The rate of innovation from a region has become the litmus test for competitiveness in the globalized knowledge economy. Cross-industry occupational decomposition was used to determine industrial innovative capacity by four digit NAICS industry. The percentage employment in technology oriented occupations was calculated for each individual four digit NAICS industry and compared to the percentage employment in these occupations nationally. A standard of twice the national percentage employment in technology oriented occupations was used to determine each industry's level of innovative capacity. Using the aforementioned standard, a total of 35 industries could be classified as innovative in 2009. The growth in technology-oriented employment and overall employment was tracked by industry from 2002 through 2009. The location quotient for the aggregate employment of the 35 innovative industries was mapped geographically. An OLS model was developed to regress the relationship between counties containing institutions that produce a large number of Science, Technology, Engineering, and Mathematics (STEM) degrees relative to the national average with counties that had high concentrations of employment in innovative industry. The results of this analysis show that there is a strong correlation between counties with an elevated level of STEM awards and innovative employment in 2009. The policy prescriptions advocated by this analytical endeavor include the development of strong trade associations that make curriculum recommendations for institutions of higher education and large scale investment in university funded research.