Where I mix career information and career decision making in a test tube and see what happens

Friday, December 12, 2014

Two Very Hot Careers

At Ivy League colleges, the most popular on-campus interviews have been for two careers: consulting and finance. By consulting, I mean specifically work for management analysts hired by consulting companies such as Ernst & Young and Accenture. Finance covers a large and diverse industry, but the focus of the on-campus interviewing has been mainly on Wall Street jobs.

Why are these jobs so popular? Probably the main draw is that they pay very, very well. ManagementConsulted.com estimates that recent bachelor’s graduates average a base salary of $50,000 to $65,000 in their first year on the job, with signing bonuses of $5,000 to $10,000 and a similar level of extra compensation in the form of relocation reimbursements and year-end bonuses. As for finance, a 2012 survey by the National Association of Colleges and Employers found bachelor’s grads earning an average of $52,800 as their base salary; the middle 50 percent had salaries ranging from $40,800 to $62,000.

The outlook for both of these careers is good, although both are sensitive to ups and downs in the economy. Right now, the economy is on an upswing, so hiring is brisk.

However, competition for jobs is intense, partly because the pay is so good and partly because both jobs take on smart college graduates who don’t necessarily have a background in business coursework. They don’t hire just any smart graduate, however. They want people who have a high level of energy, who can think quickly in numbers, who can express a reasoned conclusion confidently, who are personable, and who fit into the corporate culture—which can vary greatly among employers.

I am particularly aware of these entry requirements because I recently finished updating two guides to interviewing for these careers: Vault Guide to Finance Interviews and Vault Guide to the Case Interview. I was not the original author of either of these books, but I revised them to reflect current hiring practices and the current state of the industries.

For both careers, the on-campus interviews serve as a first cut to eliminate candidates who obviously are a bad fit. With a few quick questions, interviewers can identify candidates who are not good at thinking in quantitative terms. Some behavioral questions, on topics such as summer jobs, can eliminate candidates who have never worked in a business setting. Still other candidates fall by the wayside by responding poorly to timeworn interview questions; for example, when asked “Tell me your greatest weakness,” they may make the mistake of saying they have no weaknesses.

The candidates who make it past these hurdles are the ones who are invited to corporate headquarters (or a large office), where they often experience a “superday” of back-to-back interviews, perhaps capped by dinner. Would-be consultants, in particular, are grilled in this way. Over the course of the day, the interviews typically progress from conversations with low-level workers, where the focus is on technical issues, to meetings with the higher-ups, where the emphasis is on how the job candidate fits in with the corporate culture. Candidates for finance jobs are less likely to get such a thorough vetting.

For both kinds of jobs, it’s common for job candidates to be asked to make “guesstimates.” For example, they may be asked to estimate how many ping pong balls would fit inside a 747 jetliner, how many diapers are sold each year in the United States, or how many windows there are in Manhattan. Questions of this nature help determine whether job candidates have a rough awareness of the business environment (such as the population of the United States), an aptitude for mental calculations, and the ability to think on their feet.

In addition, interviewees are often asked brain-teaser questions, such as “Why are manholes round?” (a question that originated at Microsoft) or “If you pulled in the anchor of rowboat floating on a lake, would the water level in the lake rise, lower, or stay the same?” These questions get at the jobseeker’s creativity and logical thinking.

Wednesday, November 19, 2014

Conspiracy Theories About Jobs Numbers

Every month, the Labor Department releases figures on the current state of the economy, and every month, without fail, malcontents take to the media to say that the numbers are phony. For example, Paul Singer, a hedge fund billionaire and prominent donor to Republican candidates, recently wrote to his investors, “Nobody can predict how long governments can get away with fake growth, fake money, fake jobs, fake financial stability, fake inflation numbers and fake income growth.”

If you have read my books, you know that I rely heavily on data from the U.S. Department of Labor, so it’s obvious that I don’t share Singer’s skepticism. The data analysts at DOL are career civil servants without a stake in enhancing the reputation of whoever happens to be in power. More important, if there were a vast conspiracy to conceal the true state of the economy, surely someone would play the Edward Snowden role and blow the whistle.

It’s true that the unemployment figure does not indicate the actual percentage of people out of work, because it covers only those who are looking for work and ignores those who have given up. But how many times does the public need to be told this? The Labor Department never pretended otherwise. The numbers are what they are.

