Salary Survey Data Trends: IT Jobs

by Lyle Leritz, Ph.D. 3. September 2013 15:03

 

The third installment of Year-to-Year Analysis of Salary Survey Data Trends focuses on Information Technology (IT) positions. The analysis compares salaries submitted to ERI Salary Surveys for 2012 and 2013 reports (both nonprofit and for-profit). For each year, total averages were calculated by job title and included all available data (that is, industry and area breakouts were ignored) to maximize sample size, similar to a national report.

The preliminary dataset included 993 job titles common to reports from both years. The 2012 data included data from 601 unique organizations, while the 2013 data included 578 unique organizations. Titles with fewer than 10 observations in either year were dropped from the analysis, resulting in 171 titles for comparison. In an effort to show meaningful patterns, the job titles were grouped into job families.

While not as ubiquitous as administrative jobs, Information Technology positions are a large and growing part of the national work scene. Typically, IT positions are affected by both sides of a volatile job market with large up and down wage movement relative to other job families. As you can see in the graphic below, organizations reported higher salaries in 2013 for four of the seven computer-based titles, ranging from 4% to 12%. Survey results for Programmer and Systems Administrator both decreased by 9% in 2013. PC Specialist stayed essentially the same.  (Note:  Computer Network Administrator was dropped from this analysis due to a low sample size.)

Similar to last year, survey data for IT positions exhibited a fair amount of variability. While the positive growth was at a similar level to last year, the two drops were noticeably greater. This is not surprising given the technology sector’s tendency to have a fair amount of volatility. Nevertheless, the trend moving forward for this job family appears to be wage growth. However, it is important to keep in mind that typical salary survey methodology does not constrain analysis to person-matched data from year to year (for a number of logistical reasons, including adversely impacting sample size), nor are surveys restricted to the same list of participants.