Workforce Representation in Organizations

Organizations often have a need to know whether the make up of their workforce reflects the population of potential candidates in order to provide an indicator that fair hiring and promotion practices are in place. This is best accomplished by carrying out a comparison of the work force on key characteristics (e.g. race/ethnicity) with the population from which that workforce is drawn and/or with similarly situated organizations.

HumRRO has extensive expertise in assessing organizational representation by making appropriate comparisons to relevant, custom-tailored populations. In fact, HumRRO staff has been conducting representation analyses for the Department of Defense since 1993.

The Population Representation in the Military Services report, submitted to Congress annually, is a reference tool for policy makers and researchers. It contains demographic data describing the Armed Forces, including the Active and Reserve Components of the Army, Navy, Marine Corps, Air Force, and Coast Guard. The information is broken down by enlisted and officer, accessions and members, and active-duty and National Guard/Reserves. Key variables include gender, race, ethnicity and education. HumRRO also designed and developed a website that allows for online access to the data (see http://www.defenselink.mil/prhome/poprep2003/).

Compiling the military data into one document is very useful. However, the most important aspects of the work are (a) identifying relevant civilian comparison groups, (b) monitoring trends in military personnel and civilian data over time, and (c) providing analysis of military representation.

In the Population Representation report, most of the civilian comparison data come from the Bureau of Labor Statistics' Current Population Survey. Additional comparisons are made using data from the National Center for Education Statistics. HumRRO staff have worked with the Department of Defense to identify the most appropriate comparisons. Using age, education, and employment variables, we have defined civilian labor force groups for comparison to the military. For example, we compare active component enlisted accessions to 18-24 year-olds in the civilian population. Virtually all members of the officer corps are college graduates, so the commissioned officer corps (active component) is compared to 21-49 year-old college graduates in the civilian workforce. Although there are subtle differences between some of the civilian labor force groups, this method of customizing the benchmarks for matching the military forces to the civilian population ensures the most accurate comparisons. Another example of HumRRO's experience in workforce representation analysis was a project conducted for the Architect of the Capitol. HumRRO used local area occupation data from the U.S. Census Bureau's Equal Employment Opportunity File. Data were extracted by occupation, so that only jobs represented in the Architect of the Capitol workforce were included in the tailored civilian labor force comparison group. Analyses were performed separately by professional, administrative, technical, clerical, blue collar, and other categories. Because of the large number of blue collar staff working for the Architect of the Capitol, this category was split into skilled crafts and service groups to provide more specific information.

We conducted analyses at the occupation level for the Architect of the Capitol's most populous jobs. HumRRO used a standard deviation analysis, as suggested by the Department of Justice in their Post-Adarand Guidance on Affirmative Action in Federal Employment. Using local area data by occupation, the Architect of the Capitol was able to compare staff characteristics to the relevant labor pool and identify areas of under- and over-representation.

Regularly monitoring workforce representation enables organizations to identify trends and to assess the effects of policies. To best measure representation, comparison groups should be matched to relevant characteristics. With HumRRO's knowledge of civilian labor force data, custom-tailored workforce representation analyses are possible.

For more information, contact:
Dr. Kristina Handy or Research Notes