inclusion, innovation, and integrative design pittsburgh’s creative … · 2014-02-19 ·...

Inclusion, Innovation, and Integrative Design

Pittsburgh’s Creative Clusters What could Pittsburgh look like in 2020?

Full Report February, 2014

Presented by: In Partnership with: With Support from:

Research by: Kevin Stolarick, PhD Lou Musante, MLS

Inclusion, Innovation & Integrative Design January-‐20-‐2014 Pittsburgh’s Creative Clusters 2

Table of Contents Executive Summary Report Overview ....................................................................................................................... 3

Executive Summary Summary of Findings ................................................................................................................ 4

Executive Summary Other Findings .......................................................................................................................... 6

Executive Summary Pittsburgh’s Creative Cluster Data ............................................................................................ 7

The Scope of the Creative Sector .............................................................................................................................. 8

Definition of Study Region .................................................................................................................................. 26

Benchmarking Pittsburgh’s Future Prosperity .................................................................................................... 27

Benchmark Summary: Pittsburgh among 20 Peer Regions ................................................................................. 28

Inclusiveness Changes in the Region ................................................................................................................... 34

Pittsburgh Creative Sectors ..................................................................................................................................... 35

Industries ............................................................................................................................................................ 37

Industry Establishment Counts ........................................................................................................................... 45

Occupations ........................................................................................................................................................ 47

Comparison to Creative Industries Study Report Industry Clusters .................................................................... 55

Benchmark Comparisons .................................................................................................................................... 57

The Future of Pittsburgh’s Creative Sector ............................................................................................................. 69

Pittsburgh Creative Sector Wages ....................................................................................................................... 70

Benchmark Comparison Wages .......................................................................................................................... 72

Asking Questions ..................................................................................................................................................... 93

The Creative Sector Survey ................................................................................................................................. 93

Interconnectivity between the Creative Industries ........................................................................................... 105

Focus Groups ..................................................................................................................................................... 115


Executive Summary Report Overview This report is intended to provide community leaders with a stronger understanding of the current state of Pittsburgh's creative industries and the creative class of people that power their success. Defining the creative industry is a challenging undertaking. For the purposes of this analysis, the goal is to identify industry clusters and sub-‐clusters that can be easily measured, and for which national data was readily available. Clusters that are included in this analysis (Creative Industry Support; Data Sciences; Design; Entertainment; Fine Arts; Media Communications; Software / Hardware), were those that demonstrate a strong dependence on innovation and technology, but also on highly skilled creative employees, free agents and entrepreneurs. This report provides valuable data on the direct employment impact of Pittsburgh's creative industries, but equally important, it characterizes the creative occupational clusters that support the success of all Pittsburgh industries. Understanding these occupational clusters is an essential component of any region’s effort to fully understand their strengths and challenges. For example, nearly 50 percent of those doing work in the various information technology fields of expertise are actually working outside of industries that would typically be included in an analysis of a particular region’s technology sector. In Pittsburgh, some of the largest technology employers include organizations from the financial services, healthcare and manufacturing sectors. By analyzing multiple sets of data, the report reveals strong insights into the current state of Pittsburgh’s creative ecosystem and identifies occupational clusters that will see strong growth in the coming years. To place this progress in perspective, Pittsburgh is benchmarked against 19 other cities with the goals of including geographically diverse regions and regions with higher-‐than-‐average concentrations of creative occupation and industry clusters. This report also includes a creative sector survey that captures data from nearly 400 members of Pittsburgh’s various creative sectors. This process brings to light important initial information that details the level of connectivity that exists between the various creative industry clusters within the Pittsburgh region.


Executive Summary Summary of Findings This report establishes that the transformation to a thriving city based upon on innovation and creativity is indeed taking shape. With a few notable exceptions, the region possesses the ingredients necessary to build a sustainable ecosystem for its creative sectors. As of 2012, more than 176,000 people have occupations-‐related to the creative clusters, a number expected to exceed 200,000 people by 2020. These people earn $19.6 billion, which is 20 percent of the region’s overall workforce. From an industry perspective, more than 11,000 creative sector establishments directly employ more than 280,000 people. Without exception, each of Pittsburgh’s seven creative sector industry clusters is growing at a faster annual pace than in the national economy. Among our initial findings include: Core Observations 1.) Pittsburgh is Still a City of Makers Pittsburgh’s Design cluster has grown to employ more than 50,000 people and, with a location quotient (LQ) of 1.34, remains firmly planted in southwestern Pennsylvania (a location quotient of 1.34 indicates that the design cluster is 34 percent more concentrated in Pittsburgh than in the nation at large). Two key sub-‐clusters, engineering and manufacturing, employ the majority of workers in the design cluster. With more than 17,000 employees, Pittsburgh’s engineering sub-‐cluster has achieved an annualized growth rate of more than eight percent, in comparison to a national growth rate of just .64 percent for this sub-‐cluster. Pittsburgh’s engineering cluster has a location quotient of 2.042, meaning the industry is more than twice as concentrated in Pittsburgh than in the nation. This is one of the strongest location quotients across all of Pittsburgh’s clusters and sub-‐clusters. The manufacturing sub-‐cluster fared well through the recession, growing at an annualized rate of 1.3 percent from 2005 to 2011 -‐-‐ compared to a national decline in this sector of 2.03 percent. The industry continues to have a high concentration in Pittsburgh, with a location quotient of 1.25 (25 percent more concentrated in Pittsburgh than the nation). 2.) Pittsburgh’s Creative Industry Support Cluster is Growing at 14 Times the National Rate

To support the development of a thriving creative economy, five sub-‐clusters are considered to be essential components of a region’s economy. Among those include: R&D Organizations; Post-‐Secondary Institutions; Services; Consulting; and Associations.


In Pittsburgh, these industry clusters have a LQ of 1.24 and employ more than 161,000 people. The cluster experienced an average annual growth rate of 7.9 percent from 2005 to 2011, far faster than the national growth rate of .57 percent. 3.) Technology Talent is Growing Far Faster in Pittsburgh

Pittsburgh is home to nearly 35,000 people working in software-‐ and hardware-‐related professions, an occupational cluster that is expected to add more than 6,000 regional employees by 2020. This occupational cluster has been growing at three times the national rate. 4.) Pittsburgh Falls Short on Inclusiveness; Jeopardizes Growth Pittsburgh has almost all of the essential components to build a 21st century economy, but the one notable exception is its inclusiveness of people of color, of foreign-‐born decent and same-‐sex partnerships. Diversity issues face many mid-‐sized regions like Pittsburgh, but against the 19-‐benchmark regions, Pittsburgh ranked 20th for number of foreign-‐born residents, 18th for the concentration of the gay and lesbian community, and 13th for the percentage of population that is non-‐white. Considering the pivotal roles that each of these populations play in the creative economy, Pittsburgh will be hard-‐pressed to transition to the next level without identifying and addressing the root causes of these inequities. For example, in the technology sector, immigrants continue to play a vital role in the formation of new businesses. In Silicon Valley, 50 percent of all technology businesses have been identified as having at least one foreign-‐born founder (America’s New Immigrant Entrepreneurs: Vivek Wadhwa), which compares to 25 percent of all technology business having a foreign founder across the United States. This is an important consideration given that the average location quotient for high technology businesses in the benchmark regions is 1.2, versus .94 for Pittsburgh. Said differently, technology businesses are 20 percent more concentrated in the benchmark cities than in Pittsburgh. To move Pittsburgh closer to the average of the benchmark cities, diverse populations, including a larger share of foreign-‐born entrepreneurs will be an essential component of any growth strategy. 5.) Interconnectivity: A Marker for Innovation

First-‐of-‐its-‐kind regional research indicates Pittsburgh’s creative industry clusters must continue to promote industry spill-‐across and spill-‐overs (cross-‐sector collaborations) to increase innovative productivity. While some clusters, including Communications and Creative Industry Support Services, demonstrate high levels of interconnectivity, the majority of the sectors still exhibit a tendency toward intra-‐cluster work habits. The Social Media sub-‐cluster demonstrated the highest level of interconnectivity among all industry clusters and sub-‐clusters, followed closely by sub-‐clusters, including: Marketing, Graphic Design, Mobile Applications and Software Development.


Executive Summary Other Findings Wages in Pittsburgh: At $43,000, the Pittsburgh region’s average wages ranked as the 15th among the 19 peer regions. With this said, at 18.8 percent, our wage growth from 2006 through 2011 earned Pittsburgh the top slot for wage growth among the benchmarked regional cities. The Recession and Pittsburgh: Pittsburgh faired far better than the benchmarked cities from 2006 through 2011 in terms of job growth, ranking fifth in overall job creation. (Pittsburgh achieved a .6 percent growth rate, versus the peer average of negative 1.7 percent) Ethnic Integration: Pittsburgh is still relatively segregated according to racial and ethnic backgrounds with those communities failing to be represented proportionally across the region’s census tracks. In this category, Pittsburgh lags the national average and ranks 16th in comparison to the benchmarked cities. Human Capital Flight: Despite the rumors of our demise, Pittsburgh’s utilization of talent in universities is no better or worse than the average metro region, but among the benchmark cities, Pittsburgh ranks 19 out of 20. Regional Assets: In terms of attracting families and young people alike, Pittsburgh has several strong assets. The region has the second-‐strongest student:teacher ratio among our peer cities within primary and secondary institutions. Pittsburgh has significantly more bars and restaurants per 100,000 residents, ranking fourth against our peer cities. Regional Educational Attainment: Pittsburgh has the lowest percentage of population age 25 and above that has completed less than a high school degree. (Just 8.9 percent of our population attained less than a high school degree, versus 14.4 percent for other U.S. metro regions and 12.8 percent for other benchmarked cities).


Executive Summary Pittsburgh’s Creative Cluster Data Volume 282,165 people employed

In 11,218 establishments

176,940 people working in Creative sector jobs

Value Currently receiving over $9.6 billion in wages each year

Growth Expected to grow to over 200,000 people by 2020

Competitive Position

Pittsburgh Peer Ranking (out of 20)

Population Growth (05-‐10) 1.9% 16 Job Growth (06-‐11) 0.6% 5

GDP per capita, 2011 $43,045 13 Change in Average Wage (06-‐11) 18.8% 1

Average Wage (11) $43,561 15

Creative Sector Industry Clusters

Employment Share Establishments Share Creative Industry Support 161,390 57.2% 4,432 39.5% DATA Sciences 14,148 5.0% 649 5.8% Design 50,575 17.9% 2,323 20.7% Entertainment 21,971 7.8% 1,307 11.7% Fine Arts 4,349 1.5% 491 4.4% Media/Communications 13,564 4.8% 771 6.9% Software/Hardware 16,167 5.7% 1,245 11.1% Total 282,165

11,218

Creative Sector Employment Clusters

Employment Share Growth to 2022 Creative Industry Support 41,460 23.4% 14.5% DATA Sciences 11,910 6.7% 12.9% Design 24,040 13.6% 6.9% Entertainment 40,850 23.1% 10.3% Fine Arts 2,390 1.4% 8.7% Media/Communications 21,500 12.2% 12.4% Software/Hardware 34,790 19.7% 19.0% Total 176,940

12.7%


The Scope of the Creative Sector Creative Industry Clusters and Sub-‐Clusters Cluster Sub-‐cluster

Creative Industry Support

Associations

Consulting Post-‐Secondary Education

R&D Services

DATA Sciences

Communications

Internet Sensor

Telecomm

Design

Architecture

Engineering Manufacturing

Other Design

Textiles Urban

Entertainment

Educational IT Film & Media

Manufacturing

Post-‐Production Recreation

Toys

Fine Arts

Arts Organizations

Arts Venues Museums

Music

Performing Arts Visual Arts

Media/Communications

Advertising Broadcasting

Graphic Design

Marketing Printing

Public Relations Publishing

Software/Hardware

Health Devices Manufacturing

Retail

Software


Creative Industry Clusters by NAICS Codes Industry data is from 2011, the latest year available for the County Business Patterns (CBP) from the US Census. NAICS NAICSTitle Cluster Sub-‐Cluster Specifics

