Trends in Job Satisfaction

Much of my work is aimed at helping people find satisfying jobs. That’s why I was interested to find a survey report (PDFhere) that looked at job satisfaction, among other fulfilling aspects of life. The report, “Trends in Psychological Well-Being, 1972–2014,” by Tom W. Smith, Jaesok Son, and Benjamin Schapiro, was published by the research institute NORC at the University of Chicago. (I earned my master’s degree there, but at that time I was researching English literature.)

The researchers looked at surveys that have measured people’s level of satisfaction in general, with one’s marriage, with one’s financial situation, with the level of excitement, and (most interesting to me) with one’s job. Specifically, they looked for trends in how people’s satisfaction changed over the past four decades.

It turns out that of all the kinds of satisfaction that they looked at, job satisfaction was the most stable over the time period that they examined. Here is a graph showing the trend for those reporting they were “very satisfied” with their job or housework:

Note the contrast with this graph of satisfaction with one’s financial situation—which shows a long-term decline and a notable dip apparently caused by the Great Recession:

In addition to the trends, note the levels of satisfaction shown here. At its very peak, in the late 1970s, financial satisfaction reached only 35 percent, whereas job satisfaction came close to 90 percent at times and never sank below 80 percent.

Using data from the report, I created the following graph showing trends in job satisfaction separately for men and women. You can see that the general trend is that women used to be less satisfied than men but lately have been more satisfied. My guess is that this is the result of growing opportunities for women in the workplace:

The researchers found that job satisfaction tends to increase with age; this was true for all years that they studied. It seems likely that as people age, they gain greater mastery over their job demands, they may get greater recognition for their skills, and they may learn which job environments suit them best and thus move into more satisfying situations. Here is a graph based on the average percentages of those “very satisfied” over the entire span of the study:

Finally, here are the trends for job satisfaction, with separate trend lines based on the level of education of the respondent: less than high school, high school, or college (or beyond).

Overall, those with more education tend to be more satisfied with their jobs. A notable exception occurs just at the beginning of this century, when those with less than high school showed the greatest satisfaction—evidently the result of the tail end of the tech boom. Conversely, the Great Recession seems to have dampened, at least temporarily, the satisfaction of those with more education.

The Importance of the Sample

In my work researching and writing about occupations, I encounter a lot of statistics. And this year, with an election coming ever closer, we are likely to see the results of many surveys of voters. I want to emphasize that numbers reported from surveys tell less than half of the story. They are the results of mere tabulation. What makes the numbers meaningful is the nature of the sample. Or, to put it another way, you can’t understand what a study tells you unless you understand the sample it’s based on.

To illustrate this point, I like to bring up two anecdotes. I think you’ll find them interesting even if (maybe especially if) you’ve never taken a course in statistics.

The first anecdote is based on the research that social scientists did when they essentially invented the science of jury selection. This happened in 1972, when seven radicals were about to go on trial in Harrisburg, Pennsylvania, for conspiracy to raid draft boards and destroy records, among other planned antiwar actions. This was a time of great political polarization and in a place that is characterized by political conservatism. The researchers, working on behalf of the antiwar activists’ lawyers, wanted to find a way to predict the political leanings of jurors so the lawyers could seat a jury that would be less conservative than one chosen at random from the Harrisburg population. The lawyers would not be able to ask the potential jurors flat-out about their politics; instead, they needed an indirect way to assess this.

The social scientists surveyed citizens of that community to identify their political attitudes and then correlated these attitudes with other facts about the jurors. They discovered that the surest way to predict a Harrisburger’s politics was to ask how much education the person had: The more educated the person was, the more conservative that person’s politics.

The researchers eventually realized why this was so: Young people in Harrisburg who became highly educated acquired the occupational mobility to leave the region if they were not conservative; therefore, the sample of highly educated people who remained had to be quite conservative. If the results of their survey surprised you, it’s because you didn’t stop to think about what the sample really was: not everyone who ever lived in Harrisburg, but rather those who remained—by choice or because they were less able to move out.

