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

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

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

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.”

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.”

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).

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.

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)

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.

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

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

Methodology Part 2:
Define Scope & Value Chain Positions
Firms
Total: 1,437
Supporting
Organizations
Total: 603

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

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

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

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

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%

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

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