81321/ Grant making and Giving Services Creative Industry Support Associations

81331/ Social Advocacy Organizations Creative Industry Support Associations

81341/ Civic and Social Organizations Creative Industry Support Associations

81391/ Business Associations Creative Industry Support Associations

81392/ Professional Organizations Creative Industry Support Associations

81393/ Labor Unions and Similar Labor Organizations

Creative Industry Support Associations

81394/ Political Organizations Creative Industry Support Associations

81399/ Other Similar Organizations (except Business, Professional, Labor, and Political Organizations)

Creative Industry Support Associations

54162/ Environmental Consulting Services Creative Industry Support Consulting

Professional Services and Research

54169/ Other Scientific and Technical Consulting Services

Creative Industry Support Consulting

61131/ Colleges, Universities, and Professional Schools

Creative Industry Support Post-‐Sec

61141/ Business and Secretarial Schools Creative Industry Support Post-‐Sec

61142/ Computer Training Creative Industry Support Post-‐Sec

61143/ Professional and Management Development Training


61151/ Technical and Trade Schools Creative Industry Support Post-‐Sec

51911/ News Syndicates Creative Industry Support R&D

51912/ Libraries and Archives Creative Industry Support R&D

51919/ All Other Information Services Creative Industry Support R&D

54138/ Testing Laboratories Creative Industry Support R&D Bio Research

54171/ Research and Development in the Physical, Engineering, and Life Sciences

Creative Industry Support R&D Bio Research


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics

54172/ Research and Development in the Social Sciences and Humanities

Creative Industry Support R&D Bio Research

92711/ Space Research and Technology Creative Industry Support R&D

54121/ Accounting, Tax Preparation, Bookkeeping, and Payroll Services

Creative Industry Support Services

54199/ All Other Professional, Scientific, and Technical Services


55111/ Management of Companies and Enterprises


56111/ Office Administrative Services Creative Industry Support Services

56121/ Facilities Support Services Creative Industry Support Services

56131/ Employment Placement Agencies Creative Industry Support Services

56132/ Temporary Help Services Creative Industry Support Services

56133/ Professional Employer Organizations


56141/ Document Preparation Services Creative Industry Support Services

56143/ Business Service Centers Creative Industry Support Services

56149/ Other Business Support Services Creative Industry Support Services

56199/ All Other Support Services Creative Industry Support Services

33422/ Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing

DATA Communications Hardware

33429/ Other Communications Equipment Manufacturing DATA Communications Hardware

51751/ Cable and Other Program Distribution DATA Communications

51611/ Internet Publishing and Broadcasting DATA Internet

51811/ Internet Service Providers and Web Search Portals DATA Internet

51821/ Data Processing, Hosting, and Related Services DATA Internet Telecommunications

51913/ Internet publishing and broadcasting and web search portals

DATA Internet Telecommunications

33641/ Aerospace Product and Parts Manufacturing DATA Sensor Technology-‐

intensive


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics Manufacturing

54136/ Geophysical Surveying and Mapping Services DATA Sensor


54137/ Surveying and Mapping (except Geophysical) Services DATA Sensor


33421/ Telephone Apparatus Manufacturing DATA Telecomm Hardware

51711/ Wired Telecommunications Carriers DATA Telecomm Telecommunications

51721/ Wireless Telecommunications Carriers (except Satellite) DATA Telecomm Telecommunications

51731/ Telecommunications Resellers DATA Telecomm 51741/ Satellite Telecommunications DATA Telecomm Telecommunications 51791/ Other Telecommunications DATA Telecomm Telecommunications

54131/ Architectural Services Design Architecture Professional Services and Research

54132/ Landscape Architectural Services Design Architecture Professional Services and Research

54133/ Engineering Services Design Engineering Professional Services and Research

54134/ Drafting Services Design Engineering 33211/ Forging and Stamping Design Manufacturing Advanced

Manufacturing

33271/ Machine Shops Design Manufacturing Advanced Manufacturing

33272/ Turned Product and Screw, Nut, and Bolt Manufacturing Design Manufacturing Advanced

Manufacturing

33281/ Coating, Engraving, Heat Treating, and Allied Activities Design Manufacturing Advanced

Manufacturing

33321/ Sawmill and Woodworking Machinery Manufacturing Design Manufacturing Advanced

Manufacturing

33322/ Plastics and Rubber Industry Machinery Manufacturing Design Manufacturing Advanced

Manufacturing

33329/ Other Industrial Machinery Manufacturing Design Manufacturing Advanced

Manufacturing

33331/ Commercial and Service Industry Machinery Manufacturing Design Manufacturing Advanced

Manufacturing

33351/ Metalworking Machinery Manufacturing Design Manufacturing Advanced

Manufacturing 33399/ All Other General Purpose Design Manufacturing Advanced


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics Machinery Manufacturing Manufacturing

33441/ Semiconductor and Other Electronic Component Manufacturing

Design Manufacturing Advanced Manufacturing

33451/ Navigational, Measuring, Electromedical, and Control Instruments Manufacturing

Design Manufacturing Advanced Manufacturing

33461/ Manufacturing and Reproducing Magnetic and Optical Media Design Manufacturing Advanced

Manufacturing

33531/ Electrical Equipment Manufacturing Design Manufacturing Advanced

Manufacturing

33592/ Communication and Energy Wire and Cable Manufacturing Design Manufacturing Advanced

Manufacturing

54142/ Industrial Design Services Design Manufacturing Advanced Manufacturing

54161/ Management Consulting Services Design Manufacturing Advanced Manufacturing

54141/ Interior Design Services Design Other Design 54149/ Other Specialized Design Services Design Other Design 31311/ Fiber, Yarn, and Thread Mills Design Textiles 31321/ Broadwoven Fabric Mills Design Textiles 31322/ Narrow Fabric Mills and Schiffli

Machine Embroidery Design Textiles 31323/ Nonwoven Fabric Mills Design Textiles 31324/ Knit Fabric Mills Design Textiles 31331/ Textile and Fabric Finishing Mills Design Textiles 31332/ Fabric Coating Mills Design Textiles 48511/ Urban Transit Systems Design Urban 48811/ Airport Operations Design Urban 48819/ Other Support Activities for Air

Transportation Design Urban 61171/ Educational Support Services Entertainment Educational IT 51211/ Motion Picture and Video

Production Entertainment Film & Media

51212/ Motion Picture and Video Distribution Entertainment Film & Media

51213/ Motion Picture and Video Exhibition Entertainment Film & Media

51221/ Record Production Entertainment Film & Media 51222/ Integrated Record

Production/Distribution Entertainment Film & Media 51224/ Sound Recording Studios Entertainment Film & Media 51229/ Other Sound Recording Industries Entertainment Film & Media 33431/ Audio and Video Equipment Entertainment Manufacturing


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics Manufacturing

51219/ Postproduction Services and Other Motion Picture and Video Industries

Entertainment Post-‐production

33992/ Sporting and Athletic Goods Manufacturing Entertainment Recreation

42391/ Sporting and Recreational Goods and Supplies Merchant Wholesalers

Entertainment Recreation

45111/ Sporting Goods Stores Entertainment Recreation 48711/ Scenic and Sightseeing

Transportation, Land Entertainment Recreation

48721/ Scenic and Sightseeing Transportation, Water Entertainment Recreation

48799/ Scenic and Sightseeing Transportation, Other Entertainment Recreation

61162/ Sports and Recreation Instruction Entertainment Recreation 71121/ Spectator Sports Entertainment Recreation

71131/ Promoters of Performing Arts, Sports, and Similar Events with Facilities


71132/ Promoters of Performing Arts, Sports, and Similar Events without Facilities


71141/ Agents and Managers for Artists, Athletes, Entertainers, and Other Public Figures


71213/ Zoos and Botanical Gardens Entertainment Recreation 71219/ Nature Parks and Other Similar

Institutions Entertainment Recreation 71311/ Amusement and Theme Parks Entertainment Recreation 71312/ Amusement Arcades Entertainment Recreation 71321/ Casinos (except Casino Hotels) Entertainment Recreation 71329/ Other Gambling Industries Entertainment Recreation 71391/ Golf Courses and Country Clubs Entertainment Recreation 71392/ Skiing Facilities Entertainment Recreation 71393/ Marinas Entertainment Recreation 71394/ Fitness and Recreational Sports

Centers Entertainment Recreation 71395/ Bowling Centers Entertainment Recreation 71399/ All Other Amusement and

Recreation Industries Entertainment Recreation

33993/ Doll, Toy, and Game Manufacturing Entertainment Toys Advanced Materials:

Rubber and Plastics


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics

42392/ Toy and Hobby Goods and Supplies Merchant Wholesalers Entertainment Toys

45112/ Hobby, Toy, and Game Stores Entertainment Toys 61161/ Fine Arts Schools Fine Arts Arts

Organizations

71111/ Theater Companies and Dinner Theaters Fine Arts Arts Venues

45392/ Art Dealers Fine Arts Museums 71211/ Museums Fine Arts Museums 71212/ Historical Sites Fine Arts Museums 45114/ Musical Instrument and Supplies

Stores Fine Arts Music 71113/ Musical Groups and Artists Fine Arts Music 71112/ Dance Companies Fine Arts Performing Arts 71119/ Other Performing Arts Companies Fine Arts Performing Arts 71151/ Independent Artists, Writers, and

Performers Fine Arts Performing Arts

33991/ Jewelry and Silverware Manufacturing Fine Arts Visual Arts

54192/ Photographic Services Fine Arts Visual Arts 54181/ Advertising Agencies Media/

Communications Advertising

54183/ Media Buying Agencies Media/ Communications Advertising

54184/ Media Representatives Media/ Communications Advertising

54185/ Display Advertising Media/ Communications Advertising

54186/ Direct Mail Advertising Media/ Communications Advertising

54187/ Advertising Material Distribution Services

Media/ Communications Advertising

54189/ Other Services Related to Advertising

Media/ Communications Advertising

51511/ Radio Broadcasting Media/ Communications Broadcasting Telecommunications

51512/ Television Broadcasting Media/ Communications Broadcasting Telecommunications

51521/ Cable and Other Subscription Programming

Media/ Communications Broadcasting Telecommunications

54143/ Graphic Design Services Media/ Communications Graphic Design

42511/ Business to Business Electronic Markets

Media/ Communications Marketing

54191/ Marketing Research and Public Media/ Marketing


NAICS NAICSTitle Cluster Sub-‐Cluster Specifics Opinion Polling Communications

32223/ Stationery Product Manufacturing Media/ Communications Printing

32229/ Other Converted Paper Product Manufacturing

Media/ Communications Printing

32311/ Printing Media/ Communications Printing

32312/ Support Activities for Printing Media/ Communications Printing

54182/ Public Relations Agencies Media/ Communications Public Relations

51111/ Newspaper Publishers Media/ Communications Publishing

51112/ Periodical Publishers Media/ Communications Publishing

51113/ Book Publishers Media/ Communications Publishing

51114/ Directory and Mailing List Publishers

Media/ Communications Publishing

51119/ Other Publishers Media/ Communications Publishing

51223/ Music Publishers Media/ Communications Publishing

33911/ Medical Equipment and Supplies Manufacturing SW/HW Health Devices Bio Research

33411/ Computer and Peripheral Equipment Manufacturing SW/HW Manufacturing Hardware