Last week, a friend of mine whom I have known since seventh grade pointed out an example of the absurdity of the conspiracy theorists. He wrote on Facebook,

You may have heard about the jobs report that came out last week. The mainstream media generally received it as good but not super—248,000 jobs added (200,000 is order-of-magnitude break-even). Now, this is seasonally adjusted, and October is a strong month for jobs, so it was adjusted down, by a lot, in fact—800,000 or so. If the adjustment formula from last year had been used, growth would have been around 100,000 more. So sure enough, the daily stock market letter I look at has rumblings about government fraud to report the low number. The logic is that acknowledging the true extent of expanding employment would have undercut the case for low interest rates.

He goes on to note another competing conspiracy theory, regarding the other number that was reported—the unemployment percentage:

On the other hand, following links from the newsletter, I find another deep thinker saying that the reported unemployment rate is too low because of fraudulent underestimation of the potential work force. The reason for that fraud would be to minimize the appearance of troubles. So is the current employment picture better or worse than the government is telling us?

As my friend observes in conclusion, these market-watchers accuse the government of “two separate conspiracies working at cross-purposes.” Surely the government can’t be lying to make the economy look both better and worse than it really is.

Writing in The New York Times, Floyd Norris acknowledges that sometimes the reported economic indicators are inaccurate, but this is not because of a conspiracy to make the administration in power look better. Rather, it’s because when Labor’s economic analysts adjust figures, they tend to extrapolate from current trends. If the economy reverses direction, this tendency can cause economists to get the numbers wrong. When the economy goes into free-fall, they may overstate performance, but when it bottoms out and starts to improve, they may understate the situation. He gives the example of a 2012 Twitter comment by Jack Welch, the former chief executive of General Electric, who said that the reported decline in unemployment at that time was “unbelievable.” (This was in October of a presidential election year.) In fact, the figures later had to be readjusted to reflect the fact that the emerging economic recovery was actually more rapid than the initial figures indicated. (Incidentally, following Welch’s comment on Twitter, several other messages pointed out Welch’s reputation for manipulating the numbers reported for GE Capital.)

Norris recommends skepticism in situations where there are “rapid changes in any indicator, particularly if other indicators do not show similar changes.” But he cautions that we should “separate reality from ideology.”

Wednesday, November 12, 2014

When Robots Create a Need for Human Workers

Yesterday a Facebook friend of mine wrote about an “eerie and creepy” experience. An advertisement had just appeared in the margin of the Facebook page she was reading, showing a tee-shirt with the lettering, “Just a California Girl in a New Jersey World.” It is no coincidence that my friend is a native of California and now lives in Flemington, New Jersey. Facebook obviously sold this user-profile information to advertisers, one of whom found a way to develop a highly personalized product.

But my friend did not buy the tee-shirt, and if enough other targets of this pitch find their personalized tee-shirt unappealing, the manufacturer will lose money on the ad campaign (plus the costs of tooling up to produce the tee-shirts; the manufacturer surely doesn’t have an inventory of shirts for every possible two-state match-up). What this tells me is that although Facebook’s data-gathering (a robotic function) makes it possible to create highly personalized products, the actual creation of products that people will buy remains a human function. In the brave new world of Big Data, human creativity is still needed to make a sale.

Something very similar became clear in this month’s congressional elections. As The New York Times pointed out,

Modern political campaigns home in on their key voters with drone-like precision, down to the smallest niche — like Prius-driving single women in Northern Virginia who care about energy issues. They compile hundreds of pieces of data on individuals, from party registration to pet ownership to favorite TV shows. And they can reach people through Facebook, Pandora, Twitter, YouTube or cable television.

The only problem: They do not have enough messages for them all.

The Big Data era of politics has left some campaigns drowning in their own sophisticated advances. They simply cannot produce enough new, effective messages to keep up with the surgical targeting that the data and analytics now allow.

…Or, as Joe Rospars, the founder of the Democratic digital agency and technology firm Blue State Digital, put it, “The science is ahead of the art.” An analytics team can help a campaign make “a much more targeted buy,” he explained, but that alone will not offer a particularly efficient return on investment if the ad is still “just a white guy in a suit.”

As a result, the people who design the advertisements for electoral campaigns end up trying to tease out certain large slices of voters with something in common, such as “soccer moms” or “angry white males.” The campaigns do not have enough creative people to craft the highly personalized ads that should be possible given data-analysis tools.