The second anecdote is from the Second World War. British bomber planes flying missions over Germany were often shot down by anti-aircraft fire. The Royal Air Force wanted to shield vulnerable parts of the aircraft with armor, but they wanted to use a minimal amount of armor to avoid weighing down (and slowing down) the planes. The RAF commissioned the statistician Abraham Wald to examine the planes after bombing missions to determine where on the planes’ undersides it was most critical to apply anti-flak armor.

Wald counted bullet holes in the planes and recommended that armor be applied where there were the fewest bullet holes.

This may seem like a mistake to you. Maybe you’re thinking that armor is supposed to protect against anti-aircraft fire, so shouldn’t the RAF have armored the places that got hit the most?

Again, consider the sample: Wald was not looking at every bomber that flew a mission, but rather those that returned from missions. Bombers that got shot down were removed from the sample. The bombers that returned and made up the sample were the ones that were hit only in places that were not critical for staying airborne. The places where the surviving planes were not hit, therefore, were the most likely to be critical and in need of armor.

If you’re wondering why I’m writing about this subject in a blog about careers, consider this blog entry a look at how complicated statisticians’ work can be, not so much in terms of the mathematics, but rather in terms of the concepts that must be understood.

The nonstatistical lesson to take away from these anecdotes is that you have to be careful when you make a generalization about a population—for example, the notion that educated people are more liberal politically (or, to draw on today’s politics, the notion that people of one religion are a greater threat to security). Such generalizations may be true in some global sense, but the particular population you are dealing with may really be a subset of the global population, either self-selecting or selected by some exterior factor you have not considered. The global generalization may be a poor fit for this subset, or the subset may be a misleading basis for a global generalization.

Should I Sign That Noncompete?

It is a paradox of today’s job market that employers want ever-greater flexibility in their ability to shed workers but simultaneously want to reduce workers’ flexibility in seeking employment. Specifically, employers increasingly are imposing noncompetition agreements (“noncompetes”) that can seriously limit workers’ ability to find jobs elsewhere. According to a White House report (PDF), an estimated 30 million Americans, nearly one-fifth of the workforce, are bound by these agreements, and roughly 37 percent have been so bound at some time during their careers. Perhaps the agreements themselves have not proliferated but merely their enforcement. Whichever is the case, “The law firm Beck Reed Riden LLP found a 61 percent rise from 2002 to 2013 in the number of employees getting sued by former companies for breach of non-compete agreements.”

The White House looked into this matter out of concern that noncompetition agreements can hamper the economic recovery. “Non-competes can reduce workers’ ability to use job switching or the threat of job switching to negotiate for better conditions and higher wages, reflecting their value to employers. Furthermore, non-competes could result in unemployment if workers must leave a job and are unable to find a new job that meets the requirements of their non-compete contract. In addition to reducing job mobility and worker bargaining power, non-competes can negatively impact other companies by constricting the labor pool from which to hire. Non-competes may also prevent workers from launching new companies.”

In some states, most notably California, employment laws make noncompetition agreements essentially unenforceable.  It is thought that the absence of noncompetes is one of the factors that have contributed to the towering success of the Silicon Valley. Job-hopping is a normal part of career building in the tech industry there. In fact, job-hopping is one of the reasons that employers have traditionally tended to cluster together geographically with others in the same industry, even when access to natural resources or transportation infrastructure is not a factor. Think of New York for finance, Nashville for music, or Detroit for automobiles.

Noncompetes reduce the efficiency of these industry clusters. As a result, The New York Times reports that some states are trying to limit the reach of noncompetes in hopes of duplicating one of the factors of the Silicon Valley environment: “Hawaii banned noncompete agreements for technology jobs last year, while New Mexico passed a law prohibiting noncompetes for health care workers. And Oregon and Utah have limited the duration of noncompete arrangements.”

