How to measure job satisfaction: Single or multi-variable construct?

The term job satisfaction has been defined as a single construct that measures how people feel about their jobs and also as a multi-dimensional construct that includes the variations in feelings towards various aspects of a job.

Herzberg differentiated between these aspects by segregating them into extrinsic factors, those associated with the job environment, and intrinsic factors, those which were part of the job itself. This distinction into a multi-variate entity is important for job satisfaction as defining it as a single construct limits its usability.

Consider for example, Marks and Spencer’s annual employee engagement survey revealed that 81% of its employees feel proud to work with the company (Marks and Spencer, 2018, p. 17). This figure in itself is quite impressive, however, it leaves several questions unanswered:

• Why is there a fall of 1% from the last year’s figure?
• What factors are causing the remaining 19% employees to not feel engaged?
• What is the company doing right to make the rest of its employees committed?

It is evident that measures of job satisfaction, motivation, and employee engagement are best explored as multi-variable constructs in order to grasp the complexity of modern work environments.

There is a caveat to this statement as demonstrated by Heritage, Pollock and Roberts (2015). These researchers have reported that job satisfaction is best estimated as a hierarchical three-factor model, however, all three factors have a high degree of correlation. This makes the use of a multi-factor model untenable and has prompted the researchers to recommend an overall score as a better and more robust measure of job satisfaction.

Job satisfaction is lower for contingent workers

Wilkin (2013) conducted meta-analysis of 72 studies on jobs satisfaction and reported that contingent workers have lower job satisfaction than permanent workers. This difference shows that organizations that employ many contingent workers will benefit by paying more attention to extending good HR practices to this group as well.

 Loher et al. (1985) explored the relation between job satisfaction and job characteristics and found that Growth Need strength acts as a moderator between them. This result implies that people who are high on the growth need strength have a higher degree of correlation between their job satisfaction and job characteristics. The characteristics considered in this study included

• skill variety,
•  task identity,
• task significance,
• autonomy, and
• feedback;

All factors are associated with the task itself rather than the work environment. 

Job Satisfaction and Outcomes

Recent evidence points to stronger individual job performance links.

Job satisfaction has largely been associated with lowering of absenteeism and employee turnover but its relationship with productivity was more complex. Productivity will increase if the employees are satisfied with their jobs and the work environment, but mere satisfaction with the work environment will not translate into a better performance.

In a meta-analysis of 74 studies, Iaffaldano and Muchinsky (1985) had reiterated that the relation between job satisfaction and performance remained the same low in correlation (r is .14) as estimated by Vroom (1964). However, Alessandri et al. (2017) studied the relation between job satisfaction and performance of 1004 employees over five years. They found that not only does satisfaction lead to better job performance, job performance itself can contribute to satisfaction.

What else is known about this relationship? Ziegler et al. (2012) have reported that employees who have low ambivalence towards their jobs, that is, employees who are indifferent about the positive and negative aspects of their jobs are more likely to improve their performance if satisfied than others. This evidence suggests that employees who have high ambivalence in either direction, positive or negative, will not show as much of a change in performance when satisfied.

Job satisfaction improves revenue and profitability

A recent study has linked job satisfaction with organizational outcomes of return over assets, operating margins, and revenue per employee in 475 firms (Melián-González, Bulchand-Gidumal and González López-Valcárcel, 2015). The researchers reported that when employees were satisfied with their leadership, pay, and work life balance, organizational performance improved.

Job satisfaction improves engagement and organizational performance

Another study has reported that job satisfaction improves employee engagement which, in turn, improves the organizational performance (Al-dalahmeh, Khalaf and Obeidat, 2018). Therefore, recent evidence shows stronger support for job satisfaction and its impact on organizational outcomes.

Job satisfaction differs for Generations Y and Z.

One aspect of job satisfaction that has remained relatively unexplored is its effect on different generations of workers. Generation Y has been working in the industry for several years now and it is the turn of Generation Z, people born from mid-90s to early 2000s, to enter the workforce. This generation are digital natives, use the internet for their primary source of communication, are considered to eb impatient, agile, and more comfortable with virtual teams than real human interaction (Adecco, 2015).

A study about what motivates generation z workers reported that the work itself, relationships with colleagues, and achievement of self-goals were the most important aspects of motivation for this generation. On the other hand, factors of work-life balance, workload, and job security no longer seemed relevant.

Generation Y or the millennials, as they are popularly called, are believed to be highly educated, ethical, like working in teams, but suffer from higher levels of anxiety and neuroticism (Twenge, Campbell and Freeman, 2012; Stewart et al., 2017). SHRM reported this generation to have lower levels of job satisfaction than the generation X and the baby boomers (SHRM, 2016). Their satisfaction, when present, was attributed most to equal treatment at work, compensation, benefits, and job security. This evidence suggests that leaders may have to change their approach when dealing with employees of different generations.

Job Satisfaction and AI

AI is improving the measurement of job satisfaction.

Artificial Intelligence or AI is the hottest trend in management today. As HR practitioners apply more robotics, machine learning, and AI to routine tasks like reward management, recruitment, and even learning and development, SHRM estimates that the freeing up of time from these routine procedures will drive job satisfaction higher (Zielinski, 2018). It is believed that HR professionals will now be in a position to focus on high-value aspects of their jobs which will make them feel more satisfied with their work itself, thus improving their satisfaction. However, there is a dark side to this as well.

AI is also a riskier proposition which can easily be misused.

Research firm Gartner has reported that more than half of global companies with an annual revenue of over $750 million employed monitoring techniques for their staff (Belton, 2019). These techniques ranged from analysing their emails, online conversations, and even their computer and physical movements (called employee exhaust) to assess their performance. Though most firms claim they use this data to ensure employees satisfaction, prevention from bullying and harassment, and improve their management policies, it is evident that misuse of technology can easily graduate to oppression.

Microsoft has used AI to improve its employee job satisfaction.

In 2018, an employee survey showed Microsoft that its employees were widely dissatisfied (Romeo, 2019). The company employed AI to read through employee calendars, analysed the time spent in meetings, and also looked through transfer requests by employees. The latter were believed to show a lower level of engagement which was prompting employees to seek an internal change. The results of this analysis revealed that employees were spending unnecessary long hours in meetings which could be utilised for more productive work. Microsoft initiated policies to encourage employees to shift away from long-drawn meetings, email exchanges, and made transfer requests easier to implement believing that if employees failed to get them, they may actively look for opportunities outside. All these measures helped the company improve the employees job satisfaction.

The use of AI in human Resource policies is subject to an ethical and reflective framework which judges the pros and cons of every situation. It can definitely be an invaluable tool in assessing employee attitudes like satisfaction, but it is equally easy to fall into the big brother syndrome. The latter will forfeit all benefits of AI and can initiate a paranoia among employees which will impact their job satisfaction adversely.