After decades of job loss and a struggling reputation, manufacturing has made a comeback in the United States. Since the recession, production jobs have increased—and so have the knowledge and skill requirements.
After analyzing hundreds of thousands of job postings, we observed that manufacturers need multi-functional engineering technicians possessing both traditional manufacturing and engineering skills. The result is that today's high-value production worker is a hybrid of a boots-on-the-ground technician and an engineer laser-focused on improving how things get done.
The technical skills required yield competitive wages and also transfer well to other in-demand industries such as finance, professional services, and health care. To ensure the future of domestic manufacturing, educators and employers must recognize the potential of these high-skilled production jobs and work together to train the next generation of workers.
In this paper, we will (1) show the demand for domestic production jobs since the recession, (2) summarize the major skills that employers need, and (3) explain the compensation and transferability for these skill sets.Download this report
We used a diverse set of labor market data sources.
Manufacturing used to be the United States' top employer. During the Industrial Revolution, workers traded hand tools for powered machinery, and one-off projects turned into mass production. Later, during and after World War II, manufacturing dominated the economy.
Then it didn’t.
Between 1990 and 2007, manufacturing lost four million jobs. From December 2007 to January 2010, it shed another two million-plus jobs, making it the hardest-hit industry of the Great Recession. Meanwhile, health care rose to the top with three million new jobs.
To get a clear picture of manufacturing performance over the past three decades, we pulled data from several time periods. The following table shows manufacturing's compared to other industries from 2000 to 2009—just into the recession.
Interestingly, while manufacturing jobs have declined drastically since 1990, output escalated thanks to increased automation, efficiency, and offshoring (Figure 1).
Unfortunately, the decades-long job decline has deterred newer generations from pursuing occupations in manufacturing. Production jobs are stereotyped as dead ends, and students are encouraged to pursue a four-year degree rather than learn a trade. As a result, the manufacturing sector suffers from a skills gap and widespread vacancies, both of which will only worsen as the aging workforce retires.
Like every other industry, manufacturing has adapted to a technological world. Humans are no longer needed for every simple thing. Automation, robotics, and modern processing power streamline the production environment.
Modern production workers must straddle two spheres: traditional manufacturing and modern manufacturing, or what Deloitte University Press calls the “smart factory.” Workers must keep one foot firmly rooted in the old world of machining and welding, while planting the other in the advanced computer-automated technologies of the future.
Since the Great Recession, manufacturing has grown by nearly one million new jobs (Table 2). While it's unlikely that employment will reach pre-recession levels, we still see fierce demand for workers.
The BLS's Job Openings and Labor Turnover Survey (JOLTS) (Figure 2) shows an impressive 350% increase in job openings over the past 10 years—a greater increase than those of the fast-growing health care and IT sectors. Unemployment in manufacturing is also extremely low at 2.6% (Figure 3), which is better than many industries.
Job postings over the last three years also demonstrate that production jobs are on the rise. In fact, production jobs are on par with IT and business/finance jobs in terms of raw demand (Figure 4).
This uptick in job postings doesn't surprise us. Nearly half of the nine million people working in production jobs are 45 or older (Figure 5), spurring employers to seek younger workers to fill the impending gaps. However, attracting students to training programs is notoriously difficult. Both the National Association of Manufacturers and the American Welding Society predict massive shortages, possibly as soon as 2020.
We examined nearly 400,000 production job postings from 2017 to determine the top skills that employers need. Our analysis covers the United States and three individual states: a traditional hub of manufacturing (Michigan); a representative of the West Coast (California); and an emerging region for manufacturing in the Southeast (Tennessee).
As we walk through our analysis, keep two caveats in mind.
Now let's consider production jobs at the national level. Here are the companies that made the most job postings for production workers in 2017 (Figure 6).