42342/ Office Equipment Merchant Wholesalers SW/HW Retail

42343/ Computer and Computer Peripheral Equipment and Software Merchant Wholesalers

SW/HW Retail

42344/ Other Commercial Equipment Merchant Wholesalers SW/HW Retail

44312/ Computer and Software Stores SW/HW Retail 51121/ Software Publishers SW/HW Software Software

54151/ Computer Systems Design and Related Services SW/HW Software Software


Creative Industry Occupational Clusters and Sub-‐Clusters Cluster Sub-‐cluster

Creative Industry Support Post-‐Secondary Education R&D Services

DATA Science

Communications Internet R&D Sensor Telecomm

Design

Architecture/Engineering Architecture Engineering Industrial Design Other Design Textiles Urban

Entertainment Film & Media Recreation Toys

Fine Arts

Museums Music Performing Arts Visual Arts

Media/Communications

Advertising Broadcasting Graphic Design Marketing Other Printing Public Relations Publishing

Software/Hardware

Engineering Health Devices Manufacturing Retail Software


Creative Industry Occupational Clusters The occupational data is from 2012, the latest year available for the Occupation Employment Survey (OES) from the US Bureau of Labor Statistics (BLS). OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 11-‐9033 Education Administrators, Postsecondary Creative Industry Support Post-‐Sec 25-‐1011 Business Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1041 Agricultural Sciences Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1042 Biological Science Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1043 Forestry and Conservation Science Teachers,

Postsecondary Creative Industry Support Post-‐Sec

25-‐1051 Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary


25-‐1052 Chemistry Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1053 Environmental Science Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1054 Physics Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1061 Anthropology and Archeology Teachers,


25-‐1062 Area, Ethnic, and Cultural Studies Teachers, Postsecondary


25-‐1063 Economics Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1064 Geography Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1065 Political Science Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1066 Psychology Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1067 Sociology Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1069 Social Sciences Teachers, Postsecondary, All Other Creative Industry Support Post-‐Sec 25-‐1071 Health Specialties Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1072 Nursing Instructors and Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1081 Education Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1082 Library Science Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1111 Criminal Justice and Law Enforcement Teachers,


25-‐1112 Law Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1113 Social Work Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1122 Communications Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1123 English Language and Literature Teachers,


25-‐1124 Foreign Language and Literature Teachers, Postsecondary


25-‐1125 History Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1126 Philosophy and Religion Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1191 Graduate Teaching Assistants Creative Industry Support Post-‐Sec 25-‐1192 Home Economics Teachers, Postsecondary Creative Industry Support Post-‐Sec


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 25-‐1193 Recreation and Fitness Studies Teachers,


25-‐1194 Vocational Education Teachers, Postsecondary Creative Industry Support Post-‐Sec 25-‐1199 Postsecondary Teachers, All Other Creative Industry Support Post-‐Sec 11-‐9121 Natural Sciences Managers Creative Industry Support R&D 15-‐2031 Operations Research Analysts Creative Industry Support R&D 19-‐0000 Life, Physical, and Social Science Occupations Creative Industry Support R&D 19-‐1010 Agricultural and Food Scientists Creative Industry Support R&D 19-‐1011 Animal Scientists Creative Industry Support R&D 19-‐1012 Food Scientists and Technologists Creative Industry Support R&D 19-‐1013 Soil and Plant Scientists Creative Industry Support R&D 19-‐1021 Biochemists and Biophysicists Creative Industry Support R&D 19-‐1022 Microbiologists Creative Industry Support R&D 19-‐1023 Zoologists and Wildlife Biologists Creative Industry Support R&D 19-‐1029 Biological Scientists, All Other Creative Industry Support R&D 19-‐1031 Conservation Scientists Creative Industry Support R&D 19-‐1032 Foresters Creative Industry Support R&D 19-‐1041 Epidemiologists Creative Industry Support R&D 19-‐1099 Life Scientists, All Other Creative Industry Support R&D 19-‐2011 Astronomers Creative Industry Support R&D 19-‐2012 Physicists Creative Industry Support R&D 19-‐2021 Atmospheric and Space Scientists Creative Industry Support R&D 19-‐2031 Chemists Creative Industry Support R&D 19-‐2032 Materials Scientists Creative Industry Support R&D 19-‐2041 Environmental Scientists and Specialists, Including

Health Creative Industry Support R&D

19-‐2042 Geoscientists, Except Hydrologists and Geographers

Creative Industry Support R&D

19-‐2043 Hydrologists Creative Industry Support R&D 19-‐2099 Physical Scientists, All Other Creative Industry Support R&D 19-‐3011 Economists Creative Industry Support R&D 19-‐3022 Survey Researchers Creative Industry Support R&D 19-‐3031 Clinical, Counseling, and School Psychologists Creative Industry Support R&D 19-‐3032 Industrial-‐Organizational Psychologists Creative Industry Support R&D 19-‐3039 Psychologists, All Other Creative Industry Support R&D 19-‐3041 Sociologists Creative Industry Support R&D 19-‐3091 Anthropologists and Archeologists Creative Industry Support R&D 19-‐3092 Geographers Creative Industry Support R&D 19-‐3093 Historians Creative Industry Support R&D 19-‐3094 Political Scientists Creative Industry Support R&D 19-‐3099 Social Scientists and Related Workers, All Other Creative Industry Support R&D


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 19-‐4011 Agricultural and Food Science Technicians Creative Industry Support R&D 19-‐4021 Biological Technicians Creative Industry Support R&D 19-‐4031 Chemical Technicians Creative Industry Support R&D 19-‐4041 Geological and Petroleum Technicians Creative Industry Support R&D 19-‐4051 Nuclear Technicians Creative Industry Support R&D 19-‐4061 Social Science Research Assistants Creative Industry Support R&D 19-‐4091 Environmental Science and Protection

Technicians, Including Health Creative Industry Support R&D

19-‐4092 Forensic Science Technicians Creative Industry Support R&D 19-‐4093 Forest and Conservation Technicians Creative Industry Support R&D 19-‐4099 Life, Physical, and Social Science Technicians, All

Other Creative Industry Support R&D

25-‐4021 Librarians Creative Industry Support R&D 25-‐4031 Library Technicians Creative Industry Support R&D 11-‐9111 Medical and Health Services Managers Creative Industry Support Services 43-‐4121 Library Assistants, Clerical Creative Industry Support Services 43-‐4171 Receptionists and Information Clerks Creative Industry Support Services 43-‐5021 Couriers and Messengers Creative Industry Support Services 43-‐9021 Data Entry Keyers Creative Industry Support Services 43-‐9022 Word Processors and Typists Creative Industry Support Services 43-‐9031 Desktop Publishers Creative Industry Support Services 11-‐3011 Administrative Services Managers Creative Industry Support Services 43-‐2099 Communications Equipment Operators, All Other DATA Communications 15-‐1071 Network and Computer Systems Administrators DATA Internet 15-‐1081 Network Systems and Data Communications

Analysts DATA Internet

15-‐1122 Information Security Analysts DATA Internet 15-‐1134 Web Developers DATA Internet 15-‐1142 Network and Computer Systems Administrators* DATA Internet 15-‐1143 Computer Network Architects DATA Internet 15-‐1152 Computer Network Support Specialists DATA Internet 15-‐1011 Computer and Information Scientists, Research DATA R&D 15-‐1111 Computer and Information Research Scientists DATA R&D 15-‐2021 Mathematicians DATA R&D 15-‐2041 Statisticians DATA R&D 15-‐2091 Mathematical Technicians DATA R&D 15-‐2099 Mathematical Science Occupations, All Other DATA R&D 25-‐1022 Mathematical Science Teachers, Postsecondary DATA R&D 43-‐9111 Statistical Assistants DATA R&D 43-‐5111 Weighers, Measurers, Checkers, and Samplers,

Recordkeeping DATA Sensor


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 51-‐2093 Timing Device Assemblers and Adjusters DATA Sensor 43-‐2011 Switchboard Operators, Including Answering

Service DATA Telecomm

43-‐2021 Telephone Operators DATA Telecomm 49-‐2021 Radio, Cellular, and Tower Equipment Installers

and Repairs DATA Telecomm

49-‐2022 Telecommunications Equipment Installers and Repairers, Except Line Installers

DATA Telecomm

49-‐9052 Telecommunications Line Installers and Repairers DATA Telecomm 11-‐9041 Architectural and Engineering Managers Design Arch/Eng 17-‐1011 Architects, Except Landscape and Naval Design Architecture 17-‐1012 Landscape Architects Design Architecture 25-‐1031 Architecture Teachers, Postsecondary Design Architecture 17-‐2011 Aerospace Engineers Design Engineering 17-‐2021 Agricultural Engineers Design Engineering 17-‐2031 Biomedical Engineers Design Engineering 17-‐2041 Chemical Engineers Design Engineering 17-‐2071 Electrical Engineers Design Engineering 17-‐2081 Environmental Engineers Design Engineering 17-‐2111 Health and Safety Engineers, Except Mining Safety

Engineers and Inspectors Design Engineering

17-‐2112 Industrial Engineers Design Engineering 17-‐2121 Marine Engineers and Naval Architects Design Engineering 17-‐2131 Materials Engineers Design Engineering 17-‐2141 Mechanical Engineers Design Engineering 17-‐2151 Mining and Geological Engineers, Including Mining

Safety Engineers Design Engineering

17-‐2161 Nuclear Engineers Design Engineering 17-‐2171 Petroleum Engineers Design Engineering 17-‐2199 Engineers, All Other Design Engineering 17-‐3012 Electrical and Electronics Drafters Design Engineering 17-‐3013 Mechanical Drafters Design Engineering 17-‐3019 Drafters, All Other Design Engineering 17-‐3021 Aerospace Engineering and Operations

Technicians Design Engineering

17-‐3023 Electrical and Electronics Engineering Technicians Design Engineering 17-‐3024 Electro-‐Mechanical Technicians Design Engineering 17-‐3025 Environmental Engineering Technicians Design Engineering 17-‐3026 Industrial Engineering Technicians Design Engineering 17-‐3027 Mechanical Engineering Technicians Design Engineering 17-‐3029 Engineering Technicians, Except Drafters, All

Other Design Engineering


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 25-‐1032 Engineering Teachers, Postsecondary Design Engineering 41-‐9031 Sales Engineers Design Engineering 27-‐1021 Commercial and Industrial Designers Design Industrial Design 27-‐1023 Floral Designers Design Other Design 27-‐1025 Interior Designers Design Other Design 27-‐1029 Designers, All Other Design Other Design 27-‐1022 Fashion Designers Design Textiles 51-‐6021 Pressers, Textile, Garment, and Related Materials Design Textiles 51-‐6031 Sewing Machine Operators Design Textiles 51-‐6041 Shoe and Leather Workers and Repairers Design Textiles 51-‐6042 Shoe Machine Operators and Tenders Design Textiles 51-‐6051 Sewers, Hand Design Textiles 51-‐6052 Tailors, Dressmakers, and Custom Sewers Design Textiles 51-‐6061 Textile Bleaching and Dyeing Machine Operators

and Tenders Design Textiles

51-‐6062 Textile Cutting Machine Setters, Operators, and Tenders

Design Textiles

51-‐6063 Textile Knitting and Weaving Machine Setters, Operators, and Tenders

Design Textiles

51-‐6064 Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders

Design Textiles

51-‐6092 Fabric and Apparel Patternmakers Design Textiles 51-‐6099 Textile, Apparel, and Furnishings Workers, All

Other Design Textiles

17-‐1021 Cartographers and Photogrammetrists Design Urban 17-‐1022 Surveyors Design Urban 17-‐2051 Civil Engineers Design Urban 17-‐3011 Architectural and Civil Drafters Design Urban 17-‐3022 Civil Engineering Technicians Design Urban 17-‐3031 Surveying and Mapping Technicians Design Urban 19-‐3051 Urban and Regional Planners Design Urban 25-‐9011 Audio-‐Visual and Multimedia Collections

