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Quantifying the Nanotechnology Workforce: Methods, Barriers & Estimates

  1. Quantifying the Nanotechnology Workforce: Methods, Barriers & Estimates Stacey Frederick, Research Scientist Center on Globalization, Governance & Competitiveness (CGGC), Duke Center for Nanotechnology in Society, UCSB Rachel Parker, Program Manager United States Agency for International Development Washington, D.C. SASE Annual Meeting: Milan, Italy June 28, 2013
  2. The Promise of Nanotechnology  Increasing emphasis placed on importance of emerging technologies to economic growth and development.  Various reports suggest that the U.S. can maintain its leadership role in nanotechnology through an emphasis on manufacturing and the commercial deployment of nanotechnology enabled products.  Nanotechnology advocates have made optimistic claims regarding the potential of nanotechnology to create up to 7 million jobs
  3. NNI’s Four Primary Goals 1. To advance world-class nanotechnology R&D 2. To foster the transfer of new technologies into products for commercial and public benefit 3. To develop and sustain educational resources, a skilled workforce and the supporting infrastructure and tools to advance nanotechnology 4. To support the responsible development of nanotechnology
  4. President’s Council of Advisors on S&T (PCAST)  PCAST calls for the National Nanotechnology Coordinating Office to work with others in the Federal Government to enumerate and collect underlying data needed for the development of workforce metrics. Specifically call for the “quantification of the nanotechnology workforce.”  “Good data on the workforce will enable the implementation of additional measures to identify and mitigate further threats to occupational health and safety.”
  5. PCAST, Cont.  Report alludes to hurdles in such a characterization.  “Accurately categorizing agency-level nanotechnology investments will facilitate the identification of nanotechnology trainees, including the academic, scientific, and professional nanotechnology workforce for which there is currently a paucity of data. One area where such tracking would have significant impact is in the identification of nanotechnology-related jobs for which there are no standard occupational codes.”
  6. National Academies  NAS echoes PCAST, suggesting that the NNCO reformulate existing working groups to focus on “facility oversight and coordination and education and workforce development.” (NAS 2013)  Further echo PCASTs call for metrics, saying “NNI reports include anecdotal evidence of research that has been incorporated into products, but little is known about where students go after graduation or about whether and what kinds of barriers stand in the way of nanotechnology commercialization. The data sets called for in the present report include information related to workforce and technology-transfer activities” (NAS 2013).
  7. NAS, cont.  NAS goes further, pointing to “lost opportunities” in dearth of data being collected, however proposed metrics still not enough:  NNI-funded projects, including such information as researcher name and affiliation, funding agency and amount, and abstract. 1. Published documents arising from NNI activities. 2. Data related to impact, including frequently cited and downloaded papers and patents, invited presentations, special sessions at conferences, and reports in the mass media. 3. Number of students supported. 4. User facility and network use. 5. Data related to technology transfer, including details of meetings, workshops, and conferences, and sessions in conferences. 6. Data related to education and outreach, including workshops, activities aimed at K-12 students, and museum exhibits. 7. U.S.-based nanotechnology job advertisements. 8. NNI-related communications about environmental, health, safety, and societal implications of nanotechnology, such as NIOSH guidance regarding nanomaterials in the workplace.
  8. Nanotechnology Employment Estimates • Existing estimates are often not accompanied by a methodology or are based on broad estimations. • Early global nanotechnology employment projections made a decade ago for 2015 ranged from 2 million to 10 million (Roco 2003; Lux 2004). Scope Year Employment Includes Sources Global 2010 600,000 Researchers & Workers (Roco, 2011) USA 2010 190,000 (Average) 160,000-220,000 (Range) Researchers & Workers (Invernizzi, 2011; Roco, 2011) USA 2013 23,443 Researcher/Professional (LinkedIn Corporation, 2013) CA 2007 11,810 (Average) 4,115-19,504 (Range) Researchers & Workers (CCST, 2010) CA 2015 (Projection) 145,000 (Average) 90,000-200,000 (Range) Researchers & Workers (CCST, 2010); based on US estimate of 900,000 by 2015 (Roco, 2002) CA 2011 67,000 (Average) Researchers & Workers 2007 & 2015 Avg. Annualized to 2011 (CCST, 2010) CA 2010 33,000 (Average) Researchers & Workers CCST (2010) method using 2010 estimates of 160-220,000 (above)
  9. Difficulty in Estimating  Nanotechnology- as an enabling technology is amorphous and as such, difficult to categorically include or exclude.  Classifications for nanotechnology-related products and companies are not well delineated.  Firms are also not required to disclose activities or products that involve materials on the nanoscale  Finally, depending on where in the supply chain is targeted, the decision to include or exclude a product or company as “doing nanotechnology” varies significantly.
