The company chosen for the scenario is the BMW group. It is a giant multinational corporation that has its offices and facilities in numerous regions all over the world. It is headquartered in Munich, Bayern. BMW is a profit organization working in the heavy industry sector. At the moment, the company is one of the biggest car manufacturers in the world with 2,279,503 vehicles produced (Company n.d.). Today, its basic products are high-quality cars created with the use of outstanding technologies and the implementation of innovative techniques. BMW offers middle-class and luxurious vehicles for customers who are interested in reliable, fast, and attractive cars and motorcycles. Additionally, it provides maintenance and support services to all clients. Its main customers could be found in numerous states characterized by high and stable income. The company is focused on continuous improvement and the use of automation.
In general, automation is not a new issue that impacts modern industry. The first fears about workers losing their jobs appeared in the age of the Industrial Revolution in the 18th and 19th centuries because of the massive use of machines and new ways of production with the primary aim to reduce costs and increase the efficiency of particular plants (McKinsey&Company 2017). It resulted in the cheapening of labor and job cuts (Torraco 2016). Since that time, the concept has always remained topical. The development of continuous-flow production and the creation of the new assembly line by Ford in 1913 introduced new threats to workers and their jobs as unskilled workers acquired an opportunity to perform all functions and replace expensive and experienced ones (Frey & Osborne 2017). Broad electrification became a new stage in the development of the concept of technological unemployment as it gave rise to numerous technologies and triggered the industrial revolution in offices (Frey & Osborne 2017). In 1960, the National Commission on Technology, Automation, and Economic Progress investigated the problem because of the numerous concerns related to technological unemployment. It concluded that the use of innovations might destroy jobs, but not work (Frey & Osborne 2017). However, the computer revolution of the1960s and the rise of their commercial use reconsidered the approach to numerous occupations and created a new working environment (Peters 2017). The further decline in the price of computing and its maintenance resulted in drastic changes in the labor market and the growth of new concerns related to technological unemployment (Bennett 2016). Now, in the 21st century, we could observe the continuation of the rapid rise of technologies and significant computerization of all spheres of human activities (Bennett 2016). The development of science humanity has never witnessed before, and the implementation of new methods contribute to the increased importance of automation and fears related to future cuts and growing unemployment (Decker, Fischer & Ott 2017). Altogether, the evolution of the concept of technological unemployment could be presented in the following way:
Nevertheless, at the first stages of the scientific revolution, machines and innovative devices were not considered a significant threat to the existing labor market (Qureshi & Syed 2014). However, since the introduction of second and third generations of computers in the 1950s, the situation has been altering (David 2017). The fact is that the significant development of robotics and the production of robots is part of computerization peculiar to our world (David 2017). For this reason, the most developed countries are the first the face challenges presented by automation and technological unemployment associated with it (Pulkka 2017). For instance, Japan known as the leader in innovations and robotics introduced assembling robots in the 1960s and mobile robots in the 1980s (David 2017). Acknowledging diverse benefits arising from the development of this technology, the country cultivated further sophistication and production of robots by developing micro-technologies and using machines in different spheres. As a result, today Japan is the most innovative state that, however, faces the problem of massive computerization of industry. In accordance with particular reports, in the future 55% of actual jobs might be at risk of being eliminated and non-regular workers will be endangered (David 2017).
Moreover, the speed of technologies development and their rise is still increasing which means that even more sophisticated algorithms will appear and be used in different industries or services (Frey & Osborne 2017). Workers are the first to suffer from this process as numerous jobs in manufacturing, logistic, transportation, and other spheres will disappear (Frey & Osborne 2017). Analyzing this situation, Frey and Osborne create their list of occupations that might suffer from the tendency towards automation and the further rise of digital devices. For instance, the sphere of routine and non-cognitive tasks will obviously experience significant shifts in its structure because of the wide use of robots and technologies to improve outcomes and minimize the negative impact of the human factor (Frey & Osborne 2017). Additionally, many service or assembly line workers might also lose jobs.
In such a way, the attitude to the concept of technological unemployment is not obvious. Some research works state that the implementation of technologies will result in the further development of society and the emergence of new industries that will provide workers with jobs (Loi 2015). However, there are still numerous risks that should be considered.
Application of Frey and Osbornes Findings
The investigation of the phenomena of technological unemployment and automation could be supported by the analysis of the selected company to demonstrate how the use of innovative devices and approaches might impact its functioning and what changes in the companys structure of the workforce might be expected. Thus, BMW at the moment is one of the leading companies manufacturing vehicles for middle and upper-class customers. It means that to be competitive and preserve its positions, the corporation has to continue the mass implementation of technologies that will help it to remain beneficial (Dirican 2015). Diverse research works devoted to the issue show that organizations giving much attention to automation and computerization turn out to be efficient and successful than their rivals (DeCanio 2016). Correctly realizing the importance of this process, BMW will obviously continue computerization and automation of its fundamental activities to preserve its current status. For this reason, a particularly low-impact scenario could be applied to the company.
