It should be intuitively obvious that take-home pay is a measure of the value an employer puts on the work being done at this place and at this time. In the macro economy, it boils down to the balance between the number of people willing to do some job and the number of employers having a need for the skill level being offered. The balance can be fluid, changing from year to year. Every town once had several shoe repair shops. How many do you see now?
Salary surveys are commonly used by both sides of the hiring table. Many times, though, someone ignores the caveats. The survey depends on statistics, which raises questions about the margin of error; population size, sample size and the number of respondents; and whether they were randomly or self-selected. In the latter case, there’s a tendency for only those making a good buck to respond; the others don’t want to admit they’re getting only chicken feed.
In the ideal world, we’d find a salary survey completed within the past month to better reflect the current economic realities out there. It would be based on a population of multiple thousands and use a truly random sample size sufficient to guarantee a very low margin of error. The respondents would be totally open, truthful people who perform exactly the same work that you’re performing. The questions asked would be of a sufficient quantity and quality that would allow you to apply a multiple regression analysis to yield a meaningful personalized comparison to the numbers printed on your pay stub.
Because such ideality doesn’t exist, we’ve got to gather and digest as many inputs as possible. That’s why this month’s dive into the digital morass we call the Web is in search of practical, zero-cost, noncommercial, registration-free wage and salary resources that might come in handy one day. Remember, we search the Web so you don't have to.
The big picture
If you want a high-level view of the maintenance pay issue, you can take a look down on “Upward mobility,” a 900-word article by Bob Vavra, which is found at www.plantengineering.com/article/CA6519485.html. It offers an executive summary of the results garnered from 1,200 maintenance professionals who participated in a salary survey. Unfortunately, the information here isn’t granular enough to reveal how regional differences, job title and other relevant variables affect the reported pay scales.
On the other hand, in 1996, Sandy Dunn, who lives in Como, Western Australia, got fed up with the lack of industrial maintenance resources he needed to improve things at the plant where he worked. So, in 1999, he launched his own online venture, the Plant Maintenance Resource Center, intending to aggregate links to the materials that plant maintenance professionals need to succeed. As you can imagine, the site has grown during the past nine years and, of course, he conducts a salary survey each year. It’s open to maintenance workers worldwide, but most of the participants come from the United States, a demographic factor that could suggest that the information presented reasonably reflects pay rates where you live. Freely available at www.plant-maintenance.com/survey.shtml, the results include the raw data and are sorted by industry, country, job function, educational level and work experience. You can open the files sequentially to identify trends to help get a better idea of where you stand in the economic arena.
For the West Coast
Those seeking employment need easy access to solid market intelligence about the job situation in the location where they’re searching. The logical place to get that localized intelligence is at the library, or so thought Mary-Ellen Mort, M.L.S., from the Bay Area Library and Information System. This thinking resulted in the online Job Star Central, where Mort is the project director. Although the site has its primary focus on jobs in the metro areas around San Francisco, Los Angeles, Sacramento and San Diego, you’ll find some content that applies to the rest of the country. Pay a visit to the Internet’s West Coast at http://jobstar.org/index.php to explore the “Profession-Specific Salary Surveys” covering more than 50 broad job categories, ranging from accounting to warehousing. Most categories are further subdivided, perhaps by job title, perhaps geography. If you’re dissatisfied with your current compensation or are simply curious about how a career change might affect your take-home pay, you could explore the earnings potential in many other fields of endeavor. Check out winery workers listed under the agricultural category.
Closer to home
One salary survey appears to be focused on the domestic plant maintenance and engineering function. You can find it at www.mt-online.com, where you should click on “Articles” in the top left corner. Then, plug the keyword “$alary” into the search feature. Don’t forget to use the dollar sign as the first character. Your reward will be “2007 $alary $urvey,” a 900-word summary article by Amanda Martyka, assistant editor at Maintenance Technology magazine that appeared in the December 2007 issue. The piece features six graphics that depict the distribution of income, as well as average income as a function of age, education, facility size, industry and job function. The graphics won’t enlarge to a truly readable size when you click on them, so you’d best have eagle eyes or a magnifying glass.
Data mining at the BLS
The data coming out of this next Web site are based on the most recent Occupational Employment Statistics survey from the Bureau of Labor Statistics. Thanks to Jay Verdoorn from Wheatland, Calif., you won’t need to comb through countless pages of numbers to learn what our hired hands in Washington know about the real job market. Instead, you merely need to pay a visit to www.salaryteller.com and enter your criteria. You can find the results in either of two ways. Using the top section of the screen, you can select the nearest major city in your state and any of 22 main job classifications. The next screen requires you to select from a list of job subcategories before you see results. On the other hand, you can use the lower half of the screen to select a state on the first screen, the city on the second, occupational group on the third and occupation on the fourth. In either case, the results are an estimate of the number of people performing that job function and the 10th, 25th, 50th, 75th and 90th percentile salaries.