  10. This Research: Broad & Focused Approach Broad Approach Applied to: United States Focused Approach Applied to: California  Estimate the total number of workers employed by firms and organizations purportedly engaged in some degree of nano-related development.  Estimate the ‘nano’ portion of total employment  California accounts for largest share of nano activity in the United States Research Objectives:  Develop a repeatable methodology to estimate the U.S. nano workforce based on a defensible database of nano stakeholders  Apply the method to provide estimates of the workforce
  11. Methodology Part 1: Determine Nano Population  Meta database created with individual nano datasets of varying scope and size  Merged and cleaned to create a master file with information for each location  Total number of individual datasets included: 16  Woodrow Wilson Center, Plunkett, Lux, NanoVIP, Nanowerk, CADTSC and NSTI (California only)  General business data collected from Hoovers & websites  Key variable used: employment
  12. Methodology Part 2: Define Scope & Value Chain Positions Firms Total: 1,437 Supporting Organizations Total: 603
  13. Methodology Part 3: Focus Areas  Focused approach: only for California  Focus area: degree to which a stakeholder appears to be focused on nano-related activities  Apply percentages to total employment  Nano-specific: 100%  Partial Nano-specific: 50%  Micro- and Nano-specific: 50%  Not Nano-Specific: 0%  Subjective, yet important step towards accurate estimates
  14. Broad Approach: United States Firm Results  Employees at firm locations (n = 1,437): 283,000 employees  Top three NAICS codes at three-digit level: 60% of total  Computer & Electronic Product Manufacturing (334): 23%  Professional, Scientific & Technical Services (541): 23%  Chemical Manufacturing (325): 15%  Top five states based on number of firm locations account for 52% of all U.S. locations and 49% of employment:  California, Massachusetts, New York, Texas & Pennsylvania
  15. Broad Approach: United States Supporting Organization Results  Calculated California’s average and median employment by support organization category to generate U.S. estimates  California locations: 137 (23% of US total); Employees: 27,427  U.S. Total (firm and support): 322,000 – 419,000 Support Group Category U.S. Employment Estimates Based on California’s: Median Average Research Centers/Organizations 29,837 113,179 Industry Associations 1,463 2,032 Labs & Testing Facilities 4,681 15,822 Service Providers 2,439 4,433 Investors 899 861 Estimate Range 39,000 136,000 36% 19% 19% 16% 10% Share of Locations by Category (n=603) Research Organizations Industry Associations Labs & Testing Facilities Service Providers Investors
  16. Focused Approach: California Firm Results  California total firm:  Locations: 361  Employment: 67,665  Majority partly focused on nano (79%)  18% of locations, yet only 2% of employees , appear to be entirely focused on developing or manufacturing nano-related products or tools 18% 2% 45% 68% 34% 27% 3% 3% Locations Employees Nano-Specific Partial Nano Micro & Nano Not Nano Above: Share of CA Firm Locations & Emp. by Focus Area
  17. Focused Approach: California Employment Results by Focus Area Focus Area Nano Employment Support Firm Total Totals 13,677 33,482 47,158 Nano-Specific (100%) 370 1,299 1,669 Partial Nano-Specific (50%) 12,743 23,023 35,766 Micro & Nano-Specific (50%) 564 9,160 9,723 Not Nano-Specific (0%) -- -- -- • Results using data from this research are in line with estimates made in the California Council on Science & Technology (CCST) 2010 report on Nanotechnology in California for the number of workers in California. • Non-Farm Employment in California (April 2013): 14,602,200 • Our Results: Nano Employees Share: Focused & Broad Approach: 0.3% - 0.7%
  18. Comparison: Nano Researcher & Worker Estimates (2010-12) Existing: 2010/2011 This research: 2011/2012  United States:  160-220,000  California:  33,000-67,000  U.S. Broad Total: 322 – 419,000  U.S. Focused Total (Est.): 161-210,000  California Total: 95,092  California Focused Total: 47,158 • Conclusions: this research provides • Estimates of the U.S. and California nano workforce • A framework and scope for describing the nanotechnology economy • A database of stakeholders that can be used as a basis for tracking and developing future estimates • A repeatable methodology for estimating the nanotech workforce
  19. Limitations / Future Research Limitations Future Research  Employment estimates are only as good as estimates of nano stakeholder population  Estimates dependent on firm disclosure of nano-related activities  Without survey or US Census micro data, employment estimates are dependent on secondary sources  Expand, update and improve nano population estimates  SBIR/STTR funding data  Primary data collection  Expand focused methodology to other U.S. states and refine the % and categories  Estimates nano workforce supply and demand and job profiles  Graduate data  LinkedIn  Job listings