Using the scale suggested by Frey and Osborne (2017), we can distinguish several jobs in BMW that are at risk of being replaced by technology. The highest percentage is demonstrated by the engine and other machine assemblers (82%) (Frey & Osborne 2017). It is quite logical as the modern devices and robots could perform their functions demonstrating a high level of performance and a significant reduction in mistakes usually preconditioned by the human factor. Moreover, the process of engine assemblers replacement has already started as BMW uses specified assembly lines to manufacture its engines (Company n.d.). Nevertheless, at the moment, the company has about 124, 729 employees in different countries (Employees n.d.). About 40% of them are assemblers which means that 49,8916 people are at high risk of being replaced by robots or new technologies that are implemented on a daily basis (Employees n.d.). Even considering the fact that the process of employees change will be gradual as it is impossible to dismiss the bigger part of the stuff instantly, the changes in the companys structure will be drastic. First, the significant decrease in remaining workers motivation will be observed as they will be aware of technological unemployment and risks related to automation (McClure 2017). Second, the majority of assembling processes will be performed by robots which will minimize the probability of mistakes and ensure high-quality final products (Pulkka 2017). Third, the company might face social dissatisfaction because of the cuts in jobs (Peters 2017). For this reason, it will have to engage in specific social projects to support communities (Chace 2016). Finally, a massive reduction of workers will stipulate the reconsideration of the approach to facilities allocation because of the absence of the need for a cheap workforce and decreased significance of its outlets (Qureshi & Syed 2014). That is why its plants in China, India, and Indonesia might be closed to minimize spending.
Electro-mechanical and motorcycle technicians are another group of workers that are at high risk of being replaced in accordance with Frey and Osbornes scale (81% and 79% correspondingly) (Frey & Osborne 2017). It will also impact BMWs functioning significantly. As assembly workers, this category plays an important role in the manufacturing of products the company provides to its customers. For this reason, they comprise a significant part of its workforce (about 13,000) (Employees n.d.). Their replacement with robots will result in the appearance of the new working environment and the further development of automation. Additionally, the company will significantly reduce spending on their salaries and will acquire opportunities for running new projects (Slack, Brandon-Jones & Johnston 2011). These new ventures might result in the appearance of workplaces for workers substituted by technologies.
Finally, cutting, punching, and press machine setters, operators, and tenders, metal and plastic could be replaced (78%) (Frey & Osborne 2017). These comprise about 8,000 of all employees working for the company (Employees n.d.). In other words, 8,000 workers could be dismissed in several stages to implement innovative technologies and guarantee the increased efficiency of several processes.
Considering this information, we can assume that BMWs functioning will alter significantly as the bigger part of its employees will be replaced by robots and computers that will demonstrate a higher level of performance and contribute to better outcomes (Zuzanek & Hilbrecht 2016). The company might concentrate production in highly-developed states to ensure further automation.
Altogether, the attitude to technological unemployment remains contradictory. The mass use of robots and computers will apparently cut routine and non-cognitive jobs and deprive individuals of their working places (Wall 2018). However, some researchers assume that instead new jobs will be created to support the further evolution of society (Vogel 2015).
Bennett, J 2016, ‘Skill-specific unemployment risks: employment protection and technological progress – a cross-national comparison’, Journal of European Social Policy, vol. 26, no. 5, pp. 402-416.
Chace, C 2016, The economic singularity: artificial intelligence and the death of capitalism, Three Cs, New York, NY.
David, B 2017, ‘Computer technology and probable job destructions in Japan: an evaluation’, Journal of The Japanese and International Economies, vol. 43, pp. 77-87.
DeCanio, S 2016, ‘Robots and humans – complements or substitutes?’, Journal of Macroeconomics, vol. 49, pp. 280-291.
Decker, M, Fischer, M & Ott, I 2017, ‘Service robotics and human labor: a first technology assessment of substitution and cooperation’, Robotics and Autonomous Systems, vol. 87, pp. 348-354.
Dirican, C 2015, ‘The impacts of robotics, artificial intelligence on business and economics’, Procedia -Social and Behavioral Sciences, vol. 195, pp. 564-573.
Frey, C & Osborne, M 2017, ‘The future of employment: how susceptible are jobs to computerisation?’, Technological Forecasting and Social Change, vol. 114, pp. 254-280.
Loi, M 2015, ‘Technological unemployment and human disenhancement’, Ethics and Information Technology, vol. 17, no. 3, pp. 201-210.
McClure, P 2017, ‘“You’re fired,” says the robot: the rise of automation in the workplace, technophobes, and fears of unemployment’, Social Science Computer Review, vol. 36, no. 2, pp. 139-156.
McKinsey&Company 2017, Jobs lost, jobs gained: workforce transitions in a time of automation, Web.
Peters, M 2017, ‘Technological unemployment: educating for the fourth industrial revolution’, Educational Philosophy and Theory, vol. 49, no. 1, pp. 1-6.
Pulkka, V 2017, ‘A free lunch with robots – can a basic income stabilise the digital economy?’, Transfer: European Review of Labour and Research, vol. 23, no. 3, pp. 295-311.
Qureshi, M & Syed, R 2014, ‘The impact of robotics on employment and motivation of employees in the service sector, with special reference to health care’, Safety and Health at Work, vol. 5, no. 5, pp. 198-202.
Slack, N, Brandon-Jones, A & Johnston, R 2011, Essentials of operations management, Prentice Hall, Upper Saddle River, NJ.
Torraco, R 2016, ‘The persistence of working poor families in a changing U.S. job market: an integrative review of the literature’, Human Resource Development Review, vol. 15, no. 1, pp. 55-76.
Vogel, P 2015, Generation jobless?: turning the youth unemployment crisis into opportunity, Palgrave Macmillan, New York, NY.
Wall, M 2018, ‘Adapt or die: how to cope when the bots take your job’, BBC News, Web.
Zuzanek, J & Hilbrecht, M 2016, ‘Enforced leisure: time use and its well-being implications’, Time & Society, Web.