Job application based on job competency

Companies looking to adopt merit-based hiring should consider collecting and evaluating critical information during the hiring process.


Outside of the recruiting phase, the first real interaction between a candidate and your organization is when they fill out a job application. The application inevitably contains detailed information about the applicant, and organizations need to examine how and how well they use this critical information.

 

In Korea, a shift from 'spec-centred recruitmentto 'skill-based recruitmentbegan in 2015, led by the government. This change was a response to the negative effects of the former, which had been practised from the 1980s to 2014. During the 'spec-centered recruitmentperiod, unstructured, resume-like applications that could be purchased at the local stationery store were used. It included social security number, address, height, weight, hobbies, skills, religion, and even a "birthplaceor "original enemy,unfamiliar to today's generation. Some large companies utilized computerized application systems at the time, but the form mainly stayed the same; new items, such as grades, certifications, English language skills, volunteer work, and awards, increased the burden on applicants.

 

This was before the concepts of "on-spec- the knowledge, skills, attitudes, abilities, background, and experience required to do the job - and "over-spec- irrelevant or unnecessary requirements for the job - became commonplace. The combination of on-spec and over-spec led candidates to pile on various specs to fill up one more line on a job application. In 2013, 'beyond specificationemerged as a keyword in the recruitment market, and 'skill-based recruitment', which started with the 'Core Job Skills Evaluation Model Project', was first spread to public institutions through the government-led 'NCS-based Recruitment Consulting Projectin 2015. At this time, job applications also began to take on a more competency-oriented aspect. Initially, job applications, which were mostly common forms, began to be separated into job categories (or recruitment areas), and items unrelated to the job, such as hobbies, special skills, and religion, were minimized. Then, in 2017, 'blind recruitmentwas introduced to strengthen 'fairnessin recruitment, and items that may cause bias and discrimination, such as photos, gender, and age, were removed from job applications.

 

 


 

 

Job analysis and job applications

 

Before we get into skill-based job applications, it's essential to clarify what purpose organizations use them for. Applicants for government jobs can take a written test immediately after applying. This is primarily to provide a level playing field for South Korean citizens, and some large organizations with deep pockets do the same thing, eliminating only those who write poor cover letters and giving the rest of the applicants a chance to take the written test.

 

Most organizations have to complete the hiring process within a limited budget, so they go through a screening process to select a small number of applicants for the next stage of the hiring process. “Merit-based hiring” emphasizes evaluation and judgment based on “job skills” even in the screening process, and the purpose of the application form is to collect “valid” information related to the applicant's “job skills” in an “appropriate” way. 'Relevant' information is rich, on-spec content, and 'appropriate' means fairness and non-discrimination in the collection of information.

 

To collect 'valid' information, you need to provide specific guidance to applicants on how to complete the application form, which is preceded by a job analysis. There are many ways to do this, but you can use standardized job analysis data for efficiency. A typical method is the National Competency Standard (NCS), widely used in public organizations. NCS provides various information such as ability units, knowledge, skills, attitudes, basic occupational skills, and certifications for each job. Still, it is mainly described in text form, so summarising and applying it directly is challenging. In the private sector, it is recommended that the Korea Network for Occupations and Workers (KNOW) provided by Worknet be utilized.

 

The NCS provides quantified data on job performance, personality, knowledge, interests, values, etc., for each job, which is convenient for developing job applications and establishing evaluation criteria. However, the content is lacking. If you need additional job descriptions or details not covered by NCS or Korea Occupational Information, you can use O'NET provided by the U.S. Department of Labor. NCS, Korea Occupational Information, and O'NET all provide standardized job analysis information, but they have limitations that do not reflect the characteristics of individual organizations. However, if you discuss the contents with current practitioners and make some modifications, you can complete the job analysis efficiently.

 

The job specification derived from the job analysis includes the knowledge, skills, attitudes, and abilities (KSAOs) required to perform the job. The job application should be structured to capture this information; for example, in the 'Education' section, candidates can list their education and training for job-related knowledge, and in the 'Qualifications' section, they can list certifications related to job-related skills. This allows organizations to assess your interest and diligence in preparing for the job.

 

Additionally, the 'Work history' and 'Experience' sections allow organizations to see if the applicant has experience relevant to the job. While many job applications still ask you to list your work history and activities, limiting it to job-related content gives you a sense of the candidate's interest and preparation. This helps organizations select candidates with less of a gap between their expectations of the job and the actual work and reduces the rate of early departure for new hires.

 

Next, to collect information the "right" way, you should check your application for items that could lead to bias or discrimination. Pay particular attention to items that may be indirectly revealing. For example, military service may be included to infer gender even though it is not a Bona Fide Occupational Qualification (BFOQ), or year of birth or high school graduation may be included even though there is no age limit. In these cases, we recommend removing them. For similar reasons, we also recommend not asking for "background," which is often requested in cover letters, as it is likely a violation of blind hiring. Instead, ensure your "motivation" for applying and your "fit" with the organization and the job are experience-driven, which will serve you well in the paper and time-constrained interview rounds.

 

After organizing all items of the application, including the cover letter, you need to establish evaluation criteria based on the job analysis results. You can divide the evaluation criteria into 'quantitative evaluation' and 'qualitative evaluation', which can be approached as 'quantitative evaluation' for objective and provable content and 'qualitative evaluation' for subjective and difficult-to-prove content. The scoring and calculation method of 'quantitative evaluation' should reflect the essential KSAOs derived from the job analysis to a greater extent, and the evaluation criteria should be designed differently for each job to reflect the specificity of the job. 'Qualitative evaluation' is mainly performed by trained evaluators or managers, and the evaluation criteria and scales should be defined as precisely as possible to increase the inter-rater reliability and validity of the evaluation. After all these processes, the job application and screening process can be described as 'structured'.

