One distressing challenge associated with technological change is that although a new technology may certainly bring new jobs, those new jobs typically require new or different skills that displaced workers don’t always have. In a world with increasing automation and shifting technologies, many workers will need new or upgraded skills in order to retain, regain, or improve their employment.
Moreover, the promised benefits of technologies as well as companies’ competitiveness hinge on the ability to adopt those technologies. Yet the Future of Jobs Report 2020 by the World Economic Forum found that the top three barriers to adopting new technology were skills-related: skills gaps in the local labor market; inability to attract specialized talent; and skills gaps in a company’s leadership.1 Thus, skills play an absolutely central role not only in people’s future employment but also in companies’ technological futures.
Mind the skills gaps
Although news of job losses and hot new careers make headlines, the more important story is in the broader changes to everyone’s jobs. Even if many workers stay in the same jobs with the same job titles, their jobs will not be the same. They will likely delegate to automation many of the repetitive tasks that consumed sizable parts of their time. They will see (and need to use) a growing array of timely data about both the overall environment and each task instance. They will be expected to know all the jobs that need to be done as well as to understand the technology those jobs use. They will be expected to spot deviations from normal operations that might be caused by defects in some process, or a wrong execution of some task by an algorithm, while taking into account changes in the broader environment that may necessitate an override. And they will be expected to help determine whether a potential anomaly is something to fix, a change to adapt to, or just a burble to ignore.
Even as computers exchange ever more data within the automated parts of the business in general and supply chains in particular, people will still need to collaborate with other people. The reason is that as technology marches forward, issues that require managers’ attention are likely to become increasingly rare and less familiar. Automation may also increase supply chains’ complexity. As a result, consultations and knowledge sharing among people could increase in importance.
The U.S. Government Accountability Office (GAO) used diverse government data to determine the skills that workers will need to get jobs in the future. To do this, the agency’s researchers analyzed the skills required for different jobs as well as the expected growth for various jobs from 2019 to 2029. Next, they identified the top 20 jobs with increasing demand for three education levels (high school, some college, and bachelor’s degree or above). Finally, they tallied which skills would be needed across those high-growth jobs for each education level.2
The GAO’s research identified a baseline set of eight skills needed by everyone, regardless of education level. In Figure 1, these are listed under the “high school” category.
People seeking in-demand jobs that require some college or more (including those with bachelor’s or advanced degrees) will need those first eight foundational skills as well as five additional important skills, shown under “some college.” And finally, those seeking in-demand jobs that require a bachelor’s or an advanced degree also typically need a further set of six skills in addition to all those required for jobs with lesser levels of education. These are listed under “bachelor’s and above.”
Many of the skills mentioned in this framework are not things that are taught in standard school curricula. For example, because many simple, repetitive, blue-collar and white-collar jobs are likely to become more automated, more people will be working in service positions. These service jobs will demand a greater emphasis on social skills. However, being more social (or, one could say, more human) is not a formal subject in most schools, even though it is an essential strategy for people in an era when machines can perform more and more of the physical and mental labor that underpins the economy. Ensuring that the workforce has the above-mentioned skills may involve different approaches to education and training.
Future of service work
As mentioned above, service work, which involves significant interactions with customers as well as with team members, will play a major role in the future economy. In fact, many of the skills listed in Figure 1 are applicable to service work. It is unclear, however, what the future of service work will be. The number of service jobs may decrease or increase due to several countervailing trends; some may lead to a reduction, while others may lead to an increase in such jobs.
Three trends can potentially decrease the number of human service workers. First, many companies are automating a growing percentage of routine services, thereby eliminating human work from many interactions. For example, McDonald’s is testing several types of automation, including apps, voice recognition, and self-service kiosks for ordering, and is even testing conveyor-belt delivery of orders at drive-through windows. Another example is chatbots, such as those used by many retailers and auto dealers for communicating with customers when they call or search their website for information. Second, for non-routine tasks, service workers will benefit from new tools … that improve their productivity and reduce the number of people required to handle a given volume of interactions. Third, a growing number of smart products and smart services will include high-reliability, plug-and-play functionality with self-configuring, auto-updating, self-repairing features, which may eliminate more jobs.