On a recent broadcast of NPR’s “On the Media” (sorry, I can’t remember which date), I found another example of the limitations of technology. You may remember that YouTube moved quickly to take down the videos of the recent beheadings in Syria. You may not know that YouTube takes down many other videos because of pornographic or sadistic content, and so do most photo-posting sites, such as Flickr and Photobucket. Computer technology makes it easy to post photos and videos, and to make them searchable by keywords, but the explosion of content that has appeared on the Web requires human eyes to decide which photos and videos violate site policies.

One indication of how subtle the human decision-making must be is the fact that photo sites prefer to offshore this work to the Philippines rather than to India, where the workers are lower-paid. The reason is that Filipino workers have a better understanding of American culture and therefore can decide whether (for example) a shot of someone in a bikini is too revealing, whereas an Indian worker might reject every bikini shot.

The takeaway is that technology sometimes creates a need for more human workers, and not just those employed in creating, manufacturing, or repairing the technology. It sometimes creates opportunities for work that requires great creativity or subtle judgments. Robots may be driving cars, but they are not yet metaphorically in the driver’s seat.

Wednesday, November 5, 2014

High-Paying Occupations with a Few Superstars

My most recent book, Your Guide to High-Paying Careers, is my first for my new publisher, Meyer & Meyer. Here is a brief excerpt, giving you a peek at some occupations where the sky is the earnings limit--for a few outstanding workers.

Have you ever fantasized about winning the lottery jackpot? Some occupations have a few jackpot positions that pay extremely well. You’re certainly familiar with movie stars who earn the millions that most struggling actors can only dream about. The radio plays songs by musical superstars who bring home more than the combined earnings of 100 bar bands.
Among the occupations included in this book, some offer extremely high earning opportunities for a relatively small subset of workers. You can’t tell which occupations these are by looking at the median wage figure or even at the range of the middle 50 percent of earners. But I have a way of identifying these occupations for you.

Imagine this situation: Five friends are sitting around a restaurant table having lunch. They all earn roughly the same amount:






For the group, the median earnings figure is $52,000 (half earn more, half earn less). If you calculate the mean earnings (add them all up and divide by 5), you’ll get the same figure, $52,000. But let’s say Mike gets a phone call telling him that he was just promoted to vice president and is now earning $150,000. Note that the median for the group has not changed, but the mean has jumped to $71,200. Because there is now one superstar earner in the group, the mean is now 37 percent higher than the median.

For the 173 occupations in this book, I calculated the difference between the median earnings and the mean earnings. (The BLS reports both figures.) The following list includes those occupations in which the mean is at least 15 percent higher than the median. They are ordered by how much the mean exceeds the median. For each occupation, I list both earnings figures.

What might cause you to be among the highest of the high-paid workers? Here are some possible reasons:
  • You have an outstanding talent. Maybe you were born with some ability that few other people have.
  • Through hard work or study, you have developed outstanding skills. Whether these are physical or mental skills, they can put you ahead of the pack.
  • You use mass media to reach a very large paying audience. Think about how much more a TV chef can earn compared to a one-restaurant chef.
  • You find a specialization or a geographic location that causes you to be in high demand but have no competition. This advantage may be only temporary, but you may be able to command high earnings as long as you are the go-to person for your narrow field or community.
  • You go into management.
Whether you look at the following list as a collection of nice fantasies or as possible roadmaps to your future, the list makes for interesting reading.

High-Paying Occupations with a Few Superstars

Median Earnings
Mean Earnings
Securities, Commodities, and Financial Services Sales Agents
Agents and Business Managers of Artists, Performers, and Athletes
Real Estate Brokers
Personal Financial Advisors
Producers and Directors
Health Specialties Teachers, Postsecondary
Advertising and Promotions Managers
General and Operations Managers
Art, Drama, and Music Teachers, Postsecondary
Health Diagnosing and Treating Practitioners, All Other
Loan Officers
First-Line Supervisors of Non-Retail Sales Workers
Geoscientists, Except Hydrologists and Geographers
Biological Science Teachers, Postsecondary
Art Directors
Business Teachers, Postsecondary
Financial Analysts
Law Teachers, Postsecondary
Area, Ethnic, and Cultural Studies Teachers, Postsecondary

Wednesday, October 29, 2014

Revisiting My Predictions for the President’s Stimulus Plan

These days, it’s easy to forget the excitement that many people felt when President Obama was inaugurated. Many businesses attempted to capitalize on this historic moment by issuing commemorative merchandise, such as plates and tee-shirts bearing Barack Obama’s image. It was also a time of recession, and many people were wondering what relief they could expect from the incoming president’s promised stimulus plan. As a result, the editors at JIST Publishing thought this would be a good time for me to write a book that eventually was called Great Jobs in the President’s Stimulus Plan and that had a cover photo showing President Obama looking thoughtfully into the distance.

