Occupation Clusters

Occupation cluster analysis is a relatively new approach in regional development. In contrast to industry clusters that focus on what businesses produce, occupation clusters focus on the knowledge, skills and abilities of the individuals who work for those businesses. Occupation cluster analysis offers insights into the talent base of the regional workforce that go beyond the relatively simple measure of educational attainment (such as highest degree earned). As part of a recent study conducted for the U.S. Economic Development Administration, the Purdue Center for Regional Development developed a set of 15 knowledge-based occupation clusters. National county-level data for the clusters are available online at www.statsamerica.org/innovation/.¹

Defining Occupation Clusters

The Occupational Information Network (O*Net) divides occupations into five job zones, based on the education and experience a person needs to do the work.² This study used a clustering algorithm with some subsequent fine-tuning to construct 15 knowledge-based occupation clusters containing all occupations within the three highest O*Net job zones (see Table 1)—thus excluding occupations that require limited preparation, such as taxi drivers or customer service representatives.

Table 1: Occupation Clusters Defined in This Study

Source: Purdue Center for Regional Development

Why Occupation Clusters Are Useful

The swift transformation taking place in the global economy makes occupation cluster analysis particularly valuable. The global integration of markets has eliminated many regional competitive advantages. Low-cost land with transportation and communications infrastructure in place is no longer scarce. Technology quickly jumps national borders. Costs for reliable labor are lower in many places across the globe. In this low-cost competitive environment, a region’s best chance to differentiate itself is with its brainpower: the education, knowledge, skills, and abilities of its workforce. From this perspective, every region has the potential to be competitive.

In addition to globalization, the retirement of the Baby Boom generation and the move of businesses toward more innovative, knowledge-based markets have combined to make the skills of the workforce central to economic development. The extensive array of labor force data compiled by the U.S. Department of Labor is giving regional leaders a greater understanding of this economic development asset.

Exploring occupation clusters within one’s region represents a first step. Occupation cluster analysis can help identify which clusters of occupations provide the best opportunities for investment to build different types of skills, supporting existing or emerging industry clusters, and which occupation clusters show a competitive skills advantage in the region.

Identifying Clusters of Opportunity

The following examples, using two designated economic growth regions (EGRs, shown in map to the left) in Indiana, illustrate how the tool can be used to identify “clusters of opportunity.”

The analysis includes location quotients (LQs)—ratios describing the concentration of clusters in a region compared to the United States. When using location quotients, an LQ of 1.2 is usually considered the base point for determining whether an occupation cluster or an industry cluster has a “concentration” in the region. If it does, then the region may have a competitive advantage in that particular industry cluster or occupation cluster.

Economic Growth Region 6

EGR 6 consists of  nine counties in east-central Indiana. In this region, job growth occurred in eight of the 15 occupation clusters between 2001 and 2007, with health care and medical science having the highest growth rate (see Table 2). This cluster is also the second largest in the region (tied with legal and financial services and real estate) and its location quotient is approaching 1.2, suggesting that a regional specialization is developing in these occupations. One of the cluster’s components (medical technicians) is already specialized (LQ=1.22). The largest group of occupations in the health care and medical science cluster is comprised of registered nurses, licensed practical and licensed vocational nurses, followed by physicians and surgeons, and medical assistants.

Table 2: Occupation Clusters of Opportunity in EGR 6

Source: EMSI Complete Employment 2008 Spring Release v. 2

When making the comparison between occupation clusters and industry clusters, it is noteworthy that the biomedical/biotechnical industry cluster in EGR 6 shows a clear concentration compared with the nation, with a location quotient of 3.7 in 2007. With this kind of a concentration in both medical skills and establishments, the region could, for example, seek opportunities to grow its medical research capacities or to aim for a specialization in geriatrics and nursing homes, or other specialized nursing facilities—leveraging its own biomedical industry, as well as the large biomedical industry cluster in the nearby Indianapolis metropolitan area.

