Tuesday, March 31, 2015

A Tribute to Martin R. Katz

As I was growing up, I often thought of making a career in writing, but it never occurred to me to write about careers. This career path, which has been so rewarding to me, I owe to Marty Katz. He died March 17, age 98.

In 1979, he hired me to develop career information for the SIGI program at Educational Testing Service. The System of Interactive Guidance and Information was his brainchild and was one of the pioneering systems in the early days of computer-based career development. His ideas were so far ahead of his time that, initially, the available computers were incapable of storing the amount of information necessary to make the system work. He proposed using a carousel of slides to display the fixed information (such as occupational descriptions) so that the computer’s limited storage would be freed up for the interactive textual elements. He also conceived a radical layout for the display, making it a mosaic of text blocks rather than a solid page of text.

But SIGI was more than a technological breakthrough. It also was the implementation of his unique values-based approach to career development. Instead of basing career choice on a single domain, such as interests or skills, or encouraging birds of a feather to flock together, he posited that people choose careers in order to obtain rewards that they value. These rewards could be extrinsic, such as high income or prestige, or intrinsic, such as helping others or the opportunity to work in a field in which one has a strong interest. He did considerable research to identify which values are most widely held and most readily understood. In fact, by recording user interactions, he was able to employ SIGI itself as a research tool to gather statistics on values preferences. Besides confirming his selection of values for the system, it enabled him to study values differences between the sexes.

His values-based philosophy of career development represented a break with the theories that were the legacy of the Second World War, a time when national mobilization was more important than individual self-actualization. He also emphasized self-assessment, as opposed to testing—ironically, his employer’s main line of business. His approach was perfectly in tune with the 1960s decade of self-exploration and the 1970s “me decade.”

I did not know or understand any of these ideas when he hired me. Until then, my education had been in English literature and my work experience had been mostly in teaching English composition. I had learned a tiny bit about career development from trying to get my own career started, and especially from reading (and doing all the exercises in) What Color Is Your Parachute? From one of these exercises (a self-assessment), I discovered that I derived the greatest satisfaction and feelings of competence from research and writing. So when Marty advertised a job opening for someone to research and write career information, I applied and submitted a writing sample. He liked my writing and, when I said I hadn’t yet given up on a career as an English professor, he asked me whether I would give the SIGI job three years before moving on. I agreed. Thirty-five years have passed, and in a way I have not moved on yet.

Marty recognized potential in me and served as a valuable mentor. Although for the first two years my work for SIGI was focused almost entirely on researching salaries—using primary sources, such as the salary surveys of professional organizations, and following well-established procedures—in the following year Marty entrusted a new research project to me: developing descriptions of college majors. In its field test, SIGI had asked each college to provide descriptions of the majors they offered. This was a powerful way to help career decision makers with their planning, but the institution-specific information proved to be too costly for subsequent institutional subscribers to develop and maintain. SIGI needed generic descriptions of college majors, a kind of information that—compared to occupational information—was (and still is) very scarce. Marty assigned me a two-year research and development project that not only created a new module for SIGI but also laid the groundwork for the R&D strategies I have used in more recent years for several books—such as my next book for Meyer & Meyer Publishing, Choose Your College Major in a Day. Marty also entrusted me to key in the large amount of text that I was developing. A new text-entry program allowed relatively unskilled workers like me to enter and edit text, if only one line at a time.

In the obituary that ran in The Times of Trenton, you can read a lot more about his achievements, including the 1992 Eminent Career Award from the National Career Development Association. He probably would have achieved greater recognition in his field if he had done more self-promotion, but he seldom spoke at conferences because he was very hard of hearing as long as I have known him. And when he retired, he walked away from all involvement in the field.

He once remarked that he had taught college-level statistics although he had never taken a course in statistics. He said, “Most of what I’ve done has been without special training. I live by my wits.” This statement, with its tone of self-deprecation masking well-earned pride, strikes me as very characteristic of his personality.

Friday, March 13, 2015

Which Boats Get Lifted Fastest by a Rising Tide?

The old saying goes, “A rising tide lifts all boats.” In today’s context, this means that the recovering economy should be improving the lot of all workers. I was wondering, however, whether some boats are rising faster as the tide comes in. In other words, which types of occupations are getting the biggest boost from the improving economy?

I decided it would perhaps be most revealing to look at the places where the tide is coming in fastest—the metropolitan areas that have seen the largest gains in real personal income. Thanks to a dataset from the Bureau of Economic Analysis, I was able identify 20 metro areas in which real personal income increased by more than 6 percent between 2011 and 2012. I then looked at the increases in wage-and-salary occupational employment, for each metro area, over the same time period. Rather than deal with hundreds of occupations, I looked at the increases for major groups of occupations.

Then I computed the correlations between these employment increases for occupational groups and the real-personal-income gains in the 20 fastest-rising metro areas. Here’s what I found:


Occupational Group
Correlation
All Occupations
0.71
Transportation and Material Moving Occupations
0.70
Life, Physical, and Social Science Occupations
0.69
Installation, Maintenance, and Repair Occupations
0.67
Construction and Extraction Occupations
0.59
Office and Administrative Support Occupations
0.57
Computer and Mathematical Occupations
0.53
Business and Financial Operations Occupations
0.51
Management Occupations
0.35
Sales and Related Occupations
0.30
Architecture and Engineering Occupations
0.29
Legal Occupations
0.22
Production Occupations
0.17
Healthcare Support Occupations
0.14
Healthcare Practitioners and Technical Occupations
0.04
Arts, Design, Entertainment, Sports, and Media Occupations
-0.04
Food Preparation and Serving Related Occupations
-0.05
Building and Grounds Cleaning and Maintenance Occupations
-0.09
Protective Service Occupations
-0.11
Community and Social Service Occupations
-0.17
Personal Care and Service Occupations
-0.31
Education, Training, and Library Occupations
-0.33
Farming, Fishing, and Forestry Occupations
-0.34


These results make more sense if you’re aware that several of the 20 metro areas that figure into these calculations are in the oil patch: Odessa, Texas (10.2 percent real-income growth); Midland, Texas (9.6 percent); and Victoria, Texas (6.9 percent); and Grand Forks, North Dakota (7.3 percent). The occupational groups that are growing fastest are those that are important for getting oil out of the ground and moving it to refineries.

It’s also interesting to note that some occupational groups that grew fastest nationwide over this same time period show low correlations to income growth in these metro areas. For example, Personal Care and Service Occupations grew by 5.3 percent nationwide, faster than any other group, yet it grew by only 1.2 percent in these 20 metro areas and shows a negative correlation with income gains there. Farming, Fishing, and Forestry Occupations grew at the same rate nationwide and in these 20 metros (4.4 percent), but it also shows a negative correlation to income gains there. Food Preparation and Serving Related Occupations actually grew faster in these 20 metros (4.4 percent) than nationwide (2.9 percent), but it also shows a negative correlation to income gains there.

These anomalies can be explained partly by the difference between the economies of these 20 metro areas and that of the nation as a whole. But understand that a rising tide of income in an occupation does not necessarily bring a commensurate increase in employment for the same occupation—at least, in the short run. In many occupations, income can rise because existing workers are able to put in longer hours. Eventually, the rising income should attract new workers, but there is always a lag because of barriers to job entry, such as licensure and other credentialing, plus (at the regional level) geographical distance.