Is Your Supply Chain Talent Ready for the Future?

Editor's Note: The societal and economic spasms of the early 2020s highlighted the crucial role of supply chains in the modern global economy, as well as the growing role of digital technology, including AI and automation. In this adaptation from his latest book, The Magic Conveyor Belt: Supply Chains, A.I., and the Future of Work, Dr. Yossi Sheffi of MIT’s Center for Transportation & Logistics explores how education and training must change to prepare the supply chain workforce for a technology-focused future.

Click here to listen to Sheffi on a recent episode of The Rebound. And click here to read an interview with Sheffi. 

One can think about the development of talent as a supply chain challenge, analogous to procuring raw material, going through a conversion process, and then delivering the products to the places where they are needed. The supply chains for talent have two broad goals. The first is to deliver the skills that people need to enable them to get and retain good jobs. Ensuring people have good wages and continuous employment means ensuring they have the skills required to provide value in a complex, technology-driven world. The second, and intertwined, goal is to ensure that companies have the skilled talent they need to produce affordable and valuable products and services for customers. In other words, for those companies to be efficient and productive they must have the ability to hire and employ high-performing employees. This may require re-skilling or upgrading the talent they already have.

Achieving these goals necessitates training and educating three broad categories of people. The first are existing, productive workers who need ongoing, incremental re-skilling or up-skilling to maintain a stable or improving career path. The second are displaced workers who need substantive retraining to get their next job or career. The third are young people entering the workforce who need a foundation of skills that suit both their aptitudes and the prevailing demand for human labor in the economy. Education for this spectrum of groups calls for a range of programs—from bite-sized, on-demand learning, to mid-length skill-certification programs, to updated high school, college, and post-graduate degree programs.

The Challenge of Entry-Level Employment

One critical challenge for the future of supply chain talent revolves around entry-level workers. To the extent that automation can handle all the “easy” tasks, workers with no experience and limited educational qualifications will suffer from limited job opportunities. This scarcity of entry-level jobs poses a serious problem beyond just the individual’s livelihood or the social ills associated with mass youth unemployment. If companies have no entry-level positions, then they have no way of developing the experienced workers who are needed to handle exceptions, override machines’ erroneous decisions, and operate the company if the artificial intelligence (AI) or the communications systems fail. How does a company ensure it has the needed pool of mid-level workers with five years’ experience without hiring and employing entry-level workers for five years? This problem for workers, companies, and society can be addressed in at least three ways, including one that dates back over 600 years.

The first is the apprentice system, which dates back to the Middle Ages and was the means by which young people learned a trade and were eventually given a license to practice under the prevailing guild system. In general, an apprentice agreed to provide some number of years of labor to an employer in exchange for training and room and board. The modern German apprentice system is a two- to three-and-a-half-year program that combines about 70 percent work in a company with 30 percent training in a vocational school, and provides salaries and subsidies for living expenses. Over half (54.5 percent) of German high school graduates go into this system, which covers 327 recognized occupations. About two-thirds of the apprentices then accept a full-time job with the employer that originally hired them as an apprentice.

The second is to use advanced technologies to augment the labor of entry-level workers and enable them to provide value. For example, the use of AI-enabled augmented reality (AR) allows the employment of people with limited or no experience, because they are instructed by the software to do certain tasks. AR systems integrate digital information with the worker’s physical environment in real time. Thus, for example, warehouse workers can pick items by wearing AR goggles, which allow them to see the physical environment while overlaying instructions such as which items to pick and where they are located.

Finally, AI can be used to help less experienced workers learn from more experienced, successful co-workers. For example, Udacity is a for-profit online educational organization that used AI to boost the performance of its salespeople. Udacity collected message streams of interactions between salespeople and prospective customers (including data on whether the prospect became a customer) and then fed the data into a machine learning system. Udacity used it to guide sales agents with suggested answers for common queries and interactions learned from successful agents. The system increased the effectiveness of Udacity’s salespeople by 54 percent and doubled their productivity.

New Educational and Training Models

Traditional in-person methods of educating people in groups, one classroom at a time, suffer from high costs per student and serious restrictions—all the students and an instructor must be able to come to a certain classroom, on certain days of the week, at certain times. In a technology-driven world, new models for educating more people at lower cost became both necessary and possible.

The internet opened new online channels for sending text, audio, video, and interactive education to students as well as new means of interacting with students to assess learning and answer questions. It enabled the development of massive open online courses (MOOCs) that can be taken by anyone, anywhere with internet connectivity. They are asynchronous, providing more flexibility for scheduling and self-paced learning, and many are offered for free, with certification or credentials at a very low cost. The near-zero cost of delivering digital copies of educational content and data via broadband systems enables nearly unlimited scalability. Such education systems can even use AI to automate the evaluation of students’ exercises, test answers, and essays. However, designing and producing a credible, high-quality MOOC requires considerable subject expertise and investments in time and money for production of videos, text, exercises, quiz materials, and grading systems.

