Unemployment

Posted: January 4th, 2023

Unemployment

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Unemployment

 Unemployment is a pervasive global problem that has challenged government, organizations, and communities since the advent of industrialization. With paid labor being a source of livelihoods for many individuals and families, unemployment is a continuing hindrance to the sustainability of million across the world. According to the World Bank and the International Labor Organization, the global unemployment rate stood at 5.397% after decreasing marginally from a high of 6.189% in 2003, with 188 million people being unemployed in 2019 (International Labor Organization, 2020); The World Bank Group, 2020). At the same time, it stood at 5.2%, 6.7%, and 3.9% among the OECD and European Union member countries, and the United Kingdom, respectively. Unemployment is a grand challenge that has recently dominated the news and media reports because of the debilitating effects of the ongoing Covid-19 pandemic, which has seen the economic activities grind to a near halt. With many workplaces closed to counter the spread of coronavirus and calls to stay indoors prevail, many people are out of employment, with a global unemployment crisis looming if the situation persists. 

Although the attainment of full employment in which everyone who desires a job can get one is highly desirable, it will remain elusive because of the complexity of unemployment. The complexity emanates from the close relationship with political, economic, social, technological, legal, and environmental factors that influence the labor market dynamics. In addition, unemployment rates vary over time and are related directly to poverty, crime, mental health challenges, particularly when they reach critical levels (Blustein, Medvide, & Wan, 2012). System-based methodologies provide a critical systems approach that can be used to address the complex grand challenge of unemployment, particularly in the United Kingdom, using complex problem solving mechanisms (Dörner & Funke, 2017). A causal loop diagram is used to conceptualize the unemployment problem, while systems dynamics and soft systems are the system-based methodologies that can be used complementarily to address this grand challenge.   

Causal loop diagram

The causal loop diagram (figure 1) identifies the main variables in the unemployment challenge and their interrelatedness. According to the diagram, unemployment opportunities, business creation, competition, and business destruction are the most critical variables associated to the unemployment problem. In one loop, the increase in unemployment causes more businesses to be created to increase employment opportunities, thus absorbing the unemployed labor force. However, when all the employment opportunities are not taken up by the labor market, unemployment persists. This loop is reinforcing because the increase in one variable cause an increase in the others, as illustrated in figure 1. In the second loop, the creation of more businesses causes increased competition, which upon reaching critically high levels, causes some businesses to close down when they cannot survive. Unfortunately, the destruction of some businesses reduces employment opportunities causing the unemployment levels to rise. This loop is reinforcing because the variables need to be in balance towards an equilibrium that avoids the unemployment rates reaching critical levels, as illustrated in figure 1.

Figure 1. Causal loop diagram for unemployment

However, each variable represented in this diagram is influenced by a complex array of political, economic, social, technological, legal, and environmental factors. Specifically, business creation depends on the political environment in a country, which is informed by the economic environment therein. In this respect, a government that creates a conducive political environment that supports business creation through stable, predictable, and progressive policies reduces the levels of unemployment in a country. In the same vein, business creation results from investments by entrepreneurs, which are influenced by the economic conditions in a country and around the world. However, economies go through cycles of booms and busts, which make the level of investments into new businesses to fluctuate from time to time. The economic policies by government and the level of enforcement by government agencies, alongside the willingness of financial institutions to advance credit to investors, are critical considerations that influence the number, type, and timing of new business ventures. Similarly, the businesses created need to create employment opportunities that match the needs of the labor market, which is significantly influenced by the skill availability, wage levels, and the skill-job fit in the labor market. Therefore, the country’s training programs must develop the skills that are demanded by the job market to enable people to take up the employment opportunities that are created. Many times, the skill-sets in the labor market lag behind those needed in the emerging workplaces, thus making many people unemployable. 

In the same vein, the competitiveness among businesses is influenced by the number of businesses in the different industries, their diversity and concentration, which are influenced by customer demands as the critical social factor. Moreover, competition can occur on unfair environments that promote uncompetitive behaviors such as creation of monopolies, weak intellectual property rights protection, and excessive focus on profits at the expense of the wellbeing of communities and the environment. In this respect, law and regulations, alongside government policies, play a critical role in regulating competition and promoting a conducive environment for new startups to thrive.

System-Based Methodologies

System Dynamics Methodology

System dynamics is a methodology that can contextualize unemployment through the complex feedback systems lens. Specifically, systems dynamics helps in learning about complex problems by explaining the nonlinear behavior of complex systems. It presents feedback, stock and flow, delay, and nonlinearity of diverse interrelated components comprising the complex system that influence the complex problem (Ouyang, 2014). 