I live in New Jersey and have personal experience with this kind of shackling. In the late 1990s, my employer required that I sign a noncompetition agreement as a condition for receiving a raise. I complied, although it bound me not to compete for one year, and after a downsizing only a few years later, the agreement seriously limited my work as a consultant. The crowning irony was that only a few years after I began consulting, my old employer came back to me in need of my consulting services and presented me with a contract that contained another noncompetition agreement—this one binding me for two years.

I refused to sign it, and with no hesitation or bargaining, they struck that paragraph from the contract. Since then, I have been asked by another employer to sign a noncompete and have again refused, with no adverse consequences.

What should you do if an employer confronts you with a noncompetition agreement? First, you should investigate whether it is enforceable in your state and for your occupation. To be totally sure, you may want to consult a lawyer, but you can get useful preliminary information from a downloadable chart at the website of Beck Reed Ridin, LLP.

It’s usually a good idea to negotiate with your employer over the terms of the noncompete. If you’re lucky enough to have some bargaining power, such as a very desirable skill set, you may be able to convince the employer to strike the agreement entirely. If not, you may be able to get the employer to relax some of the terms. For example, you may suggest altering the agreement to restrict you only in a certain geographic area or only from working for certain employers. You may be able to reduce the duration of the restriction. You may get the employer to accept wording based on the conditions of your future separation—for example, that the restriction will apply only if you quit, not if you are terminated.

Be sure to examine the fine print of any noncompetition clause. (Again, a lawyer may be helpful.) For example, some agreements include the onerous requirement that the ex-employee will have to pay any legal fees that the employer incurs as part of enforcing the agreement. Such additional burdens may also be negotiable before you sign.

Understand that one reason employers like to impose noncompetition agreements is that they fear you will carry company secrets to a competing organization. It is reasonable for the employer to ask you to sign a nondisclosure or confidentiality agreement with wording that is separate from noncompetition.

A Three-Angle View on Your Career

When you think about how to improve your career, it helps to view it from several different angles. I find it useful to employ the approach called tagmemics. Please let me define this term for you before it scares you away, and then you’ll start to see its usefulness.

The idea of tagmemics is that any unit of human experience can be viewed in three forms: as a particle, as a wave, and as a field. This approach was originated by a linguist, Kenneth Pike, so it may or may not be very sound as physics, but I find it very useful for achieving insights into ideas such as the one I’m discussing here: improving your career.

First, let’s look at your career as a particle—as a static entity. To do that, you need to move away from the word career (which implies development over time) and focus instead on the word job. (If you’re still in school, consider that your job.) Ask yourself these questions about your job as it is right now:

• Does your job have a title that you’re happy with?
• During the workday, do you find the work tasks interesting and engaging, or do they involve knowledge or tasks that don’t interest you?
• Are your skills a good match for the job, or do you feel overwhelmed (or unchallenged)?
• Is the stress level one that is comfortable to you?
• Are you satisfied with the physical requirements of your job?
• Is the amount of structure in your job too loose or too confining?
• Do you enjoy the level of creativity in your work?
• At the end of a typical workday, do you have a feeling of satisfaction?
• Do you have a way of assessing your work and therefore taking pride in what you have accomplished?
• When you’re not working, is your job providing a sufficiently comfortable lifestyle and amount of leisure?

If some of your answers indicate a situation that is not totally satisfactory, this may be an indication that you need to make some changes to your job. But first, you need to consider the wave and field perspectives on your career.

Your career is a wave in that it is a dynamic process. It is unfolding over time; it has a past and a future. Here are some questions that reflect on this dynamic nature:

• Over the course of time—whether it’s a day or a year of work—does your job offer a level of variety in tasks, locations, or people that you find satisfactory?
• Do you make career choices by planning, by seizing opportunities, or by following the path of least resistance?
• Are your past career preparation and experiences a good match for your present job, or would they be a better match for something else?
• Does your job provide opportunities for advancement?
• Are you knowledgeable about future developments in your career field and the job opportunities (or threats to job security) that they will create?
• What have you done or are willing to do to prepare for these job opportunities or to counteract any threats?
• Will your career allow you to deal adequately with future changes in your lifestyle, such as marriage, child-rearing, or retirement?
• If you’re still in school, will you be able to get through the program?