The MOOC model is also changing traditional education. For example, incoming students in the residential supply chain management master’s program at MIT are required to complete an introductory MOOC that covers foundational topics, such as probability and statistics. This requirement streamlines the onboarding process and ensures that every student has the core knowledge needed for the follow-on courses. Several classes in the master’s program have borrowed the “inverted” instruction style often used in MOOCs. Students watch lectures at home, take quizzes online, and come to class ready for in-person interactions. These interactions focus on analyzing current events, case studies, or guest lectures, where students are expected to apply the principles and methods explained in the videos to the issues at hand during class discussions.

The supply chain management version of MIT’s MicroMasters credential can be earned by successfully completing the equivalent of one semester’s worth of five MOOC courses and a comprehensive final examination. The program includes one more important feature: Top graduates are invited to apply to MIT and, if accepted, complete the remainder of a full master’s degree in a single additional semester in residence at the university. In other words, those students can use the online courses to earn MIT academic credit in a “blended” program combining the MOOC courses with on-campus, in-person classes.

Digital Education for a Digital Future

Most levels of educational attainment require years of study: 12 years for a high school diploma, another two to five years for an associate’s or bachelor’s college degree, and two to six years for master’s- and doctorate-level advanced degrees. However, many educational needs can be met with much shorter, incremental offerings. For example, on average, about 40 percent of workers will require re-skilling of six months or less, according to the World Economic Forum’s Future of Jobs Report 2020, which is based on a survey of business leaders. A professional certificate program might entail three to six months of courses. A single MOOC course might last a few weeks to a few months. The WEF’s survey found that more than one-quarter of the re-skilling needed in the transportation and warehousing industry involves less than one month of effort. Moreover, the fast pace of change and the growing use of technology will force workers toward a perpetual cycle of shifting job duties and re-skilling.

Supply chain professionals therefore need opportunities to update their knowledge without having to pause their work. The Future of Jobs Report 2020 found that 94 percent of business leaders expect employees to pick up new skills on the job. Re-skilling while working will depend on non-traditional education programs that are shorter, part-time, more adaptable, and asynchronous.

Online and blended education programs are becoming the preferred choice of many supply chain professionals. One option is on-demand learning—think of it as JIT for education. These are training-delivery systems designed to quickly teach a person when they need to solve a specific problem or perform a new task. They deliver small, modular blocks of knowledge that might consist of a short video lecture or reading assignment, a quick exercise or problem set to confirm the student’s understanding, and rapid feedback on performance and any misunderstandings. Bite-sized lessons and self-tests can quickly build or refresh incremental skills.

AI can also be used to help workers improve their skills. For example, Airbus wanted to accelerate assembly of its new A350aircraft without compromising quality. The introduction of a new aircraft design comes with a learning curve as workers gain experience in setting up and running the production process. The company used its existing data and analytics infrastructure to capture raw information and fed that into an AI system to help speed the transfer of experience between workers. Overall, systems such as these recognize the patterns of creative solutions generated by human workers and then help spread them across the workforce.

Delivering a Better Future

Knowledge is power, and the ability to deliver relevant knowledge can ensure that people are supported and enabled by technology rather than supplanted by it. High-performing supply chains that get the most from human productivity and the power of technology are a key to realizing the European Union’s “Industry 5.0” vision. The ambitious goal of Industry 5.0 is to enhance the role of industry in society and place the well-being of workers at the center of the production process.

Maximizing the performance of both people and technology is vital to achieving these goals. Copious data and analytics can create transparency that enables accountability in managing and avoiding environmental impacts. Automation can help handle routine tasks so that people can concentrate on the more fulfilling parts of their jobs. AI and digital tools can augment the power of people, enabling them to handle jobs they could not in the past. Timely and affordable education and knowledge can help workers, managers, and citizens cope with technological change, volatility, and disruption.

These new technologies have the potential to change societies for the better while helping to mitigate the threats of climate change, inequality of opportunities, new infectious disease outbreaks, geopolitical power conflicts, food shortages, and other challenges. Managers and workers can make the most of AI and automation by collaborating with the technology to create fulfilling and well-paying jobs, affordable products and services, and a bright future. It is up to civil society to ensure that such a vision materializes.

Adapted from The Magic Conveyor Belt: Supply Chains, A.I., and the Future of Work, published by MIT CTL Media, copyright 2023. For more information, go to [url=https://sheffi.mit.edu/magicbelt]https://sheffi.mit.edu/magicbelt[/url]

Dr. Yossi Sheffi is the Elisha Gray II Professor of Engineering Systems at the Massachusetts Institute of Technology, where he serves as Director of the MIT Center for Transportation and Logistics (CTL).