What We Mean When We Talk about Workforce Skills

By John Alic

Labor Secretary Alexander Acosta stated recently that the United States “has more than six million open jobs, but some employers can’t find workers with the skills to fill them.” Before the 2008 recession, employers complained repeatedly of skill gaps and mismatches. With low unemployment, around 4.5%, they could not find the workers they needed. Yet the narrative did not change even as unemployment peaked, with almost 15 million people out of work in 2010. Since mid-2017 unemployment has been beneath postrecession levels and the refrain continues. Too many Americans lack skills suited to today’s economy—technology-intensive and postindustrial, exposed to global competition in services as well as manufacturing. In late 2017, the chief executive of Microsoft, Satya Nadella, told Bloomberg Businessweek “There are 500,000 jobs today in the tech sector that are open.” Some commentators go so far as to argue that skill gaps foster automation: if employers cannot find humans with the capabilities they want, they will buy robots and artificial intelligence systems.

These complaints lack context. Skill is a murky concept. It is hard to measure or observe; employers, political figures, and journalists use the term in confusing ways; and skill is too often associated with education, as if what people learn in school is all that matters. When employers speak of skills, they sometimes mean the ability to perform a particular task or job: using off-the-shelf or customized software for recordkeeping; selling enough ads to keep a struggling newspaper afloat; working as a nurse in an operating room. At least as often, employers and their HR (human resources) staff mean something quite different: social and interpersonal skills, and not just the obvious sort, the ability to get along with coworkers and deal with customers. In HR jargon, soft skills begin with showing up on time every day, doing as one is told, exercising ordinary courtesy—and also, if sometimes left unsaid, passing a drug test. As parents and schoolteachers know, these are far from universal among young people, or for that matter on Wall Street, in corporate boardrooms, and among elected and appointed officials.

Job seekers, on the other hand, claim to have been turned away even though perfectly capable of doing the work or quickly learning whatever they need to know. Some find the pay they’re offered less than merited by the job description and their experience. Others believe that employers think they’re too old or otherwise discriminate. In need of a paycheck, some take minimum wage, dead-end jobs. After the 2008 recession, many stopped looking and exited the labor force in frustration.

In bad times and good, millions of those counted as unemployed are simply in process of moving from one job to another, whether as a bartender or a biomedical engineer, part of the churn that is one of the constants of the labor market. According to the Bureau of Labor Statistics, some 5.2 million people left a job in December 2017, voluntarily or involuntarily, and 5.5 million took a new position. The bureau estimated the number of unemployed as 6.7 million, yet the long-term unemployed, those without a job for six months or more, totaled only 1.4 million, less than 1% of a labor force numbering more than 160 million people (by definition, the labor force includes those actively looking for work as well as those employed). People switch jobs for all kinds of reasons, after all, including better hours. Was it a surprise when a firm surveyed by the Minnesota Department of Employment and Economic Development responded, “It’s hard to get someone with that level of experience to work on a weekend”?

What employers want in the way of skills ranges widely. Companies ramp up their expectations when labor markets slacken, with many applicants for each vacancy, and relax them when supply tightens. Another company surveyed in Minnesota replied, “We were looking for experience in Atomic Force Microscopy.” Almost regardless of the job, employers expect basic literacy and numeracy. Employees may need to understand written instructions, if only safety manuals; they may have to compose emails or make change at cash registers. Beyond the basics, skills come in uncountable variety. Those of a dental hygienist are nothing like the skills and knowledge of an accountant, the skills of baseball players unlike those of snowboarders, the work of police officers resembles that of high school counselors in some respects and firefighters in others. Though some engineering tasks could be called “applied science,” engineering and science differ fundamentally, since the core objective in science is to understand nature, most commonly through reductive analysis, whereas engineering centers on conceptualization and design, culminating in the realization of some sort of human creation, a matter of synthesis, with science-based analysis, if present, in a supporting role.