Your answers to this second set of questions (wave-based) may help you plan for ways to remedy shortcomings revealed by your answers to the first set (particle-based). But you should also consider the field aspect of your career, which has implications for both your current situation and your plans.

Your career is a field in that it involves relationships. It occurs in a spatial and interpersonal context. Answer these questions:

• Is your job allowing you to live in a community that satisfies you?
• How do you feel about your workday commute and the amount of travel?
• Do you enjoy the physical setting of your work?
• How comfortable are you with your boss, your co-workers, and members of the public whom you deal with?
• Are you satisfied with the job’s ratio of solitary work to working with or dealing with other people?
• Do you desire more or fewer opportunities for leadership in your job?
• Are you knowledgeable about your industry, not just your job?
• Do you have credentials that have value in your industry (or another industry)?
• Are you known to people in your industry (or another industry) and, if not, do you know how to make yourself known?
• Do you feel good about the extent to which your work contributes to the well-being of other people, of animals, or of the natural environment?
• Do you worry about the possible impact of an on-the-job error on your organization or on other people?
• Does your work create stress between you and your family or community?
• Are you satisfied with the level of prestige that your work confers on you?

If you have read this far, I hope that you understand that you usually need to consider all three aspects of your career to solve any problems that you have detected in it. For example, if your work is too stressful (a particle issue), you need to think about what is causing this stress. It might be another particle issue, such as the necessity of following a restrictive rulebook, but it could also be a wave issue, such as a feeling of being in a dead-end job or worry about future threats to job security. It could also be a field issue, such as concern about making decisions that could bankrupt your employer or the perception that your long hours at work are making you lose touch with your family.

When you evaluate a possible change to your career, be sure to consider the change from the perspectives of all three aspects. For example, if you decide to get a degree or certification to improve your future employability (which you may think of as a wave-related change because it happens over time), consider the particle issues that this will raise, such as how well your skills and aptitudes will match the demands of the program. Consider also such wave issues as how the program’s demands on your time will affect your family relationships or how you can leverage your new credentials to achieve greater recognition in your industry.

Your career affects so many aspects of your life that you need to be multidimensional in your thinking when you assess your satisfaction or make plans for improving your situation. Tagmemics can provide a structure to help you expand your thinking.

Is the World of Work Really Hexagonal?

The Holland hexagon is perhaps the best-known schematic representation of people's work-related interests. This interest scheme is used with the understanding that interests on adjacent angles of the hexagon are more closely related--i.e., more likely for people to share--than interests on more widely separated angles. For example, people are thought to be more likely to have the profile RI than RS. A lot of research has been done to confirm or refute this layout, based on how people have responded to interest inventories that report out the RIASEC Holland codes. For example, I might examine people's scores to see whether their I scores indeed correlate more strongly with their R and A scores than they do with their E scores. Several researchers have done this; a good bibliography of these studies may be found in "The Structure of Vocational Interests," by Itamar Gati.

Keep in mind, however, that the Holland theory is based on the principle of congruence: that people should seek types of work that are good fits for their interests--in terms of tasks, settings, and the personalities of co-workers. Congruence makes sense as a goal only if the world of work can be described in the same terms as people's interests. With regard to the Holland scheme, this means that the opportunities for satisfaction of interests that exist in the world of work should also be describable by the same hexagon.

But are they? I'm not aware of any studies that have tested this hypothesis. To do so, one needs a data set that describes the world of work--that is, it describes a comprehensive set of occupations--in RIASEC terms. Then one can see whether the occupations really do distribute themselves around a hexagonal shape.

