Yustina Saleh, Director, Labor Market & Demographic Research, New Jersey Department of Labor & Workforce Development, draws on the O*NET database to support economic progress. New Jersey's economic revitalization projects need solid labor and workforce development research throughout the proposing and planning stages. The State calls on Yustina to design research, find data, create models, and crunch numbers. Her work enables revitalization projects to get off the drawing board, based on sound assumptions, hypotheses, and projections. For Yustina, O*NET is a must-have tool.
A fine demonstration of how Yustina's work is critical to economic revitalization projects is the Fort Monmouth (New Jersey) Reuse & Redevelopment Plan. Fort Monmouth is an 1,100+ acre Army installation located about a mile from the Atlantic Ocean and surrounded by Eatontown, Tinton Falls and Oceanport. Fort Monmouth was selected for closure by the Base Realignment and Closure Commission (BRAC). The Department of Defense estimated that the closure would cause the loss of 9,737 jobs. The Fort Monmouth Revitalization Planning Authority has been planning and managing the redevelopment of Fort Monmouth, including examining existing employment conditions and developing assumptions regarding employment growth. Enter Yustina to answer the myriad employment and workforce development questions that emerge in planning the area's economic revitalization.
What occupations is the area's workforce employed in? What skills, abilities, education and training do those workers have? We need to attract employers, but in what industries and occupations, to leverage the workforce characteristics we have? What does the local workforce lack in terms of those occupational dimensions? What training will they need to become successfully employed with the employers we attract? Using the data in the O*NET database goes a long way to help answer those questions.
"I established that in the Fort Monmouth area we have a highly trained workforce," Yustina explained. "So many workers have masters and Ph.D.s. In Phase 1, I looked at staffing within a 10-mile radius. I took the Occupational and Employment Statistics (OES) data (of the Bureau of Labor Statistics) and saw the industry clusters that people are working in here, as well as the wages they earn. That occupational data ties into the data in the O*NET database. I learned the distribution of workers among SOC Codes. I began to quantify the economic value of jobs in those workforce segments. Then the O*NET database gives me the ability to list the skills, abilities, knowledge sets, training and education that we have in the Fort Monmouth area. I can quantify how much of each of these characteristics we have here, because I know how many of each worker we have in each occupation, and what the characteristics of each occupation are.
"But I don't want just a dump of the database," Yustina further explains. "I want to work with finer factors in my model. For example, the abilities of workers in some of these Information Communication Technology cluster occupations are more important than skills. Many of the required abilities are more like what we used to call soft skills, rather than the technical skills. I can assign a stronger weight to abilities because their importance factor is captured in the O*NET database. Also, I can assign a weighting point value for frequency and level of skills and abilities, because even factors that fine are in O*NET." Yustina's work benefits greatly from the O*NET Center's enhancement of the database to include importance, frequency, and level information for occupations' tasks, knowledge sets, skills, and other factors. These ratings inform weight values in her models.
Yustina's work makes it possible to understand what workforce the Fort Monmouth area has to work with. Her research results inform planners what industries and occupations to attract to the area. But not all the information she would like to have is gathered. "It's not possible to do a definitive skills gap analysis," she points out. "I know in a broad sense what we have, and I can determine what we would need in terms of KSAs (knowledge sets, skills, abilities), if a particular company came here, if we knew how many positions they would have in which occupations. What we don't know is the specific specialties that actual, individual people have. We don't know, for instance, exactly what their BAs are in."
True, all the information that Yustina wishes for is not sitting there. But Yustina has more tools in her box than OES and O*NET data. "Yes, I have another trick. I use the New Jersey customized training data. The State gathers data reporting how many people, by employer, have been trained in which skills. Gathering this data is part of the effort to foresee skills gaps and develop a plan to fill them. Studying this data up against O*NET data about required skills, abilities, etc., gives me clues about how many workers have gained which KSAs, which occupations require which KSAs, when, where and with what frequency training in those KSAs occurs, and other insights. Most states, if not all, have such a customized training database."
Yustina's life isn't exclusively numbers. She enjoys devoting every minute she can to three-year-old son Matthew. And she burns midnight oil finishing her dissertation for a doctorate in Political Science, specializing in International Relations, from Rutgers.
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