At the same time, four trends could drive a need for more human service workers. First, as many consumer products grow in sophistication and involve greater degrees of interconnection (in-home automation; self-driving cars; or seamless, device-to-device hand-offs, for instance) consumers will almost certainly need more assistance in setting up, configuring, and troubleshooting these complex systems. Second, even as supply chains are becoming more complex, companies are confronting increased expectations to provide first-rate service, competitive performance, social and environmental sustainability, and resilience while also facing higher levels of regulation, volatility, uncertainty, complexity, and ambiguity (VUCA). The constant system updates and reconfigurations that will be necessary to respond to such changing conditions may increase the need for people in service positions. Third, the aging demographics of many countries means a growing population of older consumers who will require more intensive services for both health care and daily activities. Fourth, growing wealth created by the winner-take-all financial returns for information products and services will create a larger subset of affluent consumers who may seek, and be willing to pay for, high-touch human experiences.
How these two categories of trends combine to create either a net increase—or decrease—in the number of service workers remains to be seen. The GAO’s analysis of the top 20 growing occupations shows high growth in personal-service occupations, primarily in the health care arena.3 Customer service may bifurcate between low-cost automated services and high-touch human-focused services, such as “white glove” services that will deliver, install, and help train consumers in how to use complex, interconnected products. However, to the extent that automation cannot handle a customer’s or supplier’s issue, these non-routine interactions will require a human worker’s emotional intelligence to recognize and empathize with what the other person is experiencing and wanting.
Digital literacy and numeracy
Massive amounts of data in multiple forms, advanced artificial intelligence (AI), and widespread access to cloud platforms bring new opportunities for managing supply chains. Companies will be able to use A/B testing (a method of comparing two versions of a product or solution to determine which performs better) and rigorous analysis of natural patterns in the data to augment subjective intuition. Also, many mathematical models developed decades ago to efficiently manage supply chains are still not widely implemented, even though advances in mathematics and computing made them only more powerful. However, reaping the benefits of this huge opportunity depends on a workforce (and management team) with a strong understanding of data, technology, and analysis.
“Digital literacy” is a foundational skill that can be defined as the ability to navigate various digital platforms and understand, assess, and communicate through them. Fortunately, most children are becoming digital natives. More than three-quarters of children in the U.S. have a smartphone by the age of 13. Moreover, the COVID-19 pandemic and the switch to remote schooling in many regions forced many children to adopt digital tools for learning and communications. Of greater concern is digital literacy among middle-aged and older workers; many of them use smartphones, tablets, and computers, but they may be among those most in need of re-skilling if they lose their jobs to automation.
That’s because the basic skill of operating a smartphone, tablet, or PC, while necessary, is not sufficient. As more and more work uses data-driven approaches, workers and managers need more numerical literacy, which is the ability to use and understand mathematics, as well as statistical literacy, which is the ability to understand and reason with data and statistics. Seeing the data on a smartphone is one thing, but understanding the implications of these data and taking the right action in response is entirely another. Workers and managers need a good understanding of relevant mathematical models, data analytics, and the power and limitation of technological tools. Having both digital literacy and numeracy can radically improve the workplace and the roles of frontline workers. With new tools for gathering and analyzing data, they will be capable of identifying problems and will be empowered to take action in response.
New management skills
To better handle the growing complexity of supply chains, managers will need such advanced skills as systems evaluation and systems analysis. They will need to know how to integrate advanced supply chain tools—such as the Internet of Things (IoT), robots, self-driving vehicles, mathematical models, and AI—with their human workforce, and they will have to define the role of humans in highly automated supply chains. Managers will also need to be able to forecast workload patterns and understand the productivity of their technology-augmented workers. With this knowledge, they will be able to forecast the resource levels (people + technology) required to handle any load and stay within expected service requirements, such as availability and lead time.
Leslie Willcocks, professor of technology, work, and globalization at the London School of Economics’ Department of Management, predicts, “The evidence is that it’s not whole jobs that will be lost but parts of jobs, and you can reassemble work into different types of jobs.”4 This observation suggests that managers will also need to consider how automation will change what each worker does, and then decide how the activities of the organization and job tasks should be divided among various people and machine systems.
The “systems” skills requirements also imply that managers must have some understanding of all the technologies being used by their department, and even those of the departments or outsiders with whom the manager’s workers must interact. In particular, managers should understand the strengths and weaknesses of these technologies in order to properly deploy them and to manage appropriate “human-in-the-loop” systems. They also must understand the types of mistakes these systems can make, so they can ensure that their people know when to trust the technology they use, when to override it, and when to bring a gray area to the attention of managers and experts.