Now, almost six years later, I thought it would be a good time to revisit what I wrote in that book and to see how well the passage of time has borne out my predictions. So, for the 100 occupations I featured in the book, I am now looking at the BLS data regarding their workforce sizes in 2008 and 2012. Did these occupations actually increase in size over this period of economic recovery?

I regret to say that the occupations actually shrank in workforce size, by an average of 4.7 percent. However, I must point out the workforce size of all occupations shrank by almost the same amount: by 3.7 percent.

Where did I—and the economy—go wrong? First, I may have chosen some wrong occupations because at the time I wrote the book, a few days before the inauguration, the stimulus plan existed only in outline form. It had not been presented to Congress, let alone held to a vote. I made my best guesses about which occupations were likely to benefit, based on the industries that were targeted in the proposed legislation.

More important, the American Recovery and Reinvestment Act itself may have been insufficient to boost the economy, not to mention the specific occupations I focused on. This is the argument of Paul Krugman and some other economists. At the time the ARRA passed, he wrote, “Officially, the administration insists that the plan is adequate to the economy’s need. But few economists agree. And it’s widely believed that political considerations led to a plan that was weaker and contains more tax cuts than it should have—that Mr. Obama compromised in advance in the hope of gaining broad bipartisan support.” More recently (February 20 of this year), Krugman is conceding that “most careful studies have found evidence of strong positive effects on employment and output.” He contrasts our economy to that of the Eurozone, where nations that were forced to impose fiscal austerity—the opposite of stimulus—have fallen into double-dip recessions. Nevertheless, although the ARRA arrested the economy’s downward slide, saving many jobs, it did not create new jobs sufficiently to overcome the losses of the recession within a few years. As Krugman expresses it, “The U.S. economy continued to perform poorly—not disastrously, but poorly—after the stimulus went into effect.”

It is also worth asking whether 2012 is too soon to evaluate the success of the ARRA. Some economic effects take years to appear—for example, the results of funding for scientific research and for vocational training and other kinds of education. Also, some stimulus spending took years to be disbursed, so any results would not have been visible in 2012. A noteworthy example is health information technology, now one of our fastest-growing industries. Stimulus funding for health IT was not disbursed until 2011. It’s true that only 2 percent of expenditures remained to be awarded at the end of 2012, but for the Department of Energy, 15 percent of allocated funding had still not been awarded at that time.

I conclude that my recommendations in that book were not as misguided as they might appear at first. Economic stimulus measures and individual workers’ careers both require many years to bear fruit.

Wednesday, October 22, 2014

The Outlook for Wind Turbine Technicians

Green careers are attracting a lot of interest, but it can be difficult to find reliable figures for projected growth and even current employment. Here is an update about wind service technicians, based on the best figures I was able to find.

Back in 2009, I researched several green occupations, including this one, for a special supplement to the Occupational Outlook Handbook that I was preparing for the publisher JIST Works. At that time, the Bureau of Labor Statistics was not providing any figures for this occupation—neither for current nor projected employment. So I had to make my own calculations from data I found in government and industry sources.

The BLS now does report employment figures for wind service technicians. Last December, for example, the BLS released an estimate that 3,200 people were employed in the occupation in 2012 and that 4,000 will be in 2022, an increase of 24 percent. The BLS also estimated 800 job openings per year.

To try to get a sense of the current level of employment, I looked at the estimates of the Wind Energy Foundation. Understand that this organization exists to promote wind power, but we can avoid most possibility of boosterism if we focus on the current state of the industry rather than on projections of the future. The Wind Energy Foundation estimates total U.S. utility-scale wind-power capacity, in the second quarter of 2014, at just under 62,000 megawatts. If we assume that average turbine capacity is 2 megawatts (a fairly conservative figure) and that one operations and maintenance worker is needed for each 7 turbines (which was the ratio when I first researched this occupation), the number of these workers should be about 4,200. If we assume average turbine capacity of 3 megawatts, this still accounts for 2,950 workers.

These two estimates of workforce size bracket the 2012 estimate made by BLS, but it seems reasonable to expect that the occupation would have grown considerably in the past two years. Note that these figures apply only to operations and maintenance workers. Many other wind turbine technicians surely are engaged in constructing new capacity. In fact, again according to the Wind Energy Association, 14,000 megawatts of wind power capacity was under construction during the first half of 2014. So the occupation probably has expanded on roughly the scale projected by the BLS.