The system surrounding employment is complex, but when described simply, it involves employers and businesses. Using a causal loop diagram, such as the one presented in figure 1, the variables involved in the employment system are identified, and their interrelations and interactions defined. The methodology identifies the positive (reinforcing) and negative (balancing) feedbacks that result from the interaction between variables. In this regard, new businesses create employment opportunities for the jobless, thus lowering lower unemployment. However, it no new businesses are created, job opportunities are not expanded, and consequently, unemployment persists. Contrastingly, although new businesses absorb the jobless in society, they are subjected to competition, which may endanger their survival. In the event that the competition is very fierce as to limit profitability, the most afflicted businesses may close down and retrench employees, which may cause unemployment to rise. Since these feedbacks are presented simultaneously, they differ in occurrence and strength. To add a quantitative dimension to the unemployment dynamics, a stock and flow analysis is done to quantify the number of the unemployed at any given time and the flows in the labor market in a given country. The labor market is the stock from were employed and unemployed people are converted from one status to the other. The effects of change in the quantitative values of the variables differ across time intervals such that a change in one variable leads to a delayed response in another variable (Layton, 2012). In this case, creation of new businesses many created new employment opportunities. However, the job vacancies may take time to be filled if the skills lack in the labor market, which in turn, would have a delayed effect on unemployment levels. However, many social problems have variables that lack linearity. In this regard, although the formation of new businesses would absorb the jobless people, their rate of formation would not translate proportionally to a similar reduction in unemployment. In this case, system dynamics can be used to address the creation of new businesses as a critical aspect in addressing unemployment, as has been explained.       

Soft Systems Methodology  

The soft systems methodology injects a soft rather than the hard approach to problem conceptualization used in the systems dynamics methodology. Rather than approach the complex problem objectively and quantitatively, the soft systems methodology focuses of the people’s perceptions instead. The methodology recognizes that complex problems are perceived differently by different people and proposed solutions are often met by lack of consensus. Moreover, this methodology acknowledges that that many problems in society are unstructured, uncertain, unclear, and unbounded. Also, may people may not recognize the existence of the problem unless they are situated in it or have experienced it before. Moreover, by identifying the different players and their perceptions of the problem, the soft systems methodology encourages the stakeholders to examine their perceptions and their interconnectedness with those of others and the meaning that they attach to different solutions.

Unemployment fits the kind of problem that can be addressed by the soft systems methodology because its perception varies across people, based on their experiences. For instance, an individual who takes up any job regardless of the wage may view joblessness differently from an engineer who cannot find work that pays at the expected level. The perceptions of the solutions to unemployment will differ between these two individuals. For instance, while the minimum wage individual may blame overpopulation and the lack of commensurate creation of companies, the engineer may blame the poor performance of the industry and the subsequent inability to offer high salaries. For the two, reskilling and upskilling would be perceived differently as solutions for combating unemployment. This method can be used to investigate the phenomenon of underemployment as an aspect of unemployment.   

Critical reflections of the strengths and weaknesses of the system-based methodologies

Strengths

Systems dynamics provides an interdisciplinary approach that can be used to address the sustainability issues in a complex challenge. It also provides a holistic view of addressing the economic, social, and environmental aspects of the complex issue (Pan, Valerdi, & Kang, 2013). In addition, systems dynamics facilitates the learning about behavior of complex systems by facilitating knowledge acquisition. In this regard, systems dynamics uses causal mapping to identify and test policy options and decisions before they are applied in real life (Currie, Smith, & Jagal, 2018). This is possible when the large amounts of available data are used to developed evidence-based realistic models for understanding the interactions among subsystems (Helbing, 2013). For instance, Ahmad and Kustiwan (2019) and Bernado and D’Alessandro (2016) applauded the methodology for facilitating learning about complex systems associated with complex problems such as poverty and employment. In this respect, it provides a framework for identifying and analyzing the problem, and formulating and evaluating policy for addressing the problem (Ghaffarzadegan, Lyneis, & Richardson, 2011). 

Similarly, the soft systems methodology captures the subjective viewpoints often missed by other methodologies (Ghosh, Roy, & Sanyal 2016). It helps situate the complex problem in political contexts, thus facilitating the development of solution that move beyond technicalities. Moreover, it focuses on stakeholders, who are often left out in other system-based methodologies, thus supplementing the hard systems approach (Midgley et al. 2013; Wang, Liu, & Mingers, 2015).

Weaknesses

Systems dynamics is highly dependent on data, which may be unavailable. Besides it is a time-intensive exercise that involves the identification and definition of all the components comprising the subsystems, which constitute the complex system (Torres, Kunc, & O’brien, 2017). This requires diverse knowledge about the system and the problem, which often lacks or is not possessed by one individual (Fazey et al., 2014). Likewise, the soft systems methodology does not address the building of systems and may offer suboptimal solutions if the stakeholders are not sufficiently knowledgeable about the complex problem (Checkland & Poulter, 2018). 

Ideas of improving the grand narratives

Addressing education to bridge the gap between labor skills and demand and improve the skills-job fit is pertinent to address unemployment in the technological age (Peters, 2017). In addition, unemployment is increasingly becoming an inevitable phenomenon as population increases and economic downturns become more severe due to unprecedented events associated with adverse weather and global epidemics, like the ongoing coronavirus pandemic (Blustein, Kozan, & Connors-Kellgren, 2012; Farr, 2020). In this respect, the grand narrative should move away from eradicating unemployment to building sustainability and resilience in the labor force to make it adaptable to such unpredictable eventualities. To this end, a combination of hard and soft system-based solutions would deliver more holistic solutions that are viewed by the afflicted population as such. This would reduce the perception from the unemployed individuals that the current interventions are elitist and irrelevant, and impractical.

Conclusion

Unemployment is a pervasive complex problem that is difficult to address because of its interrelatedness to a wide variety of issues related to politics, society, economy, technology, environment, and law. System-based approaches like system dynamics and soft systems methodologies provide a comprehensive and diverse view of complex problems by using hard and soft system approaches, which are complementary. These approaches would help direct the grand narrative towards resilience and sustainability in addressing unemployment.     

References

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