The postings are dominated by the following categories:
The most in-demand skills can be sorted into four groups, or skill clusters:
The following graphic (Figure 7) illustrates three primary characteristics of these skill clusters and the intricate relationships between them:
When we examined the top four skill clusters for production jobs across the U.S., we found that two of the clusters (traditional and computer-automated technologies) are more aligned with what we typically associate with production workers. The other two clusters (Six Sigma and GMP) are more oriented toward engineering. See Figure 8 below.
1. Traditional Skills – Traditional production skills remain in high demand and are the most prominent across all production job postings. Despite the increasing automation of tasks, employers still place a premium on tried-and-true production skills like welding, machining, and brazing. Below, and in each of the following graphics, the numbered list indicates the top skills found in the cluster.
2. Computer-Automated Technologies (CAT) – The CAT cluster (Figure 10) is where manufacturing's expanding automation shows up. CAT involves the knowledge of processes and experience with technology to design and create products. Employers frequently look for people who have A) strong working knowledge of trigonometry, computer-aided manufacturing, and computer design, and B) experience in blueprinting, 3D modeling, Siemens NX (among other tools), electrical discharge machining, and tolerance (measuring and monitoring the permissible limits of variation when creating products and parts).
3. Six Sigma or Lean Process – Six Sigma is a data-driven methodology that improves performance by removing waste and reducing variation. Manufacturers operate under intense and precise parameters, so it is imperative that workers maintain these high standards. Examples of the top knowledge, skills, and abilities related to Six Sigma are continuous process improvement, business process improvement, value stream mapping, operational excellence, and Kanban Principles.
4. Good Manufacturing Practices – This final cluster is about quality control. GMP ensures that the product meets the necessary quality requirements, whether the requirements are internal, customer-driven, or imposed by government administrations such as the Food and Drug Administration. This perfection is achieved only through constant monitoring and perpetual process improvement.
Overall, the national skill cluster shows that manufacturing employers need workers with traditional production skills mixed with engineering-type skills. The demand for such a broad skill set is eye-catching, especially in this era of hyper-specialization. Workers must understand the tools of the trade as well as the advanced machinery dominating the field.
Also of note is how frequently continuous process improvement and business process improvement appear in the job postings. This indicates a strong need for workers well-versed in the practices that help the company eliminate waste, ensure the production environment operates at a high level, vigilantly track quality standards, and so on. Even small mistakes can have huge ramifications. We're all well aware of the massive financial and public relations damage of product recalls. Workers who successfully master and blend these skill sets are critical to maintaining a high-functioning workplace, and are therefore keenly sought after.
While this research is focused on technical skills, we would be remiss to skip the important soft skills that also show up in production job postings. Manufacturers often value skills like leadership, problem solving, innovation, computer literacy, and writing just as much as they value the technical skills. In the following graphic (Figure 13), we also see that workers need to be proficient in Excel, Outlook, PowerPoint, and even Spanish. This goes to show that in every industry, a well-rounded worker is highly valued.
As you'd expect, auto manufacturing dominates Michigan's manufacturing scene. General Motors, Ford, Chrysler, and many part suppliers published the most job postings in 2017.
In a deviation from the national picture, Michigan has two new clusters: vehicles and industrial design, which are closely aligned to the state's auto production specialization. The vehicles cluster encompasses production skills primarily related to the specialized needs of auto, aerospace, and defense. Industrial design is the creation of products and systems optimized for manufacturability and efficiency.
Vehicles and traditional manufacturing are both characterized by skills like hydraulics, preventive maintenance, predictive analysis, and pneumatics. However, vehicles is more specialized, defined by its own set of skills like engines, steering, and transmissions.
We saw strong overlap between GMP and Six Sigma at the national level, but here in Michigan we observe an overlap between industrial design and Six Sigma. Five key skills appear in both clusters:
Across the board, there is a strong fusion between production (traditional manufacturing, vehicles) and process improvement (industrial design, Six Sigma).
California is dominated by aerospace and defense, along with auto manufacturers. As a result, California's top skill clusters are similar to Michigan's, but the order is slightly different and GMP replaces traditional manufacturing. Vehicles is still the most prominent cluster and is now closely followed by industrial design, indicative of the advanced engineering going on throughout the state. Six Sigma is our third cluster. And fourth, we see that GMP has returned, which is likely due to California's high concentration of biotechnology and food production.