It is easy enough to say that skills are multidimensional and mysterious. How many dimensions might there be? How should skills be subdivided? The questions are nonsensical. Skills overlap, combine, and melt together invisibly, defying measurement except in simple cases such as athletic performance or chess playing. Piece-rate wages, whether in sweatshops or in selling fur coats on commission, reward both effort and skill. Software firms can count the number of error-free lines of code generated by programmers. Otherwise companies are mostly guessing when they claim to pay workers, whether at the top or bottom of the salary scale, according to their contributions to productivity and profits.

Consider math skills. These range from addition and subtraction to differential equations and set theory. Many people find themselves counting things at work, but when manufacturers talk of statistical quality control, they do not mean that factory workers analyze statistical data; that is a task for specialists. For management, instruction in quality control serves as a motivational tool: do the job right or it may disappear, perhaps to Mexico or Vietnam. What is certain is that each of the many millions of people in the labor force embodies, in HR parlance, a unique “skill set.” Some of these skills will be universal and for practical purposes indistinguishable, others (C++ programming, German grammar) distinct and perhaps arcane. When published findings in molecular biology cannot be reproduced, did replication fail for lack of some exquisitely refined laboratory skill? Or did the original report err because of deficient practices? There is no way to tell until further attempts either succeed or fail and consensus develops, consensus among those accepted by their peers as proficient in experimental technique—or perhaps proficient in argument.

Useful tests exist for academic skills such as reading and writing, for the sort of manual dexterity needed at one time in cigar-rolling and still needed in brain surgery, and for more-or-less innate traits such as IQ. The Program for the International Assessment of Adult Competencies, developed under the auspices of the Organization for Economic Cooperation and Development to assess and compare cognitive and workplace skills, includes measures of “problem-solving in technology-rich environments” (meaning “computer-rich environments”)—a desirable step but a modest one, since the test questions mostly have to do with fluency in computer usage, as in navigating the internet and interpreting on-screen information, rather than addressing more complex sorts of problems that demand judgment. Beyond these sorts of test-defined capabilities, conceptual clarity recedes. Taxonomies go little beyond mental/manual/interpersonal categories, and it is one thing to include leadership among interpersonal skills, quite another even to catalog the ways people demonstrate leadership.

Distinguishing between skills and knowledge helps a bit. Anyone with even rudimentary skill in welding can join two pieces of low-carbon steel. And anyone with knowledge of metallurgy knows that although low-carbon steel can be easily welded, steels with high carbon content cannot; phase transitions on cooling cause the weld region to crack. Welders know not to attempt to join high-carbon steel, but few know much about phase diagrams. Few metallurgists, on the other hand, know how to weld.

Much of human knowledge has been written down somewhere, codified for accessibility. The storehouse is vast and continually expanding, yet at least in principle knowledge can be subdivided, marked off in bits and pieces, cataloged for maintenance in databases and updated as needed. Heat-treatment charts for steels complement phase diagrams and serve as guides to practice. If you do not know the average molecular weight of gasoline and need it for your work, you can find the value on the internet. Know-how also comes in tacit forms, meaning things we know, or think we know, but cannot articulate. As the philosopher Gilbert Ryle put it many years ago, “The wit … knows how to make good jokes … but cannot tell us or himself any recipes for them.” Leaving aside tacit knowledge, which as in stand-up comedy often merges with skill—a good joke badly told gets few laughs—the big mysteries then concern skills rather than knowledge. In principle if not in practice we might assess the domain-specific knowledge that people carry around in their heads; we could hardly imagine doing such a thing for their full complement of skills.

This has not stopped theoretically inclined economists. They divide skills into two categories, general and firm-specific. General or generic skills are those that people take with them as they move from one job or occupation to another. Firm-specific skills are assumed to have value, in the sense of contributing to productive output, only in a particular employment setting. In this way economists explain the reluctance of employers to train their employees except in narrow skills unique to the firm; investments in general training will be lost when workers leave.