Specialists Entertainment Film & Media

27-‐1014 Multimedia Artists and Animators Entertainment Film & Media 27-‐4011 Audio and Video Equipment Technicians Entertainment Film & Media 27-‐4031 Camera Operators, Television, Video, and Motion

Picture Entertainment Film & Media

27-‐4032 Film and Video Editors Entertainment Film & Media 39-‐3021 Motion Picture Projectionists Entertainment Film & Media 11-‐9071 Gaming Managers Entertainment Recreation 27-‐2021 Athletes and Sports Competitors Entertainment Recreation 27-‐2022 Coaches and Scouts Entertainment Recreation


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 27-‐2023 Umpires, Referees, and Other Sports Officials Entertainment Recreation 27-‐3010 Announcers Entertainment Recreation 27-‐3012 Public Address System and Other Announcers Entertainment Recreation 29-‐9091 Athletic Trainers Entertainment Recreation 33-‐3031 Fish and Game Wardens Entertainment Recreation 33-‐9031 Gaming Surveillance Officers and Gaming

Investigators Entertainment Recreation

33-‐9092 Lifeguards, Ski Patrol, and Other Recreational Protective Service Workers


39-‐1011 Gaming Supervisors Entertainment Recreation 39-‐1012 Slot Supervisors Entertainment Recreation 39-‐3011 Gaming Dealers Entertainment Recreation 39-‐3012 Gaming and Sports Book Writers and Runners Entertainment Recreation 39-‐3019 Gaming Service Workers, All Other Entertainment Recreation 39-‐3031 Ushers, Lobby Attendants, and Ticket Takers Entertainment Recreation 39-‐3091 Amusement and Recreation Attendants Entertainment Recreation 39-‐3099 Entertainment Attendants and Related Workers,

All Other Entertainment Recreation

39-‐6021 Tour Guides and Escorts Entertainment Recreation 39-‐6022 Travel Guides Entertainment Recreation 39-‐7011 Tour Guides and Escorts Entertainment Recreation 39-‐7012 Travel Guides Entertainment Recreation 39-‐9031 Fitness Trainers and Aerobics Instructors Entertainment Recreation 41-‐2011 Cashiers Entertainment Recreation 41-‐2012 Gaming Change Persons and Booth Cashiers Entertainment Recreation 43-‐3041 Gaming Cage Workers Entertainment Recreation 49-‐2096 Electronic Equipment Installers and Repairers,

Motor Vehicles Entertainment Recreation

49-‐2097 Electronic Home Entertainment Equipment Installers and Repairers


49-‐9063 Musical Instrument Repairers and Tuners Entertainment Toys 25-‐4010 Archivists, Curators, and Museum Technicians Fine Arts Museums 25-‐4011 Archivists Fine Arts Museums 25-‐4012 Curators Fine Arts Museums 25-‐4013 Museum Technicians and Conservators Fine Arts Museums 27-‐2041 Music Directors and Composers Fine Arts Music 27-‐2042 Musicians and Singers Fine Arts Music 13-‐1011 Agents and Business Managers of Artists,

Performers, and Athletes Fine Arts Performing Arts

25-‐1121 Art, Drama, and Music Teachers, Postsecondary Fine Arts Performing Arts 27-‐2011 Actors Fine Arts Performing Arts 27-‐2012 Producers and Directors Fine Arts Performing Arts


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 27-‐2031 Dancers Fine Arts Performing Arts 27-‐2032 Choreographers Fine Arts Performing Arts 27-‐2099 Entertainers and Performers, Sports and Related

Workers, All Other Fine Arts Performing Arts

39-‐3092 Costume Attendants Fine Arts Performing Arts 39-‐5091 Makeup Artists, Theatrical and Performance Fine Arts Performing Arts 27-‐1011 Art Directors Fine Arts Visual Arts 27-‐1012 Craft Artists Fine Arts Visual Arts 27-‐1013 Fine Artists, Including Painters, Sculptors, and

Illustrators Fine Arts Visual Arts

27-‐1019 Artists and Related Workers, All Other Fine Arts Visual Arts 51-‐9071 Jewelers and Precious Stone and Metal Workers Fine Arts Visual Arts 27-‐1026 Merchandise Displayers and Window Trimmers Media/Communications Advertising 41-‐3011 Advertising Sales Agents Media/Communications Advertising 41-‐9011 Demonstrators and Product Promoters Media/Communications Advertising 41-‐9012 Models Media/Communications Advertising 11-‐2011 Advertising and Promotions Managers Media/Communications Advertising 11-‐2022 Sales Managers Media/Communications Advertising 27-‐3011 Radio and Television Announcers Media/Communications Broadcasting 27-‐3021 Broadcast News Analysts Media/Communications Broadcasting 27-‐4012 Broadcast Technicians Media/Communications Broadcasting 27-‐4013 Radio Operators Media/Communications Broadcasting 27-‐4014 Sound Engineering Technicians Media/Communications Broadcasting 27-‐4099 Media and Communication Equipment Workers,

All Other Media/Communications Broadcasting

27-‐1024 Graphic Designers Media/Communications Graphic Design 27-‐4021 Photographers Media/Communications Graphic Design 13-‐1161 Market Research Analysts and Marketing

Specialists* Media/Communications Marketing

19-‐3021 Market Research Analysts Media/Communications Marketing 27-‐1027 Set and Exhibit Designers Media/Communications Marketing 41-‐9041 Telemarketers Media/Communications Marketing 11-‐2021 Marketing Managers Media/Communications Marketing 27-‐3099 Media and Communication Workers, All Other Media/Communications Other 51-‐5011 Bindery Workers Media/Communications Printing 51-‐5012 Bookbinders Media/Communications Printing 51-‐5021 Job Printers Media/Communications Printing 51-‐5022 Prepress Technicians and Workers Media/Communications Printing 51-‐5023 Printing Machine Operators Media/Communications Printing 51-‐5111 Prepress Technicians and Workers Media/Communications Printing 51-‐5112 Printing Press Operators Media/Communications Printing


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 51-‐5113 Print Binding and Finishing Workers Media/Communications Printing 51-‐9131 Photographic Process Workers Media/Communications Printing 51-‐9132 Photographic Processing Machine Operators Media/Communications Printing 51-‐9151 Photographic Process Workers and Processing

Machine Operators Media/Communications Printing

51-‐9194 Etchers and Engravers Media/Communications Printing 27-‐3031 Public Relations Specialists Media/Communications Public Relations 11-‐2031 Public Relations and Fundraising Managers Media/Communications Public Relations 27-‐3020 News Analysts, Reporters and Correspondents Media/Communications Publishing 27-‐3022 Reporters and Correspondents Media/Communications Publishing 27-‐3041 Editors Media/Communications Publishing 27-‐3042 Technical Writers Media/Communications Publishing 27-‐3043 Writers and Authors Media/Communications Publishing 43-‐9081 Proofreaders and Copy Markers Media/Communications Publishing 17-‐2061 Computer Hardware Engineers SW/HW Engineering 17-‐2072 Electronics Engineers, Except Computer SW/HW Engineering 19-‐1042 Medical Scientists, Except Epidemiologists SW/HW Health Devices 49-‐9062 Medical Equipment Repairers SW/HW Health Devices 51-‐9081 Dental Laboratory Technicians SW/HW Health Devices 51-‐9082 Medical Appliance Technicians SW/HW Health Devices 51-‐9083 Ophthalmic Laboratory Technicians SW/HW Health Devices 49-‐9064 Watch Repairers SW/HW Manufacturing 49-‐9069 Precision Instrument and Equipment Repairers, All

Other SW/HW Manufacturing

51-‐2022 Electrical and Electronic Equipment Assemblers SW/HW Manufacturing 51-‐9141 Semiconductor Processors SW/HW Manufacturing 41-‐4011 Sales Representatives, Wholesale and

Manufacturing, Technical and Scientific Products SW/HW Retail

15-‐1021 Computer Programmers SW/HW Software 15-‐1031 Computer Software Engineers, Applications SW/HW Software 15-‐1032 Computer Software Engineers, Systems Software SW/HW Software 15-‐1041 Computer Support Specialists SW/HW Software 15-‐1051 Computer Systems Analysts SW/HW Software 15-‐1061 Database Administrators SW/HW Software 15-‐1099 Computer specialists, all other SW/HW Software 15-‐1121 Computer Systems Analysts SW/HW Software 15-‐1131 Computer Programmers SW/HW Software 15-‐1132 Software Developers, Applications SW/HW Software 15-‐1133 Software Developers, Systems Software SW/HW Software 15-‐1141 Database Administrators SW/HW Software 15-‐1150 Computer Support Specialists SW/HW Software


OCC_CODE OCC_TITLE Cluster Sub-‐Cluster 15-‐1151 Computer User Support Specialists SW/HW Software 15-‐1179 Information Security Analysts, Web Developers,

and Computer Network Architects SW/HW Software

15-‐1199 Computer Occupations, All Other SW/HW Software 15-‐1799 Computer Occupations, All Other* SW/HW Software 25-‐1021 Computer Science Teachers, Postsecondary SW/HW Software 11-‐3021 Computer and Information Systems Managers SW/HW Software


Definition of Study Region The region used for this study is the Pittsburgh metropolitan Core-‐Based Statistical Area (CBSA), the seven-‐county area shown in the map below. This includes just the Pittsburgh region, and does not include the New Castle micropolitan area of Lawrence County. The table below the map lists the seven counties and indicates whether each county is part of the central core of the metropolitan region or an outlying county.

Pittsburgh CBSA (Map by US Census Bureau) CBSA Code 38300 CBSA Title Pittsburgh, PA Metropolitan Statistical Area

The CBSA definitions are primarily based on contiguous geographies, population densities and cores, and commuting patterns. The full definitions are maintained by the Office of Management and the Budget (OMB) at the White House and are part of the federal FIPS-‐55 standard. This is the standard metropolitan area definition for all US metropolitan and micropolitan areas and is what is used by all government reporting agencies. This represents the US federal standard for metro definitions. County/County Equivalent State Name FIPS

State Code

FIPS County Code

Central/Outlying County

Allegheny County Pennsylvania 42 003 Central Armstrong County Pennsylvania 42 005 Outlying Beaver County Pennsylvania 42 007 Central Butler County Pennsylvania 42 019 Central Fayette County Pennsylvania 42 051 Outlying Washington County Pennsylvania 42 125 Central Westmoreland County Pennsylvania 42 129 Central


Benchmarking Pittsburgh’s Future Prosperity Pittsburgh was benchmarked against 19 other metropolitan regions from across the US. The table below lists the benchmark regions and shows their populations, Creativity Index score and overall ranking (out of 361 metropolitan regions) on the Creativity, Technology, Talent, and Inclusiveness scores. Among the benchmarks, Boulder and San Francisco generally have the highest scores, while Memphis and Birmingham, AL have the lowest scores among these benchmark regions. However, their overall rankings still show them to be ranked above at least one-‐third of all US metro regions. The comparison regions for Pittsburgh were selected to achieve geographic diversity across all regions of the country while keeping the total population close to Pittsburgh’s. Los Angeles and Boulder are notable exceptions that we included for other comparative purposes.