There is also one skill that, for the first time in our analysis, appears in three clusters: corrective and preventive actions (CAPA). It appears at the overlap of industrial design, Six Sigma, and GMP. According to the FDA, CAPA is a key skill meant to ensure that rules, regulations, and processes in a variety of tasks are followed and documented.
Note that while Michigan had two classic production skill clusters (traditional manufacturing and vehicles) and two engineer-type skill clusters (industrial design and Six Sigma), California has only one traditional cluster (vehicles) and three engineer clusters (industrial design, Six Sigma, and GMP). Again, this demand for more advanced skills is influenced by California's specialization in aerospace/defense products, automobiles, and biotech.
Compared to California and Michigan, Tennessee's manufacturing scene is small, but diverse. A wide variety of industries call Tennessee home:
Like the nation, traditional manufacturing is Tennessee's most prominent cluster. Six Sigma moves into the second most prominent spot and is the only cluster to appear in high demand across the U.S. and in each of our state regions. This indicates that Six Sigma is critical to a wide range of production jobs. Vehicles comes in at third most prominent, followed by CAT. Note the tight connection between traditional manufacturing, vehicles, and CAT with one recurring skill: machining. Whereas California was more oriented to engineering, employers in Tennessee are placing a higher premium on workers with production technology skills.
Now that we have a handle on the skills, we want to consider two important questions. First, what are employers willing to pay for the production skills we've discussed? Second, are these skills creating upward mobility or transferability for those who attain them?
Using government data to consider wages for production workers, we see that the mean wage is $15.90 per hour or $33K per year—far below the national mean wage for all occupations ($23.64 per hour, $49K per year; see Figure 32 below). This average is also below the wages of many jobs that don't require formal postsecondary education, which means jobseekers lacking a college degree aren't likely to choose manufacturing when they could earn better wages somewhere else.
However, existing taxonomies within government data struggle to tell the whole story. The low hourly wage is likely weighed down by the large number of workers engaged in on-the-job training (OJT), during which they're paid less. If employees leave the company without completing the training, they never reach a higher wage tier. The company must then hire replacements at the same OJT level, and so on. Government data cannot capture this nuance, so we see perpetually low average wages.
To derive a more accurate wage estimation for these new production jobs, we used a new skills-based compensation model. But first, a quick note about what makes wage analysis so tricky.
Throughout this paper, we've observed that an increasing number of manufacturing jobs straddle engineering and production. Yet the taxonomies within government data can't account for this blended nature. For instance, government data would classify a new job as either machine operator or mechanical engineer, but in reality, it's both.
This is an unavoidable challenge when categorizing emerging occupations or skills. Emerging occupations and skills hardly ever fall out of the sky. Rather, they are the byproducts of two or three types of work coming together to solve a new problem, or to create a better approach for solving an old one. We observed the same phenomena in our recent data science research: statistics and mathematics joined with computer science and software to create data science.
The same has occurred in manufacturing. The new hybrids of traditional production workers and engineers should be thought of as engineering technicians or technologists. But the job is far too nascent for government data to capture with its current categories.
To determine the wages associated with our skill clusters, we turned to a new compensation model that uses traditional sources mixed with observations taken from job postings and professional profiles. We then grouped the skills into the same clusters: traditional, CAT, vehicles, Six Sigma, GMP, and industrial design. This allowed us to determine the wages specific to each cluster.
We found that if workers possess these much-needed skills, compensation is greater than as indicated by government data (Table 3). For instance, the weighted average for workers who possess vehicle production skills is $48,585 per year. That’s significantly higher than the $33,000 mentioned earlier, which captures only pure production workers. Furthermore, if they possess 10 or more skills, the wage jumps to $57,000-$67,000, well beyond the high end of the wage curve we received from the government data. Likewise, workers proficient in skills related to GMP, industrial design, and Six Sigma are all paid greater wages.