Economists who labor in the subculture of “skill-biased technological change” make another assumption. Seeking to explain growing disparity in wages, with better-educated workers in the upper tiers of the wage distribution gaining while those in the lower tiers see static or declining pay, they link wages with educational attainment. In tribal shorthand, years of schooling become “skill.” This assumption reduces human skills to a unidimensional construct and sets aside as immaterial whatever people have studied, even at graduate and professional levels. On this basis economists conclude that those with more education earn higher wages because technological change since the 1970s has reduced demand for relatively routine work, jobs of the sort commonly taken by high school graduates, and, less obviously, that technological change—likewise taken to be a unitary construct—has increased demand for those with more schooling. The results leave much unexplained, yet appeal because parsimonious and because wages and education do, after all, correlate.

Unfortunately, policy-makers and the public have come to believe that more and better schooling can therefore be counted on to push wages higher, increase mobility, and wash away other labor market ills. With educators reinforcing the message, college has come to be seen as the road, perhaps the only open road, to a decent job, one with a future. The focus on education deflects attention from broader and deeper institutional problems in the labor market. There are plenty of reasons why schools should be improved and plenty of reasons for attending college. But more schooling for more people, rather than boosting wages and occupational mobility, could simply boost the numbers of “overeducated” Americans competing for whatever jobs the future may bring, a future that is bound to include further waves of technological and economic change, jobs paying whatever wages employers find they must offer to attract enough people to staff their organizations.

Learning, like skill, remains a considerable mystery, notwithstanding advances in psychology, neurosciences, and related fields, and a great deal of what we know and can do, beginning in infancy and continuing long past any terminal credential, whether GED or PhD, stems from learning that takes place outside the confines of formal education. Children learn quickly from raw experience. At first they grapple uncertainly with their surroundings, accumulating understanding more or less haphazardly. Once they grasp the meanings of spoken language and begin to talk, they go on to learn from other children, from parents and teachers, from the media. Adults of all ages likewise learn through mostly unconscious processes, often slowly and sometimes painfully.

What people learn, what they study in school, how long they continue in formal education, and how they fare in the labor market depend in part on intelligence as measured by IQ and other tests (there are many), and on much else as well. Most psychologists take cognitive ability to be inherent rather than learned. Cognitive tests, appropriately age-adjusted, show modest increases on average through the teenage years and modest declines in older adults, patterns quite unlike those for skills and knowledge, which increase rapidly from infancy, stabilize later, and at least for physically demanding skills diminish with advancing age. Many psychologists also believe that the so-called Big Five personality traits—extraversion; agreeableness; conscientiousness; emotional stability; openness to learning (each with their opposites, introversion to closed-mindedness)—capture the bulk of interpersonal differences. Although categories that are expansive in ways that IQ is not, they nonetheless can be related to intelligence; indeed, the last of the Big Five, openness to learning, has sometimes been called intellect (and alternatively, openness to experience and openness to intellectual inquiry, among others). Research further suggests that the third trait, conscientious, also called persistence, has the most to do with whether someone maximizes his or her potential, whether in scientific achievement or playing the trumpet.

Intelligence tests that come to be accepted based on large-sample statistical analyses correlate reasonably well with one another, and the measure that shows the closest correlations with the others has been labeled g, for “general intelligence.” Research shows, unsurprisingly, that g also exhibits the closest correlations with educational outcomes and with available measures of workplace competencies and labor market outcomes, whether subjective (supervisor ratings) or more nearly objective (wages, advancement along career trajectories). But IQ, g, and other measures put more weight on what people know than on how well they make use of what they know. Plenty of smart people, after all, do dumb things. Thus young people who understand full well that success in school matters for finding a good job may still drop out. In the end, measures of intelligence take us only a little ways in grappling with notions of skill.