 

 


 

 

The state of competency-based hiring

 

Recruitment in Korea currently varies between the public and private sectors. In the public sector, significant improvements have been made since the government-led NCS-based recruitment consulting project in 2015. The evaluation method and criteria for written applications and interviews have been structured, fulfilling the first requirement of fair recruitment-maximizing the possibility of accurate selection decisions. Blind recruitment, introduced in 2017, has also met the second requirement of fair recruitment-minimizing the possibility of discriminatory judgments. However, recent public sector recruitment has shown a tendency to overly focus on avoiding discriminatory judgments, highlighting the need to maintain a balance and ensure fair and unbiased recruitment.

 

For example, in the name of procedural fairness, the qualitative evaluation of documents is increasingly outsourced to external evaluators. While external evaluators have experience evaluating in various organizations, they may not have the same understanding of the organization's culture and talent as internal incumbents. For this reason, some public organizations use external assessments to avoid complaints or audit findings, and some oversimplify the application process in the name of blind hiring. This can make it difficult to evaluate in the paper round and the interview round.

 

In the private sector, however, there is a lukewarm response to 'skill-based recruitment' due to practical difficulties. There are three main reasons for this:

  1. Most small and medium-sized enterprises must conduct job analysis properly, making it challenging to introduce skill-based recruitment.
  2. As the government promotes skill-based recruitment based on the NCS, private companies may encounter burdens and misunderstandings about utilizing the NCS.
  3. The emphasis on blind recruitment may have created a false perception that listing schools of origin, final education, foreign language grades, certifications, etc., on job applications is discriminatory.

 

As a result, the private sector still often uses job-specific application forms, resume forms created by individuals on job portals, or existing forms provided by recruitment firms. When hiring for the same job, it is challenging to realize merit-based fair hiring if the application form needs to be structured. This is because it is difficult to evaluate many applicants consistently, and it relies heavily on the subjective judgment of the evaluators. The private sector has been thinking about structuring written and interview processes to solve these problems. It has progressed compared to the past, but more efforts are needed to structure and systematize the paper application process.

 

 


 

 

How to improve

 

Although the public and private sectors are different, there are ways to improve the process that can be applied in common. The first thing to do is to check whether the current application form items are based on the job analysis results. Once the job-related KSAOs have been identified, the application form items should be structured to collect information related to the KSAOs. However, the application form items should be kept the same to verify job competencies; they should require minimum 'legitimate' information necessary for the screening process.

 

This is more important in the private sector than in the public sector, where blind hiring is more established. The private sector will increasingly need to demonstrate business necessity as a defence against discrimination. On the other hand, the public sector should not be overly defensive about blind hiring but should allow for a variety of items to be added to verify competency.

 

Next, you need to check whether the application form's evaluation criteria are customized for each job. Public organizations are actively introducing quantitative evaluation for 'education' and 'qualifications', utilizing 'work experience', 'foreign language performance', 'published papers', etc. as needed. If you have past quantitative evaluation data (excluding personally identifiable information), you should analyze it comprehensively with the results of subsequent screening and post-employment evaluations to refine the evaluation criteria.

 

Recent advances in AI technology are also changing how qualitative assessments are conducted. Organizations that previously found it difficult to read and evaluate many applicants' self-introductions can now use AI technology to filter out a reasonable number of applicants before sending in evaluators. This reduces assessment time and the burden on assessors, resulting in a more accurate assessment of each applicant.

 

Finally, both the public and private sectors have emphasized the role of screening-out in the past, but in the future, the role of select-in will become more critical. The private sector has already shifted to rolling recruitment to a large extent, and the public sector is likely to increase rolling recruitment as job-oriented recruitment expands. Rolling recruitment is expected to use absolute evaluation because the number of applicants is small, and only those who meet the organization's criteria are accepted.

To make absolute evaluation work, you must be more precise with your criteria. In a paper-based process, the job application is the face of the organization, so candidates can actively challenge anything they feel is unreasonable. We're moving away from large-scale hiring and toward more negligible, job-specific hiring as a society. Fortunately for organizations, it's much easier to gather the information needed for job analysis than in the past, and advances in IT technology have made it possible to adopt more efficient recruitment methods. This shift suggests that organizations that have limited their use of job applications to the role of an application form need to think more seriously about the recruitment process.

 

 


 

 

Job analysis has emerged as a crucial aspect of modern recruitment. Human resource managers are confronted with the task of structuring job applications and screening in a job-oriented manner. This necessitates a comprehensive reevaluation of the application form, from its organization to the elaboration of evaluation criteria. It is particularly vital to set items based on the results of job analysis and eliminate elements that are not relevant to job skills. However, this process can be time-consuming and challenging to execute with internal resources, underscoring the importance of this step in the recruitment process.

 

As a potential solution to these challenges, the use of AI in job skill analysis could be considered. AI has the capacity to enhance the efficiency of qualitative assessments and reduce unnecessary bias. It can swiftly and accurately analyze large volumes of applicants, relieving the burden on human assessors and ensuring fair evaluation. Moreover, AI can provide valuable insights by analyzing data that was previously difficult to interpret, thereby refining screening criteria.

 

Are you curious about how AI technology can be used to analyze skills? If you'd like to learn more about using AI to analyze skills, we'd love to hear from you and help you revolutionize your hiring process.

 

 

 

 

 

 

 

 

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