Metropolitan Area Pop 2010 CR Index CRIdx Rank

Tech Rank

Tal Rank

Tol Rank

Pittsburgh, PA 2,360,259 0.557 143 76 107 300 Austin-‐Round Rock, TX 1,589,393 0.916 16 5 54 34 Baltimore-‐Towson, MD 2,669,987 0.837 40 55 21 103 Birmingham-‐Hoover, AL 1,112,213 0.517 165 141 75 310 Boulder, CO 295,524 0.981 1 10 5 9 Cincinnati-‐Middletown, OH-‐KY-‐IN 2,140,796 0.633 114 79 104 216 Cleveland-‐Elyria-‐Mentor, OH 2,101,821 0.676 95 87 94 173 Denver-‐Aurora, CO 2,451,038 0.896 24 42 25 48 Detroit-‐Warren-‐Livonia, MI 4,452,548 0.787 53 36 53 145 Kansas City, MO-‐KS 2,013,797 0.837 40 24 48 106 Los Angeles-‐Long Beach-‐Santa Ana, CA 12,762,126 0.901 22 26 60 24 Louisville, KY-‐IN 1,235,476 0.536 155 168 167 171 Memphis, TN -‐MS-‐AR 1,287,231 0.523 163 69 200 251 New Orleans -‐Metairie-‐Kenner, LA 1,153,788 0.555 145 202 130 152 Orlando, FL 2,023,605 0.784 56 47 163 27 Philadelphia-‐Camden-‐Wilmington, PA-‐NJ-‐DE-‐MD 5,910,593 0.806 50 64 51 97 Portland-‐Vancouver-‐Beaverton, OR-‐WA 2,163,436 0.930 13 4 59 16 Salt Lake City, UT 1,090,416 0.823 47 41 68 86 San Francisco-‐Oakland-‐Fremont, CA 4,218,534 0.970 2 3 16 17 San Jose-‐Sunnyvale-‐Santa Clara, CA 1,784,130 0.933 12 2 2 71 St. Louis, MO-‐IL 2,803,776 0.632 116 84 69 249


Benchmark Summary: Pittsburgh among 20 Peer Regions The following tables compare Pittsburgh to the other nineteen regions across a wide variety of regional measures. The benchmarks are provided in six general areas: Summary statistics, Overall performance, Technology (Innovation), Talent (Workforce), Inclusiveness (Culture and Diversity), and Territorial Assets (Quality of Life). 20 Regions in Peer Group: Austin, TX; Baltimore MD; Birmingham AL; Cincinnati OH; Cleveland OH; Denver CO; Detroit MI; Kansas City MO; Los Angeles CA; Louisville KY; Memphis TN; New Orleans LA; Orlando FL; Philadelphia PA; Pittsburgh PA; Portland OR; Salt Lake City UT; San Francisco CA; San Jose CA; St Louis MO

Summary Statistics Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer

Maximum US Metro Average

Total Population, 2010 2,360,259 8 1,090,416 2,866,248 12,762,126 696,757 GDP (millions) 2011 $117,845 10 $53,547 $168,326 $747,306 $36,736 Median Age, 2010 42.2 1 30.5 36.7 42.2 36.7

Overall Cost of Living Index 94.8 10 85.9 105.3 162.7 100.0

Overall Performance Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer


Population Growth (05-‐10) 1.9% 16 -‐15% 3.7% 15.7% 34.3% Job Growth (06-‐11) 0.6% 5 -‐12.4% -‐1.7% 16.4% -‐2.3%

GDP per capita, 2011 $43,045 13 $39,876 $50,570 $94,587 $45,222 Change in Average Wage (06-‐

11) 18.8% 1 5.7% 14.6% 18.8% 12.7%

Average Wage (11) $43,561 15 $39,188 $47,111 $69,858 $47,999 Creativity Index 0.557 16 0.517 0.752 0.970 0.500

Technology Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer


Overall Technology Index 0.722 14 0.447 0.778 0.983 0.500 Total Patents, 2009 585 10 76 1,513 8,491 232

Patents per 1,000, 2009 0.25 11 0.07 0.58 4.76 0.33 Patent Growth, Short Term (05-‐

09) 0.1% 14 -‐4.8% 1.0% 9.2% -‐1.8%

Patent Growth, Long Term (99-‐09) -‐2.6% 15 -‐6.5% -‐0.2% 4.9% -‐3.3%

High Tech LQ, 2010 0.94 14 0.51 1.20 3.24 1.00 Tech Pole Index 0.86 13 0.13 2.11 10.03 1.00


Talent Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer


Overall Talent Index 0.706 16 0.449 0.786 0.997 0.500 Creative Class as % of

Workforce, 2010 31.7% 12 28.5% 34.1% 46.9% 34.2%

Super Creative Core as % of Workforce, 2010 12.2% 13 9.3% 13.5% 24.1% 13.6%

Talent Index (Pop > 25, BA and above), 2010 28.7% 13 24.6% 31.5% 44.5% 25.3%

Human Capital Flight Index 0.629 19 0.567 0.754 1.080 0.621 Pop > 25, Graduate and/or Professional Degree, 2010 10.7% 10 8.7% 11.7% 19.4% 9.2%

% Less than High School, 2010 8.9% n/a 8.9% 12.8% 22.4% 14.4% % High School Diploma, 2010 36.8% n/a 16.2% 26.7% 36.8% 29.9%

% Associates or Some Coll, 2010 25.6% n/a 24.2% 29.0% 34.5% 30.3% % Bachelor's Degree, 2010 18.0% n/a 15.3% 19.8% 26.6% 16.1%

Working Class as % of Workforce, 2010 20.2% 10 16.3% 20.2% 26.2% 19.5%

Service Class as % of Workforce, 2010 48.1% 3 36.6% 45.6% 53.2% 46.1%

Inclusiveness Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer


Overall Inclusiveness Index 0.222 19 0.207 0.489 0.684 0.500 Non-‐white Population (% Pop),

2010 15.6% 13 3.7% 21.5% 71.1% 25.2%

Melting Pot Index (% Pop), 2010 3.0% 20 3.0% 11.5% 35.6% 7.5% Gay and Lesbian Index, 2010 0.77 18 0.70 1.10 2.22 1.00

Bohemian Index, 2010 0.83 17 0.66 1.16 2.62 0.59 Average Bohemian Wage, 2010 $33,353 19 $32,151 $41,061 $66,075 $28,000

Bohemian Wage Index, 2010 0.70 18 0.62 1.11 3.86 0.52 Integration Index, 2010 0.66 16 0.50 0.75 0.97 0.86


Territorial Assets Pittsburgh Peer

Ranking Peer

Minimum Peer

Average Peer


Social and Cultural Arts and Cultural

Establishments per 100,000, 2010

12.3 11 7.4 16.6 82.8 12.0

Restaurants and Bars per 100,000, 2010 213.2 4 150.0 192.4 241.1 184.7

Student/Teacher Ratio, 2010 13.5 2 13.4 16.8 23.0 15.6 Doctor's per 100,000, 2010 195.6 5 100.8 162.8 225.0 116.0

Regional Amenities

Golf Courses per 100,000, 2010 6.4 1 1.6 3.7 6.4 5.6 USDA Natural Amenity Scale 0.40 10 -‐1.66 1.68 9.54 0.06

Average July-‐January Temperature Difference (°F) 42.9 13 15.8 36.7 49.7 42.9

Water Share of Regional Area 1.29% 16 0.43% 9.85% 47.43% 4.59%

Housing & Transportation

Population Density (per KM2), 2010 172.5 10 44.1 267.6 1,016.3 110.8

Home Ownership Affordability Index, 2010 0.77 2 0.60 0.72 0.77 0.76

Rental Affordability Index, 2010 0.84 4 0.77 0.82 0.85 0.82

Commute Time (minutes), 2010 25.1 9 22.2 25.5 29.2 21.2


Summary Statistics Total Population, 2010

Total Population, ACS (American Communities Survey, US Census), 2010 GDP (millions) 2011

Metropolitan GDP, Bureau of Economic Analysis, 2011

Median Age, 2010

Median Age, ACS (American Communities Survey, US Census), 2010 Overall Cost of Living Index

Cost of Living Index, ACCRA, 2010

Overall Performance Population Growth (05-‐10)

Population Growth, 2005-‐2010, US Census

Job Growth (06-‐11)

Job Growth, Total Employed, 2006-‐2011, Bureau of Labor Statistics, Occupational Employment Survey (OES)

GDP per capita, 2011

GDP (2011) divided by total population (2010)

Change in Average Wage (06-‐11)

Change in average wage, 2006-‐2011, Bureau of Labor Statistics, Occupational Employment Survey (OES)

Average Wage (11)

Average wage, 2011, Bureau of Labor Statistics, Occupational Employment Survey (OES)

Creativity Index

Creative Class employment, 2011, Bureau of Labor Statistics, Occupational Employment Survey (OES)

Technology

Overall Technology Index

Equally weighted, Tech-‐Pole, long term patent growth, patents per capita

Total Patents, 2009

USPTO, Patent applications from inventors in the region Patents per 1,000, 2009

USPTO, Patent applications divided by total population in thousands

Patent Growth, Short Term (05-‐09)

Change in number of patent applications 2005-‐2009, USPTO

Patent Growth, Long Term (99-‐09)

Change in number of patent applications 1999-‐2009, USPTO

High Tech LQ, 2010

Location quotient of employment in high-‐tech industries as defined by the Milken Institute

Tech Pole Index

Product of high-‐tech LQ and share of total US high-‐tech employment in the region

Talent

Overall Talent Index


Creative Class as % of Workforce, 2010


Super Creative Core as % of Workforce, 2010

Super Creative core employment, 2010, Bureau of Labor Statistics, Occupational Employment Survey (OES)


Talent Index (Pop > 25, BA and above), 2010

Percentage of population age 25 and above with a Bachelor's degree or higher, ACS (2006-‐2010; 5-‐year 2010 sample)

Human Capital Flight Index

Percentage of the workforce, age 25+, with at least a college degree divided by the share age 20 to 24 currently attending college or university. A value greater than 1.0 indicates the region has "brain gain" while a value less than 1.0 indicates the region is suffering from "brain drain"; Census, ACS

Pop > 25, Graduate and/or Professional Degree, 2010

Percentage of population age 25 and above with a graduate or professional degree or doctoral degree, ACS (2006-‐2010; 5-‐year 2010 sample)

% Less than High School, 2010

Percentage of population age 25 and above with less than a high school degree, ACS (2006-‐2010; 5-‐year 2010 sample)

% High School Diploma, 2010

Percentage of population age 25 and above with only a high school diploma, ACS (2006-‐2010; 5-‐year 2010 sample)

% Associates or Some College, 2010

Percentage of population age 25 and above with a high school degree and an associate's degree or some college, ACS (2006-‐2010; 5-‐year 2010 sample)

% Bachelor's Degree, 2010

Percentage of population age 25 and above with only a Bachelor's degree, ACS (2006-‐2010; 5-‐year 2010 sample)

Working Class as % of Workforce, 2010

Working class employment, 2010, Bureau of Labor Statistics, Occupational Employment Survey (OES)

Service Class as % of Workforce, 2010

Service class employment, 2010, Bureau of Labor Statistics, Occupational Employment Survey (OES)

Inclusiveness

Overall Inclusiveness Index

Combination of Melting Pot, Gay/Lesbian, Bohemian and Integration indices

Non-‐white Population (% Pop), 2010

Percentage of the population this is not white or mixed race, ACS, 2010

Melting Pot Index (% Pop), 2010

Percentage of the population born outside of the U.S., ACS, 2010 Gay and Lesbian Index, 2010

Location Quotient for same sex couples, ACS, 2010

Bohemian Index, 2010

Location Quotient for individuals reporting bohemian (arts, writers, designers, etc.) occupations, ACS, 2010

Average Bohemian Wage, 2010

Average wage for individuals reporting bohemian (arts, writers, designers, etc.) occupations, ACS, 2010

Bohemian Wage Index, 2010

Bohemian wages compared to average U.S. wages for bohemians, ACS, 2010

Integration Index, 2010

Index measuring how well the race/ethnicity distribution within each Census tract within the region matches the overall race/ethnicity distribution across the entire region, ACS, 2010


