Skills-based hiring in different occupations: how does job analysis help?

Jiaying Law

People Scientist

Skills-based Hiring in different occupations: How does job analysis help?

To thrive in today’s dynamic business environment, your company must equip itself with employees possessing diverse skill sets, ensuring adequate skill flexibility within the organisation. This flexibility allows organisations to adapt to potential changes in business strategy and eventually enhance company performance (Bhattacharya et al., 2005). 

Skill-based hiring is a solution for building a company with high skill flexibility. It is an innovative recruitment approach that prioritises measurable and objective skills required for a job or company, rather than relying on indicators such as CVs, motivation letters, or education, which have low predictive power for future job performance.

For example, if your company is developing a new product or service, you may require employees with specialised product knowledge, high creativity and strong critical thinking skills. By implementing skill-based hiring, you can create job profiles tailored to your hiring needs and effectively identify suitable job candidates.

In this article, we’ll delve deeper into skill-based hiring, specifically focusing on: 

  • Skills required for different groups of occupations
  • Factors influencing skill requirements
  • How does job analysis aid skill-based hiring?

Skills required for different groups of occupations

The labour market offers numerous occupations, but how do they differ in the required skill set?

According to Handel and Colleagues (2016), occupations can be categorised into five broad groups:

a. More complex white-collar: management, technical occupations etc.

b. Less complex white-collar: data entry operators, executive assistance etc.

c. Highly-skilled blue collar: craft and repair workers, construction trades, mechanics etc.

d. Less-skilled blue collar: factory workers, truck drivers etc.

e. Service: food service workers, home health care aides, child care, police, firefighters etc.

In their survey, they found that interpersonal skills (e.g., giving information, teaching or training people, dealing with tense situations etc.) are relatively more important for white collar and service workers, in comparison to blue collar workers. Conversely, physical demands (e.g., standing for at least 2 hours, good body coordination) were relatively less important for white collar workers. 

Additionally, technology used on the job differed between white-collar and blue-collar workers, with the former employing more computer technology (e.g., laptop, databases, special software etc.) and the latter relying more on non-computer technology (e.g., machine set-up, operating robots, automated equipment etc.). 

Regarding academic skills, more complex white-collar and high-skilled blue collar workers required advanced maths skills (e.g., algebra, geometry, statistics etc.). Basic reading skills were reportedly used on the job by almost all individuals across all occupational groups. In addition, more complex white-collar workers demonstrated a need for advanced writing skills used on the job. Lastly, the complex comprehensive skills were less used by less-skilled blue collar and service workers, compared to other groups.

In summary, this analysis offers a brief overview of the skills required in different occupational groups. However, there remains a lack of information on how to identify the specific skills required for individual job positions.

Skill-based hiring in different occupations - table

Factors affecting skill requirements

Jobs are complex and it’s challenging to establish a standard set of skills for every job. Even within the same occupation, skills required and detailed tasks could vary. In this section, we will explore two factors that might influence skills requirements within the same occupation.

The nature of different sectors

The nature of different sectors significantly influences the skills needed for jobs. 

For instance, the skills required for managers in the hospitality industry differ greatly from those in the information technology (IT) industry. To excel in their position, managers in the hospitality industry may need more interpersonal skills but managers in the IT industry may need more complex problem-solving abilities (Huang et al., 2021). 

Here are examples of skill requirements in different industries:

  • Energy sector: Lyu & Liu (2021) examined job descriptions for four major professional occupations in the U.S. energy sector and discovered a growing demand for soft skills (transferable skills) compared to hard skills (job-specific skills). Among these, critical thinking, listening, mathematics, and communication skills were deemed most essential for energy-sector occupations (Gonzalez et al., 2015).
  • Fintech sector: Doherty & Stephens (2023) observed a decreasing emphasis on hard skills in the fintech sector, with a simultaneous rise in the demand for advanced soft skills among graduate hires.
  • Financial sector: Kuchciak & Wiktorowicz (2020) identified key competencies demanded by employers in the financial sector. These include handling specialised computer programs, willingness to take responsibility for tasks, and proficiency in using electronic devices like computers, tablets, or smartphones. Additionally, analytical skills (problem-solving skills), business awareness (real-life experience), and basic accounting skills are highly valued by employers in the accounting field (Kavanagh & Drennan, 2008). 

