online
Since the late 1990s, the recruiting process has largely moved online, and many large enterprises and small businesses are now using online services for applicant search and electronic resume management (Munger 276). At the same time, in the last two decades more and more people turned to the Internet in their job search efforts (Smith par. 2). The 2015 data shows that more than two-thirds of all United States citizens used online resources in their job search efforts (Smith par. 2). The internet has made applying for a job much easier for job seekers, since anyone can submit their resume through a form on a company’s website or apply through job board websites. At the same time, it made the recruiting process on the part of the companies much more complex due to a larger number of resumes waiting to be processed (Hunt 56). The quality of the final decision at least partially limited by the number of applicants the hiring manager is able to process. It is one of the reasons why companies might consider automatic system to process applicant’s resumes. The automated system for job applications screening can be considered as a piece of software which can help large organizations improve the hiring process by freeing up the hiring manager’s time. Such automated systems were introduced more than a decade ago and are called Applicant Tracking Systems (Zielinski par. 1). Technological progress is likely to make these systems smarter and more functional over time.
The Overview of the Automated System for Job Application Processing
The automated system for job application processing can operate in the following way:
- Applicants sent their resumes through the online form on the company’s website or to the specified email address.
- The received resumes are then stored as a database entry ready to be processed by the automated system.
- The recruiters use the automated system to filter through the applications according to a keyword or any other applicable parameter. The recruiters can then view the search results or narrow them further by applying new filters.
- The recruiter makes the decision to invite a particular applicant to an interview or hire them right away.
- The recruiter contacts the applicant to invite them to an interview or send the required documents to be hired for a position,
Theoretically, such system could be fully automated and require minimum input from the hiring manager. For instance, the system could determine whether the applicant is the best fit for a position based on whether their qualifications and job experience corresponds to the minimum requirements, provided by the recruiter. The system could then send the employee a pre-written message inviting them for an interview or contact them via any other means of digital communication. Even the initial input could in theory be omitted. For example, if the company’s human resource information systems are connected to the automated system, the software could start searching for a new employee once a position in the company opens. The automated system could upload a pre-written job description and post it to various job boards or the company website. The extent to which the system can be fully automated depends on the company’s ability to integrate various processes such as website management software, human resource information systems and the automated system itself, as well as the availability of necessary processing and storage capacities and technical personnel (Hendrickson 381).
The usage of such automated systems as part of recruiting technologies has its own advantages and disadvantages.
The Advantages of the Automated System for Job Application Processing
The biggest advantage of the automated system is the ability to filter a large pool of resumes according to a specific keyword. In those cases where thousands of people apply for a job, it becomes impossible for a hiring manager to manually sort through all the applications. On the part of the hiring manager the recruiting process is essentially a selection process, in which the hiring manager establishes a set of minimum requirements, such as skills and education required for the position, and reviews applicants who showed their interest in the position (“Recruitment & Selection Hiring Process” par. 2). The selection process is done in several steps but typically starts with sorting through the applications of people who showed their interest in the position. It is a relatively simple task which requires human resource specialist to read the resumes of the applicants and identify those that correspond to the minimum requirements for that position. As with other simple, yet time-consuming tasks, people are looking for ways to automate the process and use time more efficiently (Zielinski par. 13).
Automatic system could have filters or keywords that allow the hiring manager to limit the number of applicants to those who are more likely to fit the job. Such filters or keywords could include age, previous job experience, schools attended, foreign language knowledge, marital status, etc. These filters or keywords could be used to search through the large pool of applicant resumes to filter out irrelevant applications. Like a search engine, the automated system could allow the hiring manager to type in the search query and see the list of resumes which contained the required keywords. At the same time, certain keywords could be excluded if necessary. Such system has already proven effective in search engines, which rely on keywords to show relevant information. Once the position is filled in, those applicants who did not receive the invite could be emailed automatically with an advice to find job somewhere else. As such, the biggest advantage of the automated system is that is allows to narrow down the number of applications to a scale a human recruiter can handle.
Another advantage of the automated system is directly connected to the concept of big data. For the last several years, big data has been a major point of interest for companies around the globe, which see it as a key to confident decision making (Ward and Barker 1). The concept of big data is associated with data storage and analysis (Ward and Barker 1). Improvements in data storage and computational analysis allow for larger quantities of data to be stored and analyzed to find tendencies and predict trends. As such, the term of big data is “used to describe the process of applying serious computing power – the latest in machine learning and artificial intelligence – to seriously massive and of- ten highly complex sets of information” (Ward and Barker 1). Such complex sets of information can be applicant resumes, stored by a large company.
The automated software can be used to analyze the CVs of those employees who have shown great results while in their position to find patterns and predict trends. Alternatively, the automated system could analyze the CVs of those individuals who were chosen for the job but failed to meet the expectations. In big companies, there is a large number of people getting hired and fired every year, which makes the analysis of their resumes interesting from a statistical point of view. Statistically significant correlation could be found between some information included in the individual’s resume and their performance in the assigned position. Such data could improve the accuracy of candidate assessment if applied in the hiring process. Again, the software could be used to match the applicant resumes to the resumes of the top performance in that position or cull those applications which are likely to cause trouble in future. In large companies, the sheer volume of data allows to analyze this information to predict trends: for example, a theoretical employee who scored a low number of points in a pre-screening test is more likely to quit the company.