Territorial Assets Social and Cultural Arts and Cultural Establishments

per 100,000, 2010

County Business Patterns, US Census, arts and culture establishments per 100,000 residents, 2010

Restaurants and Bars per 100,000, 2010

County Business Patterns, US Census, restaurants and bars per 100,000 residents, 2010

Student/Teacher Ratio, 2010

Ratio of total number of students to total number of teachers, primary and secondary education, US Department of Education, 2010

Doctor's per 100,000, 2010

Number of doctors per 100,000 residents, BLS, OES occupational data, 2010

Regional Amenities

Golf Courses per 100,000, 2010

County Business Patterns, US Census, golf courses per 100,000 residents, 2010

USDA Natural Amenity Scale

Natural Amenity Scale (temperatures, climate, geological natural resource spaces, available water, others), US Department of Agriculture, 1999

Average July-‐January Temperature Difference (°F)

Difference between average temperature in July and average temperature in January, measure of climate variation, USDA, 1999

Water Share of Regional Area

Total share of regional area that is water, US Census, 2010

Housing & Transportation Population Density (per KM2),

2010

Total population divided by total land area of region, US Census, 2010

Home Ownership Affordability Index, 2010

1 -‐ Average total home ownership costs divided by average household income, share of income remaining after average home ownership costs are paid, ACS, 2010

Rental Affordability Index, 2010

1 -‐ Average total rental costs divided by average household income, share of income remaining after average rental costs are paid, ACS, 2010

Commute Time (minutes), 2010

Average commute time in minutes, ACS, 2010


Inclusiveness Changes in the Region The table below compares Pittsburgh’s Inclusiveness/diversity scores from 2000 and 2010. Both the score for Pittsburgh and the national score for various items are shown. As the number of metropolitan regions varies from 2000 to 2010, the ranking percentile is shown instead – so a higher percentile score indicates a better ranking. For example, in 2000, Pittsburgh’s Melting Pot score (foreign born) was 2.6% (0.026) which put Pittsburgh at the top of the bottom quartile (24.5); in 2010, the score had risen to 3% (0.030) but the national score also increased as did the scores for many other metros. As a result, although Pittsburgh improved its share of foreign-‐born population, it actually lost ground in comparison to other regions, and in 2010 was nearly a full percentage point lower ranked against all other US metros. The table provides comparison for those Inclusiveness and diversity metrics that can be compared in the ten-‐year Census-‐to-‐Census period. Although losing ground on foreign-‐born (Melting Pot), the Pittsburgh region does show improvements in the Gay and Boho Indexes and in the share of the total population that is non-‐white. But, on almost all measures of Inclusiveness and diversity, the Pittsburgh region scores well below the national average, which includes many, many micropolitan and metropolitan regions much smaller than Pittsburgh. Traditionally, smaller regions underperform on measures of diversity compared to more populous regions. Pittsburgh’s low rankings in the benchmarking report above result from Pittsburgh being compared only to larger regions. Inclusiveness Changes 2000-‐2010

2000 2010 Pittsburgh Change

Pittsburgh Score

Rank Percentile

National Score

Pittsburgh Score

Rank Percentile

National Score Score Rank

Melting Pot Index 0.026 24.5 0.074 0.030 23.5 0.075 0.004 -‐0.926 Gay Index 0.637 25.1 0.830 0.767 34.1 0.912 0.130 9.00 Boho Index 0.880 53.2 0.947 0.833 58.3 0.824 -‐0.048 5.14 Composite Diversity (CDI) 305 30.8 491 % Non-‐white 0.105 24.2 0.203 0.156 54.8 0.238 0.051 30.6 % Interracial Marriage 0.011 13.6 0.046 Integration Index 0.661 18.8 0.811


Pittsburgh Creative Sectors The following charts and tables demonstrate the industry-‐ and occupation-‐based cluster and sub-‐cluster information for Pittsburgh’s creative sector. Each chart comes in two varieties: the first shows average annual regional growth (the average of the year-‐over-‐year changes) for the Pittsburgh region; the second shows average annual growth for that cluster/sub-‐cluster for the entire US. For each chart, the X-‐axis (horizontal) changes. As the values change, the scale of the growth numbers can also change. The reader is advised to pay careful attention to the labeling and scale of the X-‐axis between the two graphs. Often, especially when the regional cluster/sub clusters are presented, one bubble may have had some large year-‐to-‐year shifts that result in a larger range of values for the X-‐axis. The other information presented on the two charts:

• Bubble size is representative of the total number of individuals employed in that industry or occupation – the larger the bubble the greater the number of people working there. Full-‐time equivalent employment is counted so part-‐time workers are accumulated to FTE counts. Often the CBP industry data only provided a range of employment in a particular 5-‐digit industry group. When that was the case, employment is estimated at the lower end of the range plus 10%. The ten percent figure rather than the mid-‐point is used to more accurately reflect the actual employment count, whose distribution is very, very skewed to lower numbers.

• The Y-‐axis is the location quotient for the cluster/sub-‐cluster. A location quotient (LQ) is a ratio of the employment share of that cluster in the Pittsburgh region to the employment share across the entire US. It is, in effect, a measure of how concentrated a particular cluster is within the Pittsburgh economy compared to the rest of the country. For example, if the Design industry is responsible for 4% of all employment in Pittsburgh and only 2% of the US, then the LQ would be 2.00. (=4/2) However, if Design was 8% of US employment, then the Pittsburgh LQ would be 0.50 (=4/8). An LQ above 1.0 indicates that a region has a higher concentration of employment in that cluster while an LQ below 1.0 shows that the cluster is less represented across the region.

• Growth, whether regional or national, is the average of the year-‐to-‐year growth for the past five years. The most recent industry (CBP) data is from 2011 so industry cluster growth is 2005-‐2011. The most recent occupation (OES) data is from 2012 so occupation cluster growth is 2006-‐2012.

• The standard, BCG product matrix can be a helpful way to interpret cluster bubble charts. The meaningful axes are average growth above or below 0% and location quotients above or below 1.00. The quadrants then become:

o Upper Right – positive growth, high LQ – clusters that are growing and where the region has a high relative concentration.

o Upper Left – negative growth, high LQ – clusters with a high concentration but which have been in decline – from a cluster perspective, bubbles in this region could be warning signs of significant challenges to the region. If a cluster is in decline, having a high concentration of employment in that cluster may not be a good thing. This is also an place to look at differences between the regional and national growth – is the cluster in decline nationally but growing in the region or vice versa?

o Lower Left – negative growth, low LQ – clusters without any significant concentration and in decline. Clusters in this position may be safely ignored or may represent significant opportunity if the growth potential and regional concentration can both be increased.

o Lower Right – positive growth, low LQ – growing clusters but not ones that are highly concentrated in the region. These clusters could represent opportunities to try and increase the regional competitive advantage associated with an increase in regional concentration. Or, they


could become significant drains of resource, energy, and attention that produce very little reward – in effect, chasing rainbows. Clusters for which the region currently has little competitive advantage and could find it difficult to successfully grow. Another place where comparing the regional and national charts could be very enlightening – is the growth in the Pittsburgh region different from the national growth?

Along with each pair a charts, a table is provided that shows the actual numbers for all of the clusters/ subclusters presented in the charts.


Industries

Industry Clusters/Regional Growth

Industry Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Creative Industry Support 161,390 1.240 7.92% 0.57% DATA 14,148 0.696 0.75% -‐0.83% Design 50,575 1.344 3.30% -‐1.80% Entertainment 21,971 0.869 3.87% 0.45% Fine Arts 4,349 0.982 2.53% -‐1.23% Media/Communications 13,564 0.775 0.81% -‐3.31% Software/Hardware 16,167 0.661 5.19% 1.15%


Creative Industry Support Clusters/Regional Growth

Creative Industry Support Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Associations 10,202 1.048 -‐1.02% -‐1.27% Consulting 2,401 1.384 16.39% 4.92% Post-‐Secondary 51,958 2.823 12.56% 2.70% R&D 12,854 1.619 8.43% 0.94% Services 83,975 0.899 7.71% 0.33%


Data Sciences Clusters/Regional Growth

Data Sciences Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Communications 551 0.618 -‐6.56% -‐10.67% Internet 4,516 0.901 7.98% 1.72% Sensors/Sensing 357 0.088 4.93% -‐0.82% Telecommunications 8,724 0.828 3.62% 1.89%


Design Clusters/Regional Growth

Design Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Architecture 1,337 0.845 3.87% -‐4.36% Engineering 17,588 2.043 8.20% 0.64% Manufacturing 30,676 1.254 1.30% -‐2.03% Other Design 177 0.466 8.77% -‐2.70% Textiles 157 0.153 1.93% -‐10.00% Urban Systems 640 0.338 2.48% 0.46%


Entertainment Clusters/Regional Growth

Entertainment Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Educational IT 979 1.159 19.75% 6.16% Film & Digital Media 1,139 0.434 -‐4.21% -‐0.21% Manufacturing 275 3.460 -‐12.50% -‐13.28% Post-‐production 110 0.501 83.30% 1.27% Recreation 18,581 0.916 6.22% 0.75% Toys 1,162 0.810 -‐1.56% -‐2.93%


Fine Arts Clusters/Regional Growth

Fine Arts Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Arts Organizations 429 0.581 3.90% 2.49% Arts Venues 479 0.823 -‐1.03% -‐2.60% Museums 1,836 1.800 9.02% -‐0.22% Music 691 1.155 -‐2.18% -‐3.20% Performing Arts 292 0.538 3.95% -‐0.05% Visual Arts 622 0.631 1.98% -‐2.89%


Media Communications Clusters/Regional Growth

Media Communications Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Advertising 3,000 0.852 3.07% 0.45% Broadcasting 1,809 0.735 -‐2.66% -‐1.34% Graphic Design 454 0.968 -‐3.00% -‐2.86% Marketing 276 0.273 -‐9.35% -‐2.36% Printing 4,144 0.823 3.54% -‐4.83% Public Relations 277 0.570 1.25% 3.94% Publishing 3,604 0.773 1.48% -‐5.57%


Software Hardware Clusters/Regional Growth

Software Hardware Clusters/US Growth Cluster Emp2011 LQ RegGR USGR Health Devices 2,082 0.780 -‐2.91% -‐1.32% Manufacturing 588 0.934 18.28% -‐7.14% Retail 2,522 0.563 -‐0.51% -‐3.38% Software 10,975 0.650 10.51% 3.65%


Industry Establishment Counts The table below presents the same information as was presented in the industry-‐based cluster charts but instead of total employment, the total number of firms is used as the measure of size. Essentially, the results are the same, but some differences could be noted. Looking at number of establishments provides a different, but related view of the industry clusters in Pittsburgh’s creative sector. Pittsburgh US LQ 2011 GR1011 AvgEstGR 2011 GR1011 Avg