 

These examples demonstrate how the skills demanded in various sectors can differ significantly, emphasising the importance of tailoring skill sets to specific industries and occupations.

The labour strategy

Skill requirements also vary based on the labour strategy employed within each organisation, or in other words, an organisation’s plan to effectively manage its workforce.  

To illustrate, let’s examine a case study that demonstrates how national skill formation policies can impact labour strategies. Krzywdzinski (2017) conducted a comparative analysis of skill requirements in manufacturing industries, particularly highly automated automotive suppliers, between Germany and Central Eastern Europe (CEE).

In Germany, vocational education often includes dual programs with intensive workplace training, whereas in CEE countries, workplace training tends to be less structured and shorter. That means, skill formation programs in CEE may not offer the same level of technological and practical knowledge as vocational education in Germany does.

As a result, manufacturing plants in Germany may adjust their labour strategies to prioritise a more highly skilled workforce by creating complex roles. Conversely, in CEE, manufacturing plants may adopt more standardised workflows or provide job-specific training when hiring less skilled workers. 

These differing labour strategies lead to notable differences in job roles, even in the same occupation. For example, production workers in German manufacturing plants may be involved in product development or new technologies implementation, while their counterparts in CEE are less likely to participate in product-related planning processes.    

 

In short, the characteristics of different industries and the labour strategies employed can influence the skills needed for each job position, even within the same profession. Therefore, relying solely on existing job profiles for certain occupations may not entirely meet your hiring needs when filling new roles in your company.  

So, how can we ensure greater accuracy in determining the skills needed for our open positions or adjusting existing job profiles to fit our requirements? We need to focus on the specific job tasks that must be fulfilled in our work positions.

How does job analysis aid skill-based hiring?

A job task involves carrying out work activities that yield tangible outcomes, such as goods and services, while a skill is the ability possessed by a worker to perform these tasks (Matthes et al., 2014). Therefore, to determine the required skills for a job, we must first comprehend and analyse the specific tasks associated with the job role. One recommended approach is to conduct a comprehensive job analysis, which involves examining all job tasks, identifying the most important ones, and then pinpointing the critical skills needed to accomplish these tasks.

Examining job tasks

The initial step is to compile a list of all tasks that the job role entails. It’s advised to be as detailed as possible during this phase to avoid overlooking any crucial tasks, which could impede subsequent steps in the job analysis process.

For instance, Patterson and colleagues (2008) detailed core competencies for various hospital specialists, establishing a solid, scientifically-based selection criterion for specialisation. 

Through detailed job analysis, they observed differing skill requirements among specialists. 

For example, paediatricians (doctors dealing with children) may need to adjust their communication style from adult to child, while anesthesiologists may need to articulate their intentions and explain their actions to various team members (e.g., surgeons and support staff). 

Understanding the precise job tasks enables us to refine our hiring process effectively.

Categorising job tasks

The next step involves assigning scores for the most crucial tasks of a position in different scales. For example, Matthes and colleagues (2014) recommended assigning scores for job tasks in a position in 5 scales, which included whether the tasks require a more interactive or analytic skill; whether the tasks are more (non-) routine or need more autonomous initiative; and whether the tasks require physical effort (see Figure 1). Once all crucial tasks are scored, a job profile can be created, indicating the types of tasks individuals in the role frequently handle (see examples in figure 2). 

 
Matthes and colleagues (2014)

Fig 1. Adapted from Matthes et al., 2014

 

Matthes et al

Fig 2. from Matthes et al., 2014

 

Deriving the critical skills

Before establishing hiring criteria, it’s essential to select the most critical skills to evaluate.