The wild card in projections for wind power capacity—and, therefore, employment of technicians—is whether or not this country will invest heavily in offshore installations. The most reliable winds are found there, and some industry observers believe that this coming year will see the beginnings of offshore wind-power projects, despite their high cost relative to dry-land installations.

One advantage that wind turbine technicians enjoy in the job market is that often they face little competition. This is partly because the technology is new and expanding rapidly, so not many trained workers are entering the job market compared to the demand for their services. But another reason is that many people do not like working at great heights and in confined spaces.

Tuesday, October 14, 2014

Am I Using a Credential Fraudulently?

You may notice the “PhD” following my name on some of my book covers. I do hold a doctor of philosophy degree (earned, not honorary), but my use of these letters brings up an interesting question of when it is—and is not—appropriate to use work-related credentials. This issue is particularly timely because so many people are now working (or seek work) in fields that they did not prepare for formally.

What raised this issue for me was a question in “The Ethicist” column of last Sunday’s New York Times Magazine. The query, posed by someone whose name was withheld, was this: “A Pilates-certification-program teacher uses the credentials ‘Ph.D.’ after her name in connection with the course description on the studio’s website. However, her degree is in finance, which is never mentioned on the site. Is this acceptable?” The core of the answer from columnist Chuck Klosterman was, “Anyone who includes an academic designation alongside the description of a class she’s teaching is implying that these things have a material connection. She is actively trying to make people misinterpret what she has to offer.”

I admire Chuck Klosterman for his often subtle parsings of ethical issues, and I believe he was correct in making this judgment. So after reading this column, I had to ask myself whether I am using my PhD credential ethically. And as I thought about how to answer this question, I realized that many people deal with a similar issue. Because of my interest in careers, I often ask people how they got into the line of work they presently are doing, and a great many of them describe a crooked career path that did not include the “appropriate” academic training.

As for me, it’s true that I am not teaching Pilates or any other course, but it could still be argued that my use of “PhD” on my books implies what Klosterman calls “a material connection” between my education and the contents of my books. And the fact is that although my books are about careers, none of my degrees is in economics, counseling, psychology, or education. My degrees are all in English literature. (In case you’re curious, my specialization was pre-Shakespearean drama, and my dissertation was about morality plays.) But the particular focus of my academic work, literature, doesn’t really matter. What’s important is that in preparing for and writing my dissertation, I learned how to do research and write about it, and these skills do have a material connection to the work I do now.

You might argue that research and writing skills are necessary but not sufficient qualifications to write about careers; the writer should also be well-informed about career development issues. I often joke that getting a degree in English guarantees that you’ll become informed about career development issues, and in my case there was some truth to this statement. Not long after I got my degree, it became obvious that I was not going to find a permanent job teaching at a university, so I had to decide what else I was going to do with my life. I read What Color Is Your Parachute? and did all the exercises. From my self-assessment, I realized that teaching was not what I liked or was especially good at; instead it was researching and writing, as I had done for my dissertation. The first opportunity that came my way for a job involving these tasks was developing career information for Educational Testing Service. This job led to a 19-year stint. During that time, I engaged in what amounted to an apprenticeship in career development theory, with Martin R. Katz as my mentor. In that setting, the world’s biggest testing organization, it was also inevitable that I would learn a lot about assessment. At Trenton State College (now The College of New Jersey), I took three graduate courses from the counseling master’s program: an introduction to counseling and two educational statistics courses.

Therefore, the credentials I bring to my work are a combination of formal education (mostly the PhD) and on-the-job training (my apprenticeship at ETS), and I try to mention both of these elements on my book covers: The “PhD” appears on the front cover after my name, and on the back cover is a statement that I have been working in the field of career information for more than 30 years.

Many people, like me, are working in fields where their credentials consist, at least in part, of informal on-the-job learning. But most people present their credentials to the world mostly through a business card, which does not accommodate as much text as the back cover of a book. People who work in fields where certification is available as a credential have the chance to put certain relevant initials after their name on the card, but this is not an option in most fields.

If you are working in a field where you do not have formal credentials—perhaps because they do not exist—I would advise you to be hesitant about putting a degree after your name. But I would give you a lot of leeway for arguing (as I do here) that your degree really is relevant to your qualifications.