The simple answer is from experience, at school and on the playground, at home and at work. A gifted few, very few, can learn just about anything they want or need on their own. For the most accomplished scientists, after all, education is simply the starting point in careers marked by continued learning, discovery, and invention. For others, school is little more than a place to make friends, pick up basic skills, and become accustomed to the sort of regimented discipline found in many workplaces.

Schools seek first to convey codified knowledge and skills, treating these as standardized and formulaic even in many college courses. Postsecondary occupational preparation likewise begins in the classroom, then may follow an apprentice-like model, familiar from art classes and the construction trades, that combines formal instruction with less structured practice. Medical students learn the basics of physiology and anatomy, of suturing and bone-setting, of listening to patients and evaluating symptoms. Suturing is mechanical. Diagnosis is not, and thus far more difficult to teach or to evaluate. And once physicians leave school, some, like their counterparts in other occupations, continue to learn while others do not. Studies of continuing medical education find little or no change, on average, in clinical practice. Physicians have few incentives to keep up with advances in medicine since customers cannot evaluate their skills. After all, who can really tell whether the family doctor falls in the 40th percentile of skills or the 90th percentile? Or for that matter their child’s third-grade teacher? Much the same holds for auto mechanics and financial advisers.

Schools get much blame for workforce skill deficiencies. Since the US Department of Education’s 1983 report A Nation at Risk, the public has repeatedly been told that primary and secondary schools fail to prepare young people for work (as if that was their chief task), that too many leave high school unready for college, and that shortages of STEM (science, technology, engineering, and mathematics) graduates threaten the nation’s economic future. US students rank in the middle or below in international surveys of educational achievement, and with calls for school reform going back generations, the reasons, and the appropriate responses, continue to be argued over. Recent popular proposals include secondary-school courses in what’s usually called computer science. In some cases this seems little more than training in off-the-shelf software (high school students in North Carolina can earn certification in Microsoft Office) and in others programming. Apple’s chief executive, Tim Cook, told Fortune magazine “we think that coding is the sort of the second language for everyone in the world. And that’s regardless of whether they’re in technology or not. I think that you don’t have to be in technology for coding to be very important.” Few of the four million or so people with jobs in what the Bureau of Labor Statistics considers one of the computer occupations will ever write or even look at code, and computer science as a discipline is more about systems and problem-solving than line-by-line programming, just as writing an essay is more about what is said than spelling and grammar. Even so, learning to code in Java or Python can be a useful step toward rigorous thinking, much like algebra, and for some people a point of entry into a rapidly growing field full of opportunities to learn more and advance, a field in which experiential learning will almost certainly remain as important as in the past. Information technology simply could not have expanded as it did if dependent on academic training: employment has increased much faster than the number of graduates from specialized programs, and people continue to pick up skills informally, in the workplace and outside it, from peers, through trade and professional societies, from vendors. These forms of learning should be encouraged, systemized, incentivized, and supported, and not just in information technology. This is, after all, how postdocs are supposed to get their start in research and how established scientists stay at the frontiers of their fields.

Employers interview job candidates and expect letters of reference for some positions, but they rely more heavily on educational attainment and credentials, which as screening devices have proven far more reliable. Like supervisor evaluations of incumbent workers, interviews and references mean little. Educational attainment, on the other hand, reflects thousands of hours spent in ordered and supervised settings not unlike those of typical workplaces. When hiring, then, firms place more weight on a high school diploma than a supposedly comparable GED, on a two-year degree from a reputable community college than a seemingly comparable credential from a for-profit school (the more so if known for shady practices and underperforming graduates), on a four-year degree from a “good” university than from one with a lesser reputation. More than 20 million people enroll in US colleges and universities each year, and around 60% of them eventually graduate, according to the Department of Education. Respectable grades from a respectable school signal ability to learn and also discipline (showing up), persistence (turning in work on time), agreeableness (please the teacher, please the boss), and social skills sufficient to stay out of too much trouble.

