The Matrix: Customized
Industrial and Occupational Staffing Patterns & Wages
Last year, Research & Planning (R&P) introduced customized staffing patterns as a tool to help understand one resource (Labor) necessary to actively recruit businesses to Wyoming. This year, due to improved data supplied by the Bureau of Labor Statistics (BLS) Occupational Employment Statistics (OES) program, R&P has updated the staffing patterns based on a new survey round and incorporated several improvements. The first of these improvements is that the wage information when provided is both occupation- and industry-specific. For example, a wage given for an engineer in coal mining is different from the wage provided for an engineer working in Government. The second enhancement is that the data from the previous year were compiled from several data sources, but current data are the product of only two data sources both originating from the OES program itself. Lastly, because the OES program provided the data with more detail than last year, the staffing patterns are separated into two distinct aggregations discussed in the following paragraphs.
Occupations by Industry
The first aggregation is similar to last year’s staffing pattern release. The "occupations by industry" tables provide the distribution of occupations within a two-digit industry following the Standard Industrial Classification (SIC) coding system. Table 1 below is an extract from the downloadable acrobat file for SIC 07 (agricultural services). Here's a brief description of the column headings.
Table 1: Extract from occupation_by_industry.pdf
If your community desired to recruit a company that provides agricultural services, Table 1 gives you a rough estimate of the labor necessary. For example, let's say a company was interested in relocating or establishing a business in your city. They question whether they can recruit the skilled labor needed from your community. Table 1 offers not only an estimate of labor supply needed but also the expected wages relative to the nation.
Industries by Occupation
The data fields in Table 2 are similar to those discussed above with the exception of p_in_occ becomes p_in_ind (percent in industry) and the occupation becomes the primary aggregation level. This presentation of similar data adds a new twist, suppose part of your mission is to provide career development advice to prospective college students or the general public. With Table 2 it is possible to advise an individual where their future plans could lead or where their current work experience could earn the greatest wage.
Table 2: Extract from industry_by_occupation.pdf
Data are provided in two formats with the first being two separate acrobat files. These documents are quite large, each exceeding 900 pages. It is anticipated that after downloading these files the industry or occupation desired will be located and only those pages be printed.
The second format is Excel and it offers the advantage of only one file with both tables, drop down menus to select only the occupation or industry desired and the ability to specify the anticipated employment and have the number of individuals needed for each occupation calculated.
Other formats (Lotus and Quattro Pro) were explored for posting and download potential but due to limited capacity these formats were abandoned. We apologize for any inconvenience.