Most data sets of this kind provide one-, two-, and three-letter RIASEC codes for occupations. For example, one might consult the Dictionary of Holland Occupational Codes, co-authored by Holland himself. I decided instead to use data from the O*NET database, which rates 974 occupations on the RIASEC interests. This data set is not only more readily available at no cost, but it also provides numerical ratings that represent differences among occupations that are more nuanced than just permutations of six letters. In the O*NET database, two occupations that have the same Holland code might have somewhat different numerical ratings. For example, take Educational, Guidance, School, and Vocational Counselors and Recreation and Fitness Studies Teachers, Postsecondary, both of which are coded S. In the O*NET database, the former has an S rating of 7, while the latter's S rating is only 6.67. In each case, the S rating is so much higher than the ratings for the other five Holland types that the occupation is given only the single S code; nevertheless, the ratings indicate that one occupation is a bit more Social than the other.

I used the numerical ratings from the most recent release of the O*NET database (20.3). When I ran correlations between occupations' ratings on the six RIASEC interests, I found the figures illustrated on the hexagon below:

Among five of the interests--IASEC--the correlations support the prediction that interests will have a positive correlation with interests on adjacent angles and a negative or negligible positive correlation with interests at a distance of two angles--and, furthermore, that correlations between interests at opposite angles will be more strongly negative. But the sixth interest, Realistic, is anomalous; it shows only a negligible (and negative) correlation with the two interests (C and I) that are supposed to be adjacent. To be sure, it shows negative correlations with the opposite interest (S) and the two-angles-away interests (E and A). In any diagram, it should be placed distant from them; but it should also be placed farther from C and I than any other pairs of adjacent angles are distant from each other.

Because Realistic shows no positive correlation with any other interest, a hexagon does not adequately describe its relationship to the other interests. I suggest that if we must use a geometrical shape to describe the layout of the six interests, we need one that allows Realistic to sit away from the others. Perhaps this is best shown as a diagram resembling a frying pan:

 

On the other hand, there is a good argument for using a hierarchical arrangement of the six types, as Gati has proposed in the article cited above. A hierarchical model is based on the assumption that people make a first-cut decision between one group of interests and all other groups, and then make a second-cut decision between one interest and all others within that first-choice group. Gati created groups by observing that certain pairs of RIASEC codes had the highest correlations (in score data from assessments). Here is his hierarchical diagram:

My analysis of data from the world of work (specifically, O*NET data) suggests a somewhat different hierarchy: 

The first cut consists of choosing between R and everything else. The second cut recognizes two clusters (A and S, with a correlation of 0.31; and E and C, with a correlation of 0.27), and I standing off by itself because its best correlation (0.20, with A), is as weak as the E-S correlation.

The frying pan model has one advantage over the hierarchical model: It makes clear that diametrically opposed interests are more distant from each other than interests that are closer on the circumference.

Reduced Prospects for Young Saudis

Last week, The New York Times reported that young people in Saudi Arabia are having a tough time finding jobs. The Saudi government has long been a major employer of its citizens but now is forced to spend less lavishly as the price of oil declines. I had a foretaste of this situation 15 years ago, when I was doing research in the Kingdom.

In 1999, I was engaged by King Fahd University of Petroleum and Minerals to develop a computer-based system for career assessment and information. Eight years before, Saudi Arabia had financed the first Gulf War to the tune of $50 billion. But the Kingdom was not recouping its investment, because the price of oil had been on a generally downward slope ever since the end of that war, and in the previous year the inflation-adjusted price had reached an all-time low. Students at the technology-oriented college paid no tuition and were actually receiving stipends. Therefore, the government was eager to find a way to get students to declare a major that they could complete reasonably fast rather than change majors several times and delay graduation.