EstGR Cluster Subclus Totest Est totest Est Creative Industry Support

Associations 1.413 1,394 -‐1.13% -‐1.15% 122,840 -‐1.15% -‐0.85%

Consulting 0.718 194 -‐6.73% -‐1.15% 33,667 -‐3.07% 2.15% Post-‐Sec 0.974 155 8.39% 2.11% 19,810 1.37% 1.07% R&D 1.454 317 1.93% 0.23% 27,160 1.86% 0.44% Services 0.956 2,372 -‐2.91% 0.22% 309,008 -‐1.11% 0.61% Creative Industry Support Total 1.077 4,432 -‐1.84% -‐0.25% 512,485 -‐1.01% 0.33% DATA Communications 0.615 6 20.00% -‐18.21% 1,215 -‐1.14% -‐10.73% Internet 0.859 129 17.27% -‐3.42% 18,692 5.19% -‐2.72% Sensor 0.727 63 6.78% -‐2.74% 10,790 -‐2.72% -‐1.60% Telecomm 1.098 451 -‐1.96% 4.02% 51,161 -‐2.14% 2.36% DATA Total 0.987 649 2.37% -‐0.07% 81,858 -‐0.62% -‐0.75% Design Architecture 0.778 165 -‐2.94% -‐1.66% 26,420 -‐3.81% -‐2.67% Engineering 1.252 601 0.67% 0.71% 59,783 -‐0.50% 0.33% Manufacturing 1.018 1,459 -‐0.07% -‐0.63% 178,483 1.60% 0.28% Other Design 0.568 60 -‐6.25% -‐1.48% 13,145 -‐1.67% -‐1.64% Textiles 0.658 13 0.00% -‐0.30% 2,461 -‐2.11% -‐5.28% Urban 0.475 25 -‐7.41% -‐0.24% 6,558 0.31% 1.54% Design Total 1.009 2,323 -‐0.34% -‐0.42% 286,850 0.42% -‐0.15% Entertainment Educational IT 0.959 58 -‐1.69% 2.92% 7,532 0.56% 3.20% Film & Media 0.609 103 0.98% 0.04% 21,059 0.90% 0.22% Manufacturing 0.268 1 0.00% -‐8.33% 465 0.22% -‐1.71% Post-‐production 0.518 10 -‐9.09% 2.88% 2,403 0.88% 2.20% Recreation 1.004 1,056 -‐1.95% -‐1.22% 131,042 -‐0.07% -‐0.14% Toys 0.878 80 -‐6.98% -‐4.59% 11,345 -‐2.37% -‐2.19% Entertainment Total 0.936 1,307 -‐2.10% -‐1.24% 173,846 -‐0.07% -‐0.09% Fine Arts Arts

Organizations 1.001 94 0.00% 0.30% 11,700 1.69% 1.86%

Arts Venues 1.136 30 -‐3.23% -‐2.45% 3,290 0.73% -‐1.21% Museums 0.782 71 0.00% -‐1.18% 11,308 -‐1.27% -‐1.39% Music 1.080 72 9.09% -‐0.98% 8,302 -‐0.31% -‐1.38% Performing Arts 0.360 65 4.84% 1.26% 22,505 1.16% 2.01%


Pittsburgh US LQ 2011 GR1011 AvgEstGR 2011 GR1011 Avg

EstGR Cluster Subclus Totest Est totest Est Visual Arts 1.008 159 -‐3.64% -‐0.16% 19,652 -‐1.33% -‐1.54% Fine Arts Total 0.797 491 0.41% -‐0.45% 76,757 0.05% -‐0.03% Media/Communications Advertising 0.896 213 -‐0.47% -‐0.28% 29,617 -‐1.66% -‐0.95% Broadcasting 0.774 61 10.91% -‐0.48% 9,814 -‐1.27% -‐0.85% Graphic Design 0.752 92 -‐5.15% -‐4.83% 15,226 -‐1.07% -‐1.33% Marketing 0.497 25 -‐16.67% -‐5.68% 6,265 0.18% -‐0.09% Printing 1.014 236 -‐2.48% -‐2.79% 28,983 -‐4.08% -‐3.37% Public Relations 0.607 40 -‐11.11% 1.69% 8,204 -‐0.18% 2.16% Publishing 0.630 104 5.05% -‐3.39% 20,567 -‐4.04% -‐2.10% Media/Communications Total

0.809 771 -‐1.41% -‐2.29% 118,676 -‐2.38% -‐1.60%

SW/HW Health Devices 0.819 76 -‐9.52% -‐2.67% 11,552 -‐1.31% -‐0.88% Manufacturing 1.533 14 7.69% 2.95% 1,137 -‐0.52% -‐3.06% Retail 0.986 258 18.35% -‐0.53% 32,587 4.06% -‐1.12% Software 0.838 897 -‐1.64% 2.59% 133,282 0.85% 2.27% SW/HW Total 0.868 1,245 1.47% 1.40% 178,558 1.27% 1.33%


Occupations

Occupational Clusters/Regional Growth

Occupational Clusters/US Growth Cluster Emp2012 LQ RegGR USGR Creative Industry Support 41,460 1.028 1.48% -‐0.22% DATA 11,910 0.921 2.10% 4.95% Design 24,040 0.962 -‐0.22% -‐1.47% Entertainment 40,850 1.015 0.14% -‐0.02% Fine Arts 2,390 0.591 0.13% 0.70% Media/Communications 21,500 0.947 0.12% -‐0.62% SW/HW 34,790 1.033 3.34% 0.81%


Creative Support Industries/Regional Growth

Creative Support Industries/US Growth Cluster Emp2012 LQ RegGR USGR Post-‐Secondary 12,620 1.064 12.47% 1.49% R&D 10,840 0.961 6.53% 0.85% Services 18,000 1.048 -‐4.47% -‐1.89%


Data Sciences Clusters/Regional Growth

Data Sciences Clusters/US Growth Cluster Emp2012 LQ RegGR USGR Internet 7,010 0.993 15.13% 19.82% R&D 1,040 0.984 13.81% -‐0.16% Sensors 410 0.680 2.61% -‐1.91% Telecommunications 3,450 0.824 -‐8.62% -‐1.82%


Design Clusters/Regional Growth

Design Clusters/National Growth Cluster Emp2012 LQ RegGR USGR Arch/Eng 1,450 0.910 -‐1.57% 0.37% Architecture 620 0.691 -‐4.92% -‐3.07% Engineering 13,980 1.009 0.03% -‐0.04% Industrial Design 330 1.339 0.00% -‐2.25% Other Design 610 0.753 -‐1.60% -‐4.30% Textiles 730 0.248 -‐10.26% -‐6.25% Urban Systems 6,320 1.357 4.91% -‐1.47%


Entertainment Clusters/Regional Growth

Entertainment Clusters/US Growth Cluster Emp2012 LQ RegGR USGR Film & Digital Media 1,100 0.938 6.23% 1.95% Recreation 39,500 1.012 -‐0.07% -‐0.08% Toys 250 4.131 0.00% 5.91%


Fine Arts Clusters/Regional Growth

Fine Arts Clusters/US Growth Cluster Emp2012 LQ RegGR USGR Museums 230 1.025 18.28% 1.10% Music 690 1.213 2.60% 3.10% Performing Arts 1,060 0.410 -‐5.20% 0.67% Visual Arts 410 0.621 30.55% -‐0.67%


Media Communications Clusters/Regional Growth

Media Communications/US Growth Cluster Emp2012 LQ RegGR USGR Advertising 4,220 0.742 2.51% 0.47% Broadcasting 550 0.663 26.19% -‐2.17% Graphic Design 1,910 0.909 -‐1.18% -‐0.18% Marketing 8,200 1.181 1.23% 1.17% Printing 2,310 0.846 -‐6.70% -‐5.89% Public Relations 2,660 1.230 5.08% 0.23% Publishing 1,610 0.777 -‐0.82% -‐0.93%


Software Hardware Clusters/Regional Growth

Software Hardware Clusters/US Growth Cluster Emp2012 LQ RegGR USGR Engineering 1,280 0.703 -‐2.76% 0.70% Health Devices 2,670 1.501 66.85% 1.24% Manufacturing 2,340 1.181 0.63% -‐2.18% Retail 2,530 0.817 -‐3.03% -‐1.06% Software 25,970 1.039 3.69% 1.37%


Comparison to Creative Industries Study Report Industry Clusters The table below compares the report focus industries with the creative sector industry clusters. For each of the report clusters (bold headings), the industry clusters are listed. Both employment totals and establishment counts are given. Only those industry clusters that overlap with the report cluster are included. When the report cluster includes some firms in an industry that was not included in a creative sector cluster, the totals are shown as “not in a report cluster”. The totals for the six creative sector clusters that also had some firms that were not included in the report clusters are also shown. The Data Sciences cluster was completely included across several of the report clusters. The only place with complete overlap between the two was the Design/Manufacturing subcluster which intentionally maps to the report Advanced Manufacturing cluster. The relationship and overlap is summarized in the second and third table. Report Industry Cluster Establishments Employment Advanced Manufacturing 1,459 30,676

Design 1,459 30,676 Advanced Materials: Chemicals 83 3,161

-‐-‐Not in a report cluster-‐-‐ 83 3,161 Advanced Materials: Rubber and Plastics 162 5,650

-‐-‐Not in a report cluster-‐-‐ 158 5,605 Entertainment 4 45

Bio Research 281 14,321 Not in a report cluster 8 599 Creative Industry Support 197 11,640 SW/HW 76 2,082

Energy Technology 662 23,040 -‐-‐Not in a report cluster-‐-‐ 662 23,040

Hardware 21 1,414 DATA 7 826 SW/HW 14 588

Health Services 2,941 92,332 -‐-‐Not in a report cluster-‐-‐ 2,941 92,332

Professional Services and Research 881 19,598 Creative Industry Support 85 528 DATA 60 243 Design 736 18,827

Remediation and Waste Management 93 1,389 -‐-‐Not in a report cluster-‐-‐ 93 1,389

Software 991 11,842 -‐-‐Not in a report cluster-‐-‐ 94 867 SW/HW 897 10,975

Technology-‐intensive Manufacturing 47 1,542 -‐-‐Not in a report cluster-‐-‐ 44 1,428 DATA 3 114


Report Industry Cluster Establishments Employment Telecommunications 640 14,774

DATA 579 12,965 Media/Communications 61 1,809

Report Cluster not in PTC Cluster 7,040 190,846 Creative Industry Support 4,150 149,222 Design 128 1072 Entertainment 1,303 21,926 Fine Arts 491 4349 Media/Communications 710 11,755 SW/HW 258 2,522

Establishments Creative Sector Not CS Total

PTC 4,178 4,053 8,231 Not PTC 7,040

Total 11,218

Employment Creative Sector Not CS

PTC 91,318 128,422 219,740 Not PTC 190,847

282,165


Benchmark Comparisons The following section includes twelve tables. The first four use the industry-‐based cluster definitions and show total employment; the next four use the industry-‐based cluster definitions and show total number of firms; the final four use the occupation-‐based cluster definitions and show total employment. Each table shows results for the entire US, the Pittsburgh region, and the nineteen benchmark regions. Within each set of four tables are:

1. the total (employees or firms as appropriate). 2. the location quotients (LQ). By definition, at the national level, all LQs are 1.0. 3. the percentage change in the past year for the number reported. For industry data, this is 2010-‐2011.