For instance, in Figure 2, software developers and analysts commonly perform analytic and autonomy tasks. Consequently, the top two critical skills for hiring a software developer could be strong cognitive skills for analytic tasks and behavioural traits that foster self-motivation for autonomy tasks. 

Other skills can be listed as “nice to have,” as filtering out potential candidates solely based on these non-critical skills in the initial phase is undesirable. For instance, a candidate with lower physical capabilities but possessing adequate cognitive skills and suitable behavioural traits may still excel in a software developer role.

All in all, conducting a job analysis provides a better understanding of your open job role and enables you to design hiring criteria more effectively, leading to a more efficient hiring process. 

To conclude…

When implementing skill-based hiring, it’s crucial to not only have a general understanding of the skills needed for various broad occupation groups but also to recognize that other factors can influence job requirements. Specifically, the industry we operate in and the labour strategies we employ may impact the skills necessary for new hires. Therefore, a more effective approach to developing or adjusting job profiles to meet our needs is through thorough job analysis, which involves examining all job tasks, categorising them, and deriving critical skills from these task dimensions. Happy hiring! 🙂

References

Bhattacharya, M., Gibson, D. E., & Doty, D. H. (2005). The effects of flexibility in employee skills, employee behaviors, and human resource practices on firm performance. Journal of management, 31(4), 622-640. https://doi.org/10.1177/0149206304272347 

Doherty, O., & Stephens, S. (2023). Hard and soft skill needs: higher education and the Fintech sector. Journal of Education and Work, 36(3), 186-201. https://doi.org/10.1080/13639080.2023.2174954 

Gonzalez G. Robson S. Phillips A. Hunter G. P. & Ortiz D. (2015). Energy-sector workforce development in west virginia : aligning community college education and training with needed skills. RAND Corporation.

Handel, M. J. (2016). What do people do at work?. Journal for Labour Market Research, 49(2), 177-197. https://doi.org/10.1007/s12651-016-0213-1 

Huang, A. Y., Fisher, T., Ding, H., & Guo, Z. (2021). A network analysis of cross-occupational skill transferability for the hospitality industry. International Journal of Contemporary Hospitality Management, 33(12), 4215-4236. https://doi.org/10.1108/IJCHM-01-2021-0073 

Kavanagh, M. H., & Drennan, L. (2008). What skills and attributes does an accounting graduate need? Evidence from student perceptions and employer expectations. Accounting & Finance, 48(2), 279-300. https://doi.org/10.1111/j.1467-629X.2007.00245.x 

Krzywdzinski, M. (2017). Automation, skill requirements and labour‐use strategies: high‐wage and low‐wage approaches to high‐tech manufacturing in the automotive industry. New technology, work and employment, 32(3), 247-267. https://doi.org/10.1111/ntwe.12100 

Kuchciak, I., & Wiktorowicz, J. (2020). Individual Determinants for the Transfer of Knowledge in the Financial Sector. Human Resource Management/Zarzadzanie Zasobami Ludzkimi, 133(2). http://dx.doi.org/10.5604%2F01.3001.0014.0734 

Lyu, W., & Liu, J. (2021). Soft skills, hard skills: What matters most? Evidence from job postings. Applied Energy, 300, 117307. https://doi.org/10.1016/j.apenergy.2021.117307 

Matthes, B., Christoph, B., Janik, F., & Ruland, M. (2014). Collecting information on job tasks—an instrument to measure tasks required at the workplace in a multi-topic survey. Journal for Labour Market Research, 47(4), 273-297. https://doi.org/10.1007/s12651-014-0155-4 

Patterson, F., Ferguson, E., & Thomas, S. (2008). Using job analysis to identify core and specific competencies: implications for selection and recruitment. Medical education, 42(12), 1195-1204. https://doi.org/10.1111/j.1365-2923.2008.03174.x 

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