Alternatively, the region could try to develop a capacity for physical therapy and the kind of skilled nursing required in rehabilitating patients who need prosthetics. Such potential strategies should obviously be worked out by the economic development stakeholders in tandem with medical and related professionals in the region—in other words, those who would be in the front lines of moving such strategies forward.

A surprising finding is that the information technology occupation cluster (IT) has the third highest employment growth rate in EGR 6. Even more strikingly, the location quotient (while well below 1.2 in 2007) has grown by over 17 percent during the period. Further inspection into the occupational structure of this cluster reveals that the major occupations within the cluster are largely composed of computer software engineers, systems and data communications analysts, network and computer systems administrators, and support specialists.

It is possible that this emerging occupation cluster is related to the presence of Ball State University (postsecondary education and knowledge creation cluster) in the region. Research of these clusters at the national level indicates that the information technology cluster tends to co-locate with the engineering cluster and the mathematics, statistics, data analysis and accounting occupation clusters. However, these two clusters are both smaller, unspecialized and declining in the region, while the IT cluster, though currently small, is growing and increasing in degree of specialization compared to the nation. Clearly, given this kind of information, economic development stakeholders in EGR 6 will want to explore ways to support the further expansion of this important cluster.

Not all of the higher-growth clusters provide direct regional opportunities for 21st century global or even national competitiveness. For example, the 7 percent job growth in primary/secondary and vocational education and social services occupations and an increasing level of concentration of such jobs is beneficial inasmuch as good professional jobs are provided, and the region’s education resources are increased; however, this cluster is more of a “pipeline” for future competitiveness.

Economic Growth Region 11

EGR 11 consists of nine counties in southwestern Indiana. In this region, all of the occupation clusters grew between 2001 and 2007 except for three: engineering; mathematics, statistics, data analysis and accounting; and agribusiness and food processing. Moreover, six clusters showed job growth of 5 percent or more (see Table 3). As in EGR 6, the health care and medical science cluster showed the largest percentage gain in jobs, with a concomitant rise in the size of the location quotient, and a similar internal occupational structure to the EGR 6 cluster (concentration of physicians and surgeons, nurses, and medical assistants). However, the next two highest growth rates occur in very different occupation clusters—building, landscape and construction design followed by arts, entertainment, publishing and broadcasting.

Table 3 : Occupation Clusters of Opportunity in EGR 11

Source: EMSI Complete Employment 2008 Spring Release v. 2

The building, landscape and construction design occupation cluster in EGR 11 is not a large cluster (960 jobs in 2007), nor is it the type of cluster that focuses on exportable products. However, it is an important cluster from the point of view of maintaining and increasing “quality of life” factors for the region and can increase the value of the arts, entertainment, visitor industries and recreation industry cluster if the region becomes known for exceptional design and physical attractiveness.

The third fastest growing occupation cluster in EGR 11 is the arts, entertainment, publishing and broadcasting cluster. While southwestern Indiana provides many opportunities for outdoor recreation and tourism, the fastest growing occupations in the arts and entertainment cluster in EGR 11 appear to be concentrated around casino-style entertainment, photography, graphic design and publishing. It might be worthwhile for regional planners and economic developers to explore the potential synergies of outdoor recreational opportunities with this cluster.

Summary

Since working with occupational data can quickly become overwhelming for users, this research focused on 15 knowledge-based occupation clusters that can simplify analysis and aid in understanding. The occupation cluster tool provides fast insights into the talent base that drives a local or regional economy. With this tool, economic development professionals can begin to structure effective collaborations with business managers, educators, and workforce development professionals. To begin using these data or to learn more about the cluster research, visit www.statsamerica.org/innovation/.

Notes

1. Research was conducted by the Purdue Center for Regional Development, the Indiana Business Research Center at Indiana University's Kelley School of Business, Strategic Development Group, Inc., the Rural Policy Research Institute, and Economic Modeling Specialists, Inc.
2. O*Net is developed under the sponsorship of the U.S. Department of Labor/Employment and Training Administration (www.onetcenter.org/overview.html).

Christine Nolan
Senior Associate, Purdue Center for Regional Development, Purdue University