The automated system relies on a database which contains applicants’ CVs. This database could provide its own benefits for the company. The automated system could store all the CVs which the company received in the specified period of time, for example, a year. If another position opens in the company, the software could then do outreach and email those applicants, who showed interest of working in the company, but were denied a position previously. Since these people have already shown their interest in working within the company, and only those people who have the required qualification and experience could be emailed, the recruiter is more likely to fill in the position much faster.
The reporting feature of the automated system for job application processing has its own advantages. Reporting tools allow the hiring manager to view and break down the data gathered from different sources. These tools could not only allow the hiring manager to quickly obtain the statistics in relation to the applicant resumes, but also view the scores the applicants achieved in different assessment tools, ability tests or pre-screening quizzes. This information could be further broken by various features, such as specific applicant characteristics.
The Disadvantages of the Automated System for Job Application Processing
Although the automated system has many benefits, there are certain disadvantages inherent to its application.
As it was mentioned before, the automated system for job application processing is a lot like a search engine, which relies on keywords and parsing to return relevant results. Just like a search engine can be cheated by putting in relevant keywords all over the web page, the applicants can cheat the automated system by adjusting their resumes to meet the job description as closely as possible. This has already happened in the search engine space, with thousands of agencies offering search engine optimization services, aimed at improving the content of web-pages to result in better search engine rankings. The greater the influence of the automated systems will get, the more people will try to put in relevant keywords, skills and qualifications to beat the algorithm. Applicants try to make their resumes more attractive all the time, but in the case traditional recruiting practices are applied, a recruiter is likely to see a mismatch between former employees, college attended, and skills described. However, the automatic system cannot (yet) actually understand the content of the resume, it is simply looking for a perfect match of selected parameters.
If the job application processing is fully automated, the recruited might not actually have an interview with the applicant to determine whether they have the knowledge and skills required for the job. It might not be the problem for simplest of jobs, such as positions of cleaning staff or cafeteria workers, but in case of those jobs which require doing complex tasks or imply a high level of responsibility, the interview is still a must. For instance, the automated system cannot accurately judge whether a photographer or web-designer is the best fit for the company’s position. In case of a photographer or web-designer, the automated system can only scan the portfolio to report a number of portfolio entries, possibly keywords if they are included, such as name of the brands the professional had worked with before. Current research suggest that most advanced computational networks are only able to judge the originality and influence of art, but fail to judge different dimensions of creativity, such as the use of subject matter or perspective (Elgammal and Saleh 22). Even if the automated system is advanced enough to judge the originality and influence of the photographer or web-designer works, it might be much more expensive than the work of a traditional hiring manager.
Get your first paper with 15% OFF
The automated system is also applicant-unfriendly since it does not give a chance for the applicant to prove their competence. The software is looking for a perfect match between the requirements sent for the job, and the information the applicant provided in their resume. This fact means that a competent applicant, who has the required skills and knowledge and could have been chosen by the hiring manager after an interview, might have their application declined by the automated system on the grounds that it does not have most of the required keywords. Limiting the involvement of human staffers might result in better processing speed at the expense of the quality of the final decision. In other words, borderline candidates, or applicants switching professions, however capable they might be, will always be at a disadvantage if the automated system is used. Real people are unique and might not be exactly similar to the profile the automated system is looking for. In order to find the best candidates for more demanding positions, the involvement of human personnel is still necessary to make the final decision.
The pre-written messages sent by the automated systems to those applicants who did not qualify for a job lack personalization and might make them feel like their applications go straight to the void. After all, the automated system for job application processing is essentially designed to disqualify applicants. In those cases when the applicant does not have a substantial work experience, or has switched jobs and has a highly varied resume, the automated system is likely to reject their applications and make the process of job search more demoralizing for them. In other words, the automated system adds to the impression that the process of looking for a job online is mostly futile.
Today, technology constitutes a great part of our everyday lives. It is difficult to imagine a world without the Internet and many useful services it provides. Although the internet made the process of job search easier for people looking for a job, it led to a situation when the hiring managers of large companies cannot manually screen all the applications they receive. The automated system for processing job applications can help the hiring manager disqualify irrelevant applications or automate the hiring process entirely. The automated system allows the hiring manager to quickly narrow down the number of applications to a manageable level by omitting irrelevant applications. This fact reduces administrative costs and the amount of paperwork. However, despite its advantages, the application of the fully automated system is limited to simple jobs which do not require high level of responsibility or creative skills. Due to the limitations of computational algorithms, such as a reliance on a set of filters or keywords used to find a perfect candidate, the application of the automated system still requires human staffer’s assistance.
Elgammal, Ahmed and Babak Saleh. Quantifying Creativity in Art Networks. 2015. Web.
Hendrickson, Anthony. “Human Resource Information Systems: Backbone Technology of Contemporary Human Resources”. Journal of Labor Research, 24.3 (2003): 381. Print.
Hunt, Steven. Hiring Success: The Art and Science of Staffing Assessment and Employee Selection, Hoboken: John Wiley & Sons, 2007. Print.
Munger, Roger. “Technical Communicators Beware: The Next Generation of High-Tech Recruiting Methods”. IEEE Transactions on Professional Communication, 45.4 (2002): 276-290. Print.
Recruitment & Selection Hiring Process n.d. Web.
Smith, Aaron. Searching for Work in the Digital Era. 2015. Web.
Ward, Jonathan and Adam Barker. Undefined By Data: A Survey of Big Data Definitions. 2013. Web.