Knowledge-Based Economic Development: Measuring the Talent Pool for Innovation Capacity

With the growing attention to the competitive advantages of a knowledge-based economy has come a renewed focus on innovation as the process that can transform information into value and thus spur growth and development. This pursuit of knowledge-based economic development has intensified the focus on localized assets and resources and in particular the human capital dimensions of innovation.

Those communities able to attract or cultivate a highly educated, technically proficient, motivated and flexible work force will reap the greatest benefits from the global information-based economy. However, a significant obstacle remains the lack of standard measurements of the innovation capacity of human capital. This article identifies some commonly employed data standards and points to several nascent innovation indices that could present a more complete profile of a destination’s labor assets.

New Metrics for a New Economy

The basic principles of economic development have remained constant for centuries. Improve the inputs of land, labor and capital and reap the benefits of jobs, payrolls, profits and taxes. How the outputs are measured hasn’t changed; though the nature of the inputs certainly has. For example, land was once measured by its natural resources, its proximity to shipping infrastructure and its suitability for industrial production. While those factors still matter, a site’s proximity to core knowledge and information infrastructure (such as universities and research institutes) and suitability for research parks and laboratory buildings are often more important to innovation-based growth.

The best measure of financial capital was formerly available credit for loans. However, today venture capital, cash in the pockets of angel investors and government grants are the preferred source of financing for innovative companies. Similarly, labor once meant people who could lift, turn, push and move products on an assembly line. Today it is increasingly their knowledge of science, technology, engineering and math, as well as their skill in bringing new ideas to market, that creates value for a company and its community.

What Human Capital Dimensions Are Measured?

Over the centuries, standardized methods have been developed to gauge the important aspects of land, capital and labor inputs. However, the evolving nature of innovation often defies measurement by the more traditional standards. Rather, dozens of methods have been developed and perhaps none so abundantly as those metrics that attempt to assess the contributions of human capital to an area’s innovation economy. A sample of these North American measures and their advantages and drawbacks is described below.

New Scientists and Engineers. The objective of this metric is to depict the ability of a region to generate new ideas and commercialize new products or services. Often reported as the number of college students enrolled and graduated, this measure also frequently includes graduate students and post-doctorial fellows in the sciences. While the data are relatively easy to collect, they have several notable shortcomings. First, by an overwhelming number, technology entrepreneurs are older than recent graduates (typically in their mid-40s) and have worked most of their life for large firms. Second, the focus on technical talent does not address other critical skills needed to bring new discoveries to the market such as finance, regulatory affairs, marketing, intellectual property management, etc. Third, it is a poor predictor of the types of innovation that built non-technology powerhouses like Wal-Mart or Starbucks.

Number of persons with college degrees. Though very general, this metric is commonly used because of its ease of extraction from the U.S. Census and other data sources. The attraction of this measure also is premised on the reasonable assumption that workers with more knowledge are the most likely to innovate. Other popular indicators include the number and/or share of PhDs, MS and BS degree holders compared to the United States at large.

High school performance. Further down the innovation “gradient” are data describing high school graduation rates and average SAT scores, etc. At first glance such metrics would seem to be plausible indicators of creativity and innovation. After all, a person who has graduated high school with high scores on the scholastic aptitude tests is a more likely entrepreneur than a high school dropout. However, high school graduation rates do not help us understand how many students choose to attend college, if they went to college nearby or where they reside now. Perhaps a better metric would be data describing the number of students having taken advanced placement or international baccalaureate courses.

Number of persons employed in high-tech industries (using NAICS the North American Industry Classification System codes). These data typically include the codes for industrial machinery, electronic equipment, instruments, chemicals, communications, research and development and business services. This metric addresses the reality that most successful technology start-ups are founded by former employees of large corporations. It also accounts for that broader skill set (beyond the sciences) needed to fully realize the potential of new discoveries. However, again, by relying on measures of technology-based employment the economic developer or site selector may be ignoring sources of business model innovation.

Number of persons employed in tech-based occupations (using the U.S. Bureau of Labor Statistics Standard Occupational Classification codes). Metrics based on occupational data are perhaps the best yardstick of specific STEM (science, technology, engineering and mathematics) skill sets in a particular destination. However it’s important that users distinguish between occupations engaged in the social sciences versus those focusing on the physical or natural sciences (e.g., biologists, analytical chemists). Distinction should also be made between the scientists and engineers who design and direct much of the actual discovery and development processes and the various technicians who often lack an advanced degree and whose primary mission is to assist and report the results.

Examples of Innovation Indices

Over the years there have been numerous attempts to combine human capital and other variables into general indices of the knowledge capacity of nations, states and regions. For the purposes of this article, it would be insightful to examine three state indices that have garnered national attention, including The Indiana Business Research Center’s Innovation in American Region, the John Adams Innovation Institute’s Index of the Massachusetts Innovation Economy and Jeremy Hall’s (University of Texas at Dallas) 50 State Indices of Innovation Capacity and Commercialization Capacity. Each of these tools attempts to quantify the capacity of a region to support turning new ideas into economic growth through the discovery and commercialization of new products and services.

These three indices used different combinations of variables to measure innovativeness. For example, Innovation in American Regions found a high degree of correlation between economic growth and educational attainment; employment by occupation, employment by industry, access to broadband, level of R&D expenditures; availability of venture capital funds, numbers of new patents, small businesses per thousand workers and population growth of 25- to 44-year-olds.

The Massachusetts Index of the Innovation Economy (used by the state’s leadership to benchmark against other leading technology hubs) uses 25 such indicators. They are grouped into economic measures (e.g., percent of employment in science-related fields), research (e.g., corporate R&D activity, patents); technology development (e.g., number of Small Business Innovation Awards); business development (e.g., IPOs); capital formation (e.g., venture capital investment per capita) and talent. For this latter category they specifically measure the working population with bachelor’s or higher degrees; high school attainment of 19- to 24-year-olds; public investment in K-16 education; and specific science, IT and engineering degrees. The result is a terrific tool for policy makers that also plays an important role marketing the state.

Hall’s 50-State Indices of Innovation Capacity and Commercialization Capacity is more of an academic ranking than the other two indexes discussed, but it does provide practical insights. It comprises six human capital and 13 financial capacity variables. The findings led him to conclude that the effort needed to build the human capital required to achieve an innovation “critical mass” would likely require a massive shift in state spending on behalf of science and engineering education. Hall has argued that those states that lack the financial resources or talent base are unlikely to ever catch up and thus should continue to focus on more traditional industries.

Conclusion

Creativity and the capacity for innovation spring first and foremost from the human mind. Coupled with the ongoing shift toward a knowledge-based economy, this emphasis on human capital requires that site selectors and economic developers alike develop new methods to identify and quantify those attributes (education, proficiencies, entrepreneurial skills and spirit) that can distinguish a truly innovative work force. The metrics and indices profiled here provide good examples of new standards being developed to measure human capital and the ability to innovate.