For the occupational data, this is 2011-‐2012. 4. the average of the year-‐to-‐year percentage changes for the past five years. For industry data, this is

2005-‐2011. For the occupational data, this is 2006-‐2012. Industry Clusters – Employment Employment (2011) Creative

Industry Support

DATA Design Entertainment

Fine Arts

Media/ Communications

SW/HW Total

US National 14,060,384 2,195,200 4,064,307 2,729,795 478,371 1,890,183 2,640,507 113,425,965

Pittsburgh Pennsylvania 161,390 14,148 50,575 21,971 4,349 13,564 16,167 1,058,939

Austin-‐San Marcos Texas 74,495 14,730 32,793 15,933 2,664 12,151 31,490 653,617

Baltimore Maryland 138,603 15,833 50,839 25,761 3,983 13,357 38,124 1,062,322

Birmingham Alabama 37,769 9,612 8,889 6,623 1,176 6,507 4,546 432,202

Boulder-‐Longmont Colorado 14,925 3,169 8,095 4,443 563 3,977 11,494 131,872

Cincinnati Ohio-‐Kentucky-‐Indiana

93,045 17,099 27,300 18,039 2,938 21,240 16,085 875,217

Cleveland-‐Lorain-‐Elyria Ohio 113,721 13,622 45,811 14,694 3,405 11,610 15,799 889,949

Denver Colorado 117,910 47,264 42,650 30,050 4,369 16,227 39,007 1,049,564

Detroit Michigan 217,850 22,003 103,808 30,719 5,300 23,983 33,989 1,554,363

Kansas City Missouri-‐Kansas 75,370 29,533 31,655 15,415 3,118 19,168 20,883 859,449

Los Angeles-‐Long Beach California

690,061 121,190 215,942 237,560 33,308 110,807 119,431 4,949,519

Louisville Kentucky-‐Indiana 47,902 7,946 14,453 8,523 1,557 12,957 5,206 517,444

Memphis Tennessee-‐Arkansas-‐Mississippi

72,463 3,942 6,532 8,316 1,418 4,949 10,066 509,410

New Orleans Louisiana 43,155 4,670 10,821 10,516 1,511 3,871 4,386 453,437

Orlando Florida 82,519 16,553 26,927 54,701 3,855 12,209 18,065 881,329

Philadelphia Pennsylvania-‐New Jersey

330,911 50,287 79,057 53,424 10,212 41,526 66,304 2,449,574

Portland-‐Vancouver Oregon Washington

99,914 16,303 42,012 20,191 4,183 13,993 26,707 863,546

Salt Lake City-‐Ogden Utah 51,161 10,597 23,479 18,585 2,390 8,518 17,282 530,264

San Francisco California 202,403 45,050 80,610 52,491 11,752 35,362 97,596 1,758,043

San Jose California 148,102 36,182 61,166 17,879 2,838 7,025 110,306 874,495

St. Louis Missouri-‐Illinois 153,098 23,968 37,058 29,807 6,791 20,412 28,882 1,174,986


Employment LQ (2011) Creative

Industry Support


Fine Arts


SW/HW

US National 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Pittsburgh Pennsylvania 1.229 0.690 1.333 0.862 0.974 0.769 0.656

Austin-‐San Marcos Texas 0.919 1.164 1.400 1.013 0.966 1.116 2.070

Baltimore Maryland 1.053 0.770 1.336 1.008 0.889 0.755 1.542

Birmingham Alabama 0.705 1.149 0.574 0.637 0.645 0.903 0.452

Boulder-‐Longmont Colorado 0.913 1.242 1.713 1.400 1.013 1.809 3.744

Cincinnati Ohio-‐Kentucky-‐Indiana 0.858 1.009 0.870 0.856 0.796 1.456 0.789

Cleveland-‐Lorain-‐Elyria Ohio 1.031 0.791 1.437 0.686 0.907 0.783 0.763

Denver Colorado 0.906 2.327 1.134 1.190 0.987 0.928 1.596

Detroit Michigan 1.131 0.731 1.864 0.821 0.809 0.926 0.939

Kansas City Missouri-‐Kansas 0.707 1.776 1.028 0.745 0.860 1.338 1.044

Los Angeles-‐Long Beach California 1.125 1.265 1.218 1.994 1.596 1.343 1.037

Louisville Kentucky-‐Indiana 0.747 0.793 0.780 0.684 0.714 1.503 0.432

Memphis Tennessee-‐Arkansas-‐Mississippi 1.148 0.400 0.358 0.678 0.660 0.583 0.849

New Orleans Louisiana 0.768 0.532 0.666 0.964 0.790 0.512 0.416

Orlando Florida 0.755 0.970 0.853 2.579 1.037 0.831 0.880

Philadelphia Pennsylvania-‐New Jersey 1.090 1.061 0.901 0.906 0.988 1.017 1.163

Portland-‐Vancouver Oregon Washington 0.933 0.976 1.358 0.972 1.149 0.972 1.329

Salt Lake City-‐Ogden Utah 0.778 1.033 1.236 1.456 1.069 0.964 1.400

San Francisco California 0.929 1.324 1.280 1.241 1.585 1.207 2.385

San Jose California 1.366 2.138 1.952 0.850 0.770 0.482 5.418

St. Louis Missouri-‐Illinois 1.051 1.054 0.880 1.054 1.370 1.042 1.056


Employment Growth (10-‐11) Creative Industry Support


Fine Arts


SW/HW Total

US National 4.17% 2.47% 2.19% 0.43% -‐0.34% -‐2.40% -‐0.39% 1.30%

Pittsburgh Pennsylvania 8.93% 9.33% 5.69% 5.61% 0.88% 0.06% -‐0.27% 2.72%

Austin-‐San Marcos Texas 7.02% -‐6.11% 2.74% 0.11% 3.62% 13.04% -‐8.08% 2.04%

Baltimore Maryland 2.77% -‐7.44% -‐1.04% 4.86% -‐8.77% -‐8.17% 2.26% 0.26%

Birmingham Alabama 7.48% -‐4.88% -‐6.06% -‐7.42% -‐6.14% -‐30.15% -‐6.81% -‐0.47%

Boulder-‐Longmont Colorado 10.08% -‐5.49% 3.87% -‐2.61% -‐2.09% 14.67% -‐27.68% -‐1.04%


0.46% 26.71% 1.16% -‐4.75% -‐2.39% 5.82% -‐5.27% 0.08%

Cleveland-‐Lorain-‐Elyria Ohio 12.98% 3.12% 6.28% -‐3.84% -‐1.31% -‐6.37% 4.42% 2.27%

Denver Colorado 4.89% 7.87% 7.35% 4.62% 0.30% -‐4.68% -‐3.10% 1.10%

Detroit Michigan 10.96% 3.18% 12.21% 2.52% 1.42% 2.44% -‐4.88% 3.56%

Kansas City Missouri-‐Kansas 1.26% 4.76% -‐8.21% -‐2.33% -‐2.84% -‐4.59% 3.22% -‐0.14%


11.60% -‐0.85% 1.18% -‐1.14% -‐1.18% -‐3.63% -‐1.11% 2.00%

Louisville Kentucky-‐Indiana 7.48% 12.12% 5.13% -‐4.18% -‐0.38% 0.28% -‐26.75% 0.47%


3.86% 1.15% -‐13.25% -‐0.49% -‐5.46% -‐5.82% -‐6.74% 0.05%

New Orleans Louisiana 4.24% -‐1.29% 0.78% 5.17% -‐7.41% -‐2.64% -‐0.36% 1.65%

Orlando Florida 11.30% -‐1.41% -‐4.85% 18.64% -‐36.98% 3.75% -‐26.17% 2.98%


7.08% 15.42% -‐0.92% 3.03% 0.15% -‐4.88% -‐3.96% 1.16%


0.74% 6.27% -‐26.02% 4.93% 4.84% 3.20% -‐0.50% -‐0.83%

Salt Lake City-‐Ogden Utah 4.61% -‐16.76% -‐0.13% 4.28% -‐1.48% -‐9.13% 6.34% 0.78%

San Francisco California -‐8.92% 4.31% 1.45% -‐0.01% 7.73% -‐1.89% 0.95% -‐0.55%

San Jose California 8.99% 1.51% -‐3.03% 3.84% -‐5.49% 6.34% -‐6.67% 2.04%

St. Louis Missouri-‐Illinois 0.21% 0.10% 3.96% -‐2.23% 1.22% 2.01% 1.10% 0.46%


Employment Growth (05-‐11 annual average)



Fine Arts Media/ Communications

SW/HW Total

US National 0.57% -‐0.83% -‐1.80% 0.45% -‐1.23% -‐3.31% 1.15% -‐0.38%

Pittsburgh Pennsylvania 7.92% 0.75% 3.30% 3.87% 2.53% 0.81% 5.19% 0.27%

Austin-‐San Marcos Texas 7.47% 7.69% 2.57% 7.92% 3.59% 8.16% -‐0.43% 2.00%

Baltimore Maryland 4.34% 3.45% 5.10% 2.92% 9.95% -‐1.97% 5.41% -‐0.37%

Birmingham Alabama 5.97% 0.63% 1.58% 5.41% 10.78% -‐2.43% 0.89% -‐1.05%

Boulder-‐Longmont Colorado 1.39% -‐0.83% -‐2.42% 6.46% -‐0.91% 4.20% -‐3.12% -‐0.20%

Cincinnati Ohio-‐Kentucky-‐Indiana 4.12% 2.51% -‐2.00% 3.30% 1.18% 0.06% 2.81% -‐0.41%

Cleveland-‐Lorain-‐Elyria Ohio 2.42% 1.93% 0.18% 0.59% 0.53% -‐4.18% 2.45% -‐1.22%

Denver Colorado 1.35% 6.87% 4.87% 6.75% 6.54% -‐0.30% 5.55% 0.03%

Detroit Michigan 1.42% -‐1.72% -‐2.97% -‐0.06% 4.64% -‐2.79% 10.97% -‐2.40%

Kansas City Missouri-‐Kansas 1.67% 0.04% 1.40% -‐0.57% 0.84% -‐1.72% 6.34% -‐0.60%

Los Angeles-‐Long Beach California 0.47% -‐0.23% -‐2.95% 0.22% -‐1.16% -‐2.18% -‐0.07% -‐0.96%

Louisville Kentucky-‐Indiana 3.67% 1.14% 1.14% 0.90% -‐0.76% 1.22% 6.95% -‐0.48%


5.25% -‐1.70% -‐6.92% 1.54% -‐3.81% -‐7.63% 8.25% -‐0.72%

New Orleans Louisiana 3.16% -‐0.45% 6.39% -‐1.78% 6.40% 0.61% 3.67% -‐1.65%

Orlando Florida 3.77% 3.51% -‐0.93% 5.31% -‐11.03% 4.21% 5.76% -‐0.30%


3.87% 2.89% 1.90% 3.25% -‐3.18% -‐3.34% 1.47% -‐0.45%


1.91% 4.62% 3.93% 8.17% 5.81% 3.77% 6.40% -‐0.33%

Salt Lake City-‐Ogden Utah 5.98% -‐2.22% 5.25% 10.02% -‐1.02% 2.01% 5.84% 0.82%

San Francisco California -‐2.96% 3.92% -‐0.01% 3.72% 3.19% -‐0.04% -‐0.01% -‐1.32%

San Jose California 3.47% 1.87% -‐2.29% 3.44% 1.47% 2.61% 6.47% 0.28%

St. Louis Missouri-‐Illinois -‐0.22% 1.42% 0.37% 5.00% 4.45% -‐3.27% 3.37% -‐1.01%


Industry Clusters – Establishments Establishments (2011) Creative

Industry Support


Fine Arts


SW/HW Total

US National 512,485 81,858 286,850 173,846 76,757 118,676 178,558 7,354,043

Pittsburgh Pennsylvania 4,432 649 2,323 1,307 491 771 1,245 59,052

Austin-‐San Marcos Texas 3,413 610 2,287 1,044 426 886 1,829 41,924

Baltimore Maryland 4,772 710 2,825 1,460 528 999 2,525 64,425

Birmingham Alabama 1,616 299 857 454 183 401 484 25,246

Boulder-‐Longmont Colorado 1,075 142 1,031 377 164 280 695 11,419


3,325 440 1,856 1,042 370 939 1,098 45,607

Cleveland-‐Lorain-‐Elyria Ohio 3,844 499 2,830 1,045 407 885 1,199 51,600

Denver Colorado 6,289 1,079 4,351 1,659 726 1,500 2,985 73,419

Detroit Michigan 6,942 887 5,231 1,901 695 1,389 2,401 96,919

Kansas City Missouri-‐Kansas 3,691 657 1,906 997 461 987 1,298 49,878


24,504 3,343 15,272 12,851 11,507 7,327 8,726 331,734

Louisville Kentucky-‐Indiana 2,011 302 1,011 644 244 532 559 29,228


1,916 255 557 438 145 354 431 25,131

New Orleans Louisiana 2,180 270 962 