Most importantly, managers need these skills to create human-machine collaborations with the necessary interoperability, authority balance, transparency, and mutual learning. These skills will help them design and manage human-in-the-loop systems using the available staff, automated systems, and internal and third-party digital tools. For example, does the AI check the human’s work for errors or anomalies? Does a human check the AI’s work? Or do both people and AIs cross-check each other in a kind of consensus system? And if errors and anomalies happen too often, does the organization retrain the system, the humans, or both?
Adaptability, learning, and change management
Adopting automation in an organization or a supply chain is not a one-time event but a progressive process driven by lessons learned during usage, by changing needs, and by ongoing updates to all the technologies and the processes involved. The requirements of continuing adaptation and organizational changes may seem to run counter to an organization’s overarching operational goal of maintaining smooth and stable supply chain operations. Such operations depend on predictable, consistent performance by the people and the technology in the supply chain to create smooth deliveries of products and services. However, that does not mean that change is something to be avoided. As Charles Darwin purportedly said, “It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change.” Although this quote seems to appear nowhere in Darwin’s writings, it captures an important principle that is as applicable to supply chains as it is to evolution: Change is a necessity for organizations to survive.
Agile adjustments in complex systems, such as supply chains, cannot be made without understanding all the elements of the system and how they interact with each other. The complexity of supply chains means that almost every action has far-reaching and wide-ranging ramifications and often has unintended consequences. Even in the case of significant supply chain disruptions, when people throughout the organization spring into action, they have to be methodical about carrying out the actions needed to rectify the problems and get the supply chain going again. Of course, during a disruption everybody wants to help, but quick and unplanned actions can make the situation worse. Thus, adaptation and change are a necessity, but when dealing with systems as complex as supply chains, changes have to be made with a deep understanding of the entire system and its intricacies.
In a world of increasing uncertainty, supply chain workforces must be creative and adaptable—able to step quickly into situations that automation cannot handle as readily. All workers will need skills such as monitoring, critical thinking, judgment, and decision-making so they can promptly spot and correctly respond to problems that arise. These problems can be the result of anything from a machine error to a change in the objectives of the organization. They can also be the result of a change in the operating environment or a customer request that goes beyond what the machine was programmed or trained to do. Furthermore, workers in most high-skill positions will need active learning and complex problem-solving skills to stay on top of variations in their job, their field, their company’s strategy, or the direction of their industry.
Supply chain professionals continuously interact with people both inside and outside their organization, so they need good communication, relational, negotiation, and persuasive skills. But it is likely that all workers will need significant social, digital, cognitive, and management skills. In fact, the previously referenced World Economic Forum report estimated that about 40% of the core skills required, even for workers who will remain in their existing roles, will change by 2027.5 The challenge, then, is to build and improve people’s abilities and create opportunities for them to quickly acquire the skills they need to enter, remain, and advance in the future workforce.
[THIS EXTRACT FROM THE MAGIC CONVEYOR BELT: SUPPLY CHAINS, A.I., AND THE FUTURE OF WORK BY DR. YOSSI SHEFFI ©2023 IS REPRODUCED WITH PERMISSION FROM MIT CTL MEDIA. FOR MORE INFORMATION, GO TO HTTPS:SHEFFI.MIT.EDU/MAGICBELT.]
1. World Economic Forum, “The Future of Jobs Report 2020,” (October 20, 2020), 35: https://www.weforum.org/reports/the-future-of-jobs-report-2020/digest
2. U.S. Government Accountability Office, “Workforce Automaton: Insights into Skills and Training Programs for Impacted Workers,” Report to Congressional Committees, (August 2022), 14: https://www.gao.gove/products/gao-22-105159
3. U.S. Government Accountability Office, “Workforce Automation: Insights into Skills and Training Programs for Impacted Workers,” 38–49.
4. Leslie Willcocks, “The value of robotic process automation,” interview by Xavier Lhuer, (March 1, 2017): https://www.mckinsey.com/industries/financial-services/our-insights/the-value-of-robotic-process-automation
5. World Economic Forum, “The Future of Jobs Report 2020,” 38.