Additionally, our research indicates that workers with traditional production experience can successfully progress into higher-paying positions when they acquire industrial design, GMP, and Six Sigma skills. Workers in the classic production areas are introduced to principles and techniques closely related to engineering, even business. Returning to school for an advanced engineering degree would prepare them for increased responsibility or a management position, both of which offer higher wages.
For example, one industrial designer at Texas Instruments began her studies at a community college, went on to earn her Ph.D., and is now working as an industrial engineer and solving complex business problems at the company.
To round out the picture, let's relate our skill clusters to associated job titles and typical education levels. In Table 4, we see the top job titles associated with each of our major skill clusters. For instance, “welder” is the most common job possessed by people with traditional skills. Workers with Six Sigma skills are most often manufacturing engineers or production supervisors.
As we explored the job titles associated with the skill clusters, we found them to be surprisingly generic. In other high-demand industries like IT and health care, the job titles are more specific. We also found that employers tend to overstate education requirements. For instance, some manufacturing plants may “require” a bachelor's degree, but will hire at the associate's level.
That said, here is a list of the most common job titles in each skill cluster. Each title is also associated with a specific level of education, based on the education reported by individuals currently working these jobs. The highest-paying skill clusters (GMP, industrial design, Six Sigma) are generally oriented toward engineering and tend to require bachelor's degrees. Note that for some manufacturing engineers/production supervisors, the required education is a high school diploma, yet they still earn decent wages thanks to their Six Sigma skills.
Our final question is this: Do these skills prepare workers for competitive career pathways—promotions within a company or transitions into similar positions outside manufacturing?
The answer is yes.
We've already noted that workers can increase their wages by acquiring advanced skills that qualify them for higher positions. These positions may exist within the same company. But related careers also abound outside manufacturing.
Opportunities are especially plentiful for workers with Six Sigma skills. Not only are Six Sigma skills useful in non-production departments within a company (departments like sales, operations, and finance), they're also in high demand within other industries. Figure 33 below provides three quick examples. The figure illustrates the distribution of demand for Six Sigma skills among three fast-growing, high-wage disciplines outside manufacturing: 1) professional services (legal, PR, accounting, etc.), 2) health care, and 3) finance.
Let's paint a picture. Say a young production worker earns $25 an hour as a welder or machine operator at a manufacturing company. While working part- or full-time, they acquire an engineering degree (or certificate) that provides Six Sigma-related skills. Now they transition into a quality assurance engineering role, which boosts their pay to $35 an hour. Once they gain experience with business process improvement, they take a few finance and accounting courses and move into a business role—within the same company or perhaps at a different organization. Given our data findings, such a pathway is very possible.
How do we solve the manufacturing talent shortage? Collaboration is vital. Below, we recommend a few first steps for employers, educators, students, and parents.
In a post-recession renaissance, modern manufacturing has emerged with a remarkable new look. It's easy to bemoan the job loss that hit manufacturing in the 21st century, but that would be to ignore the industry's bright gift for the future: high-demand, high-wage careers with a fusion of traditional hands-on skills and tech-heavy engineering.
Yes, there are fewer jobs to go around, but the remaining jobs demand greater proficiency in a wider variety of skills. These jobs also provide great stepping stones to careers in other growing industries.
It's up to colleges and manufacturing companies to spread the word about these promising opportunities and help students navigate an exciting new world of highly educated, multi-skilled employees.
Emsi provides high-quality labor market data and expert analysis to professionals in higher education, economic development, workforce development, commercial real estate, and talent acquisition. Since 2000, hundreds of institutions and employers across the US, UK, and Canada have used Emsi to align programs with regional needs, recruit and retain students, equip students with career visions, support local business activity, and hire the right talent. Learn more at www.economicmodeling.com. Follow us @desktopecon or on LinkedIn.
For more information about this report or Emsi data, contact Rob Sentz at firstname.lastname@example.org.