I drew on my experience as one of the developers of the SIGI PLUS system at Educational Testing Service in writing my proposal for the system.  Like SIGI PLUS, the Career Oasis system would use work-related values as one of the ways students could identify potentially suitable occupations. But it seemed likely that the SIGI PLUS set of work-related values, which had worked well with American and Australian students, might not be a good fit in the Kingdom. So, as part of the development plans, I included on-site research into the values of Saudi students.

With a committee of faculty and staff, I worked out a set of values to test, based mostly on the content model of O*NET, the career information database developed for the U.S. Department of Labor. For these values, the O*NET database provided ratings for hundreds of occupations. But we decided to add a value that might be important to people growing up in the conservative Islamic culture of the Kingdom. After some discussion we defined the value as “not being in situations that break with norms, customs, or traditions,” and eventually we settled on the name “Conventionality.”

I had a very lively discussion with the committee about whether, in the Saudi context, the value “Conventionality” occupied a conceptual space different from the O*NET-derived “Moral Values.” The latter was defined by O*NET as “not being pressured to do things that go against your sense of right and wrong.” Contributing to the controversy was the fact that the only Arabic words we could settle on to translate “right” and “wrong” were the religious terms “halal” and “haram.” In the end, we decided to let my research clarify whether students perceived a difference, and in fact they did give different levels of support to these two values. On questionnaires that asked the students to weight the importance of the values, they gave Moral Values considerably higher weightings than Conventionality.

What is particularly interesting, however, in light of last week’s Times article, is what the students’ highest-weighted values said about their career ambitions. I surveyed two types of students: those in the orientation year at the (all-male) university, and the children of faculty and staff in the (all-male) high school within the university compound. Here are the top 10 values of the high school students:

Rank	Value	Mean Weight	Standard Deviation
1	Social Status	4.8	1.0
2	Achievement	4.7	1.0
3	Advancement	4.6	0.9
4	High Income	4.6	0.8
5	Moral Values	4.5	1.2
6	Security	4.5	1.0
7	Co-workers	4.2	1.2
8	Creativity	4.1	1.3
9	Social Service	4.1	1.5
10	Conventionality	4.1	1.6

And here are the top 10 of the orientation-year college students:

Rank	Value	Mean Weight	Standard Deviation
1	Moral Values	4.6	0.9
2	Achievement	4.6	0.8
3	Social Status	4.6	0.9
4	Security	4.5	0.9
5	Creativity	4.4	0.9
6	Advancement	4.4	1.1
7	High Income	4.3	1.0
8	On-the-job Training	4.0	1.0
8	Working Conditions	4.0	1.4
10	Conventionality	3.9	1.3

What I concluded from these responses was that—apart from the fairly high ranking of Creativity for both groups—the job that seemed to best fit their preferences was the well-paid, not-very-demanding job of a government functionary. “All they want is a diploma and a job in government,” comments a political science professor at King Saud University quoted in Saudi Arabia: Its People, Past, Religion, Fault Lines--and Future, by Karen Elliott House (Vintage, 2012).

At the time, I had doubts about how well the students’ values could be satisfied by the opportunities available to them. Now, 15 years after I completed my research, one of the main points of the Times article is that although “70 percent of working Saudis are employed by the government,” this kind of job is now much less available to young people than it has been in the past. “With oil revenues crashing and the numbers of young people reaching the work force growing by the day, those jobs have become harder to get as the government cuts costs and pushes Saudis toward the private sector, where job security and salaries are lower on average.”

This economic trend raises troubling questions about the future stability of the Kingdom. Seventy percent of the population is under age 30, and 250,000 reach working age each year. Some workplace conventions are changing–it is now easier for women to enter the work force—but at the same time, it is questionable whether young people have developed a better work ethic than the older generation. As a result, some private-sector employers have resisted the government’s pressure to hire Saudis rather than guest workers.

The social contract that underpins the Kingdom is that the rule of the royal family will not be questioned so long as they enforce a very conservative strain of Islam and keep the citizenry economically secure. The Islamic State now holds out an example of a different model for an Islamic society, and the Kingdom now is draining its deep reserves of cash to prop up the economy. If the values of young Saudis increasingly go unfulfilled, what will become of this key American ally?