Although STEM occupations make up only a small slice of the workforce, around 6%-7% by most accounts, since the late 1940s handwringing over the numbers of graduates has been a “central, at times hysterical concern,” in the words of physicist and science historian David Kaiser. During the Cold War, educators and government officials claimed the United States risked falling behind the Soviet Union in engineering and science. With détente and the later collapse of the Soviet empire, economic competition, first with Japan and then with China, became the new challenge, to be won through innovation and productivity growth, hence research and development and STEM graduates.

STEM training has undeniable value across wide swaths of the economy, as demonstrated by the jobs held by those with engineering and science degrees, over half of which fall into non-STEM occupational categories. Although occasionally portrayed as underemployment, or a misallocation of human capital, this is better seen as an indicator of demand for employees with good quantitative and analytical skills, regardless of field of application. Indeed, it would seem hard to argue that there could be an oversupply of STEM graduates, and for such reasons the acronym seems unobjectionable as an exercise in branding. The attention recently focused on STEM might even be taken to suggest some sort of inchoate yearning for a citizenry better equipped to respect specialized knowledge and hard-headed empiricism, rationality in a word. At the same time, many Americans—around one-fifth, according to the most recent surveys—continue to find their way into STEM occupations without relevant academic credentials. Mobility of this sort has always been a strength of the US economy, likewise to be encouraged.

Despite the wage premiums that come with degrees from well-regarded colleges, Fortune tells us that “In its early years, [Google] had recruited from elite schools like Stanford and MIT. But when Google examined its internal evidence, it found that grades, test scores, and a school’s pedigree weren’t a good predictor of job success. A significant number of executives had graduated from state schools or hadn’t completed college at all.” Indeed, “the proportion of people without any college education increased over time.” Meanwhile a September 2017 report from the Government Accountability Office titled Low-Wage Workers found that “the percentage of workers with college degrees earning $12.01 to $16 per hour increased from 16% in 1995 to 22% in 2016.”

Recognition of these sorts of dynamics has spread, with pundits, politicians, and some employers pointing to apprenticeships and occupationally oriented community college programs (often called career and technical education) as underappreciated alternatives to four-year degrees. Yet in the United States apprenticeships have never spread much beyond construction, where poaching of trained workers by nonunion contractors has curbed participation by unionized firms, and companies in other industries that once trained employees or subsidized tuition no longer do so. In most parts of the country, community colleges have been underfunded from their beginnings, and states have been cutting support for four-year public institutions. As the Wharton School’s Peter Capelli argues, businesses have succeeded in pushing off more and more of the costs of workforce preparation onto the public sector. Leave it to the schools, seems to be the message. The response from government: Leave it to student loans. As policy, this amounts to viewing human capital as a purely private good rather than a national resource. It also assumes that young people and their parents are fully capable of assessing the content and quality of yet-to-be-delivered educational services, even though these are hard-to-judge intangibles, the value of which will depend on their suitability for careers extending decades into the future. This is like treating purchases of education as equivalent to buying an off-the-shelf smartphone or an insurance policy.

Put simply, and a bit crudely, they want it all: high skills with low wages; big pools of well-educated job candidates from which to pick and choose potential superstars—engineers, computer scientists, and entrepreneurial managers who just might seed a billion-dollar line of business (the reason that Silicon Valley, like Hollywood, obsesses over “talent”); obedient employees, whether counter workers or data scientists, who when asked can nonetheless bring creativity and independent initiative to the workplace; freedom to hire and fire at will. And they’d like the public to pay the costs of preparing workers to fit their job openings. These expectations underlie many of the complaints over skill gaps, mismatches, and shortages.

Much of what employers want they get. Among wealthy nations, US employment law has always been uniquely friendly to business and hostile to workers. Into the twentieth century the courts typically accepted, in the words of historian Melvin Urofsky, “the legal fiction that employer and employee stood as equals in the bargaining process.” Labor-friendly legislation, whether barring child labor or wages paid in scrip accepted nowhere but the company store, might make it through state legislatures only to be struck down as interfering with freedom of contract. Workers, said the courts, could always say no (and shouldn’t a father be free to contract out his offspring to work in the mine or the mill?). Then as now, employers also used implicit or overt threats to move production out of state or out of the country to hold down wages, salaries, and benefits. Other regulations governing business conduct, such as antitrust policy and enforcement, might wax and wane; the general rule in labor law has always been weak standards, weakly enforced. Firms that take differing positions in Washington on trade policy and compete vigorously for favors from local and state governments find their interests aligned when it comes to employment law and policy.

Following something of an interregnum during the Great Depression and World War II, the 1947 Taft-Hartley Act marked the beginning of resurgence in employer prerogatives, and when the Reagan administration further deregulated labor markets, “right to work” laws—resurrected and refurbished on the model of union-busting strategies devised a century earlier—resumed their spread. Despite legal prohibitions enacted since the 1960s against racial and other forms of discrimination, employers remain largely free to fire employees with or without cause. Low minimum wages hold entire families beneath the poverty line. Since the late 1970s the share of productivity gains delivered to employees in the form of compensation has fallen and the share flowing to owners in the form of profits and dividends or held as retained earnings has risen; while economists search, so far in vain, for technical explanations, it seems at least as likely that the turn away from what had seemed a well-established pattern of wages increasing in step with productivity growth reflects a still-continuing rise in the political power of business interests and weakening of labor. Underlying these trends since the 1980s has been the fraying of social safety nets for individuals and families, but not for businesses.

Without too much risk of overgeneralization, we can conclude that many—not all—claims of skill gaps and mismatches reflect misunderstandings of the nature of skills, the wishes and expectations of employers and their hiring practices, and the purposes of public education.

• Skills, unlike knowledge, cannot in general be observed or measured except in the simplest cases, as for basic literacy and numeracy.
• Companies often state that they cannot find workers with needed skills, yet at the same time decline either to raise wages or provide training.
• To employers, educational attainment signals potential. They evaluate applicants on the basis of credentials, not necessarily because of what job candidates may have learned in school (beyond basic skills, and with exceptions as for STEM occupations and professional degrees), but because a diploma or degree signifies, first of all, willingness to work and to conform. The weight given to credentials such as degrees from Ivy League schools also helps preserve social hierarchies.
• Many firms, and their supporters in policy circles, behave as if private interests coincide with public interests and the chief task of education is to prepare young people to slide seamlessly into available jobs—in today’s workplaces, which will not be tomorrow’s.

Viewing education and training as public goods, which they are, would shift our perspective to preparation for the future. Some policy-makers do recognize this. In February 2018, David Long, president pro tempore of the Indiana State Senate, told The Hill that “Fifty years from now, half the jobs that we know of today will be gone.” This may prove an understatement. Yet policy-makers continue to tinker at the margins of schooling rather than seeking to build platforms for continuing learning of the sort that many Americans in computer occupations had to improvise. And we seem to have let educators highjack “lifelong learning,” now taken almost reflexively as meaning “go back to school” (and then do it again), which is hardly realistic for most of those already in the workforce.

Rising inequality in wages, benefits, and wealth has been one of the most pronounced shifts in US society over the past half-century. Higher wages accompanied by employer-supported training would dissolve most of the concerns over skill shortages in the labor market and would begin to counter, if not necessarily reverse, economic inequality. Basic literacy and numeracy, willingness to learn, and flexible access to high-quality training on a continuing basis comprise the necessary starting points. Tax revenues are the proper source of support. Studies of actual skills deployed in actual workplaces, based on careful observation rather than HR talk, show that relatively few workers need high-level specialized skills. What everyone needs are opportunities to learn and to advance in accord with their wishes and motivations without sacrificing already meager paychecks.