Southeastern New England Marine Science and Technology Workforce Gap Analysis
By Salvador Balkus
Recent research by the UMass Dartmouth Public Policy Center has demonstrated that Southeastern Massachusetts, also known as SENE, has been largely excluded from the thriving Greater Boston innovation economy. Meanwhile, the traditional maritime-related economic drivers of the region have encountered many economic challenges in recent years. As a result, UMass Dartmouth has risen to the task of developing a Southcoast Blue Economy Corridor in order to strengthen the region’s maritime sector. New technologies in blue economy-related industries will be imperative to the success and revitalization of the maritime sector in the region, and as such, an initial goal of this project is to conduct a comprehensive assessment of the Marine Science and Technology (MST) sector in and around the region. This portion of the project has been taken up by the Public Policy Center.
Working at the Public Policy Center with support from the Office of Undergraduate Research, I spent this summer completing an important component of this research project: conducting a gap analysis for the SENE Marine Science and Technology regional workforce. My job was to analyze the occupations most relevant to the sector, create a profile of the “high priority occupations” which are critical to the operations of MST firms and pose a great challenge to attract and hire, and determine the gaps between the educational programs currently offered in SENE and the education necessary for MST workers. To analyze the Marine Science and Technology sector workforce, I relied on an inventory of Marine Science and Technology firms, survey data, and key informant interview notes from the Public Policy Center, as well as economic data from Emsi, an economic modeling software. This workforce assessment will help the university inform policy decisions and succeed in their endeavor of successfully creating a Blue Economy Corridor.
NAICS, which stands for North American Industrial Classification System, is a standardized, code-based classification for industries. My first task was to determine an appropriate NAICS-based definition of the Marine Science and Technology sector that would include all of the private MST companies in the region. To do this, I obtained two different lists of NAICS codes. The first was compiled by the UMass Donahue Institute, while the second came from the NAICS codes of all businesses contained in the PPC inventory of Marine Science and Technology firms. I performed an analysis of the MST sector using both of these codes to obtain as accurate a picture of the sector as possible.
Using the Emsi Staffing Patterns tool, I compiled a list of all of the occupations employed by businesses in the MST sector. However, even if an occupation is employed within one of the industries that makes up the sector, it is not necessarily an important occupation to the sector as a whole. In order to identify the high priority occupations – those which are both critical to the operation of MST firms and also pose a challenge to attract and hire – I used data science techniques to rank the importance of each occupation to the sector. A high-priority occupation is defined by one or more of the following metrics:
- High number of jobs in Marine Science and Technology industries, indicating that many workers of this occupation are needed in the sector.
- High ratio of Marine Science and Technology jobs to total jobs for the occupation in the region, indicating that this job is relatively unique to the sector.
- Large difference between growth in Marine Science and Technology industries and growth overall, indicating that the occupation’s employment is growing faster than normal.
- Low Location Quotient (LQ), indicating that the region has a low concentration of workers in this occupation compared to the rest of the country.
For presentation, I decided to select the top 25 occupations as the high-priority occupations; these are shown below. These occupations fell into three neat categories: engineering, production, and natural science, each of which requires different types of education and preparation. Further research was also performed using Emsi to get a sense of the tasks that these occupations perform, as well as analyze commuting patterns within these occupations.
Figure 1: Priority Occupations for SENE Marine Science and Technology sector, 2018
Next, I analyzed PPC survey data. This data allowed me to examine the importance of various worker qualifications to MST employers, see what type of degree one would need to work in Marine Science and Technology, and explore the relationship between MST businesses and universities within Southeastern New England. This informed me which educational areas I should focus on researching. I also used text-entry responses from the survey, which asked which skills and types of worker were most difficult to find for MST firms, as well as notes from key informant interviews conducted by the Public Policy Center to inform further research.
From the survey, I found that an education in engineering is the most important qualification for workers in MST, along with related skills such as lab experience, qualification in advanced manufacturing or precision machining, and quality control experience. Companies typically require 4-year or graduate degrees. The biggest workforce-related challenge is finding workers with the right technical skills for the job. Despite the importance of engineering education, less than half (40%) of respondents considered universities in the region a source of skilled labor for the business. Free response survey questions and interview data also indicated that the most difficult workers to find were software engineers and skilled manufacturing workers.
Figure 2: Sample chart created from the PPC survey data
After going over the survey and interviews, I researched available programs in engineering and production, the two groups of occupations found to be of the greatest priority to the sector. These were compiled into list graphics for the final report. A chart showing the available engineering degrees is shown in Figure 3. The region offers a wide selection of traditional engineering degrees, including computer science, the field with the most bachelor’s degree programs. The engineering field with the lowest number of degree programs is software engineering. Furthermore, the region offers five programs that teach advanced manufacturing, machining, or welding skills, though the Massachusetts side of SENE includes an abundance of high-school programs offered through vocational schools across the region.
Figure 3: Engineering programs available in the SENE region
One of the scarcest and most highly sought-after occupations in MST is that of the software engineer – specifically, the occupation of “systems software developer” as defined by the Bureau of Labor Statistics. Despite the abundance of computer science degrees, my research found that most do not teach the hardware and software engineering skills necessary to work as a software engineer in the sector. These skills are mostly found in computer engineering and software engineering programs, two of the least abundant engineering programs in SENE. An adequate education for a systems software developer to fix this educational gap would include aspects of both computer engineering and software engineering.
In addition to software engineering, the other occupation type facing a significant workforce gap is that of the skilled production worker. In other words, the region needs to train more welders and machinists. As well as receiving an education in the necessary skills for the job, these workers also must go through an apprenticeship in order to be ply their trade. My research found that apprenticeships in the region are scarce, and access to those that do exist is controlled by unions, which may be hard to enter if one did not have the foresight in eighth grade to attend a vocational school. Furthermore, interest in production jobs among middle and high school students has been waning over the past eight years. If unions developed a new strategy to attract workers, or if new businesses arose that allowed welders and machinists to gain experience as apprentices and go on to work at an MST business, this educational gap in production may be eliminated.
Through this summer research project, I was able to practice my data analysis skills while also improving my writing ability and collaborating with other researchers. In the future, when I go on to work in the data science field, these skills will make me a more well-rounded employee and increase my employment prospects and work quality, for which I am very glad. Likewise, I am also prepared to do further research during my undergraduate career. I would like to thank the Public Policy Center for giving me the opportunity to work on this project, and specifically research associate Michael McCarthy for providing valuable report-writing advice. Thank you, Office of Undergraduate Research, for allowing me to work on such a valuable project!