My Generic Career Decision-Making Advice

Every so often, I get an unsolicited e-mail from a total stranger, asking me for advice with career decision making.  Following is my response to such messages. If you know someone who is facing a career decision (maybe you), the following suggestions may be helpful:

Thank you for your interest in my work. I’m not a counselor, but I can recommend the exercise that I personally used 35+ years ago when I needed to make a career change. (The exercise is modified from one that was in What Color Is Your Parachute? in the late 1970s.) Set aside about an hour for this exercise.

On a piece of lined paper, draw three vertical lines to create three columns. In the leftmost column, list any role you have played that is at all like work. This can include academic programs and hobbies, because they involve some work tasks. In the middle column, list the major tasks for each role that you played. Put a star next to each task that you enjoyed and were good at. Then, in the rightmost column, try to identify the skills that were required for each starred task. You should start to see patterns emerging: skills that you’ll want to use in your work.

This list of skills may already suggest certain occupations that are worth investigating. But you may also want to visit http://www.myskillsmyfuture.org/. Although it asks you to enter an occupation name, it also works well if you enter the name of a skill. It will suggest occupations to explore. On the other hand, you may want to keep your options open and not narrow down your thinking to an occupation title. Perhaps there’s a niche job out there that isn’t listed in any reference book. I didn’t know there was such a thing as occupational information expert, but that’s what I became.

There are many excellent books and websites, such as the Occupational Outlook Handbook, for exploring occupations and for learning where the economy is growing. However, once you start getting a clearer idea of your goals, there is no substitute for speaking with actual working people. Ask them what a good day is like on the job and what a bad day is like. Ask them how they got into their field and what they would recommend for someone starting now. Ask them where their field is offering the best opportunities.

A lot of career advice also is available from education and training providers, but you must be wary of recruitment pitches, which may be deceptive. Working people can steer you toward the best entry routes and away from the programs that run up debt with little payoff.

If you are shy or introverted, it can be difficult to do the networking that I am suggesting, but you must force yourself to overcome your hesitation. Set a goal of x number of contacts per day. If you make it clear that you are only after information, not a job opening, people will usually be very open and helpful.

Good luck with your career decision making. I hope you’ll write back sometime in the future, when you have made some progress.

Cheers,
Laurence Shatkin, PhD

This Year’s Biggest Changes in Outlook

Early last month, the Employment Projections office at the Department of Labor released its projections for the decade from 2014 to 2024. Later in the same month, the BLS released the text of the Occupational Outlook Handbook (OOH), which was based in part on those projections. Both of these resources are updated every two years, and I thought you’d be as interested as I am in seeing which occupations have the forecasts that are the most greatly revised from the previous update.

The economic models that BLS uses are not foolproof. Sometimes new data comes in that makes the economists at BLS realize they have significantly overestimated or underestimated the growth an occupation can expect. The outlook may change for many reasons, such as new developments in technology, international trade, consumer tastes, or the formulas Medicare uses in reimbursing health-care providers. For an understanding of what may have changed, I find it useful to look at the “Job Outlook” section text of the OOH statement (article) about an occupation, comparing the wording in the previous edition to the wording that appears there now. (You can make the same comparisons by looking at the previous OOH edition stored in the Wayback Machine site.) But often it’s hard to find a good explanation of what accounts for the revised forecast.

A useful example is Wind Turbine Technicians. This is the occupation with the greatest increase in its projected growth: from a formidable 24 percent growth projected for 2012–2022 to an amazing 108 percent projected for 2014–2024. However, the OOH outlook wording has changed very little between the previous edition’s statement and the current edition’s. The major difference is that only the previous edition has this wording: “In addition, the Renewable Electricity Standard calls for 25 percent of U.S. electric power generation to come from renewable sources by 2025, which should further drive employment growth.” Although the new edition doesn’t mention the Renewable Electricity Standard, presumably this commitment is continuing to drive growth, but it’s interesting to note that the number of states with this standard in place has not increased over the past three years—both then and now, it came to 29 states, the District of Columbia, and two U.S. territories. A change that may be more relevant to the revised forecast appears in the wording regarding offshore wind turbines. The current edition lacks a cautionary sentence that appears in the previous edition: “However, the high cost of building wind towers in the ocean may inhibit new offshore projects from being approved.” Still, I wonder whether the cost of building offshore turbines has fallen enough to make this sentence no longer necessary.

I don’t want to make too much of this apparent disconnect between the greatly changed numbers and the mostly unchanged prose. The outlook section notes that this is a very small occupation (in fact, employing only 4,400 workers in 2014), so the sextupling of projected new job openings, from 800 to 4,800, still does not represent a large number of new opportunities.

Something similar seems to have happened with another small occupation, Forensic Science Technicians. In the past two years, its ten-year job-growth projection has soared upward from 6 percent to 27 percent. However, the OOH outlook section has changed little from the previous edition. In fact, the main difference is that only the latest edition offers this advisory sentence: “Larger police departments will be more able to staff full-time forensic science technicians, but they, too, may face budget constraints.” Again, both editions note that this is a very small occupation (with 14,400 workers in 2014), so relatively small changes in the economy can cause a large change in outlook without actually creating a comparably large number of new jobs.

Not all the occupations with greatly changed forecasts were those with small workforces. For example, Personal Care Aides (1.8 million workers) had its growth projection cut almost by half: from 49 percent to 26 percent. Yet, again, the text of the OOH outlook section shows almost no revision, except for the removal of the word “companionship” (as one of the functions of the occupation) in two places and the removal of this paragraph: “Clients often prefer to be cared for in their own homes, rather than a home care facility or hospital. Studies have found that home treatment is frequently more effective than care in a nursing home or hospital.”

Another large occupation with a big change in forecast is Market Research Analysts, which was projected to grow by 32 percent for 2012–2022 but only by 19 percent for 2014–2024. In the wording of the OOH outlook section, there is one hint of a reason for this change. The following sentence was cut from the current OOH: “Rapid employment growth in most industries means good job opportunities should be available.” This deletion reflects the overall downward forecast for job growth: The projection for all occupations changed from 10.8 percent to 6.5 percent. I compared the old projections with the new ones and found a mean (unweighted) change of -5.5 percentage points.

Nevertheless, for occupations that had greatly changed forecasts, I would appreciate a better indication in the OOH outlook section of what factors have changed expectations.

Here is a list of the 20 OOH occupations that had the greatest revisions (either upward or downward) in their projections for job growth.

Occupation	Projection for  Job Growth (Percent)
	2012– 2022	2014– 2024
Wind Turbine Technicians	24.5	108
Diagnostic Medical Sonographers  and Cardiovascular Technologists  and Technicians, Including Vascular  Technologists	38.8	0.2
Market Research Analysts	31.6	0.2
Nurse Anesthetists, Nurse Midwives,  and Nurse Practitioners	31.4	0.3
Geographers	29	-1.6
Mental Health Counselors and  Marriage and Family Therapists	29.1	0.2
Skincare Specialists	39.8	12.1
Insulation Workers	37.6	13.3
Medical Equipment Repairers	30.3	6.1
Political Scientists	21.3	-2.3
Meeting, Convention, and Event Planners	33.2	9.9
Personal Care Aides	48.8	25.9
Software Developers	21.9	0.2
Health Educators and Community  Health Workers	21.5	0.1
Surveying and Mapping Technicians	13.5	-7.6
Radiologic and MRI Technologists	21.2	0.1
Pest Control Workers	19.7	-1.2
Forensic Science Technicians	5.8	26.6
Nursing Assistants and Orderlies	20.9	0.2
Bill and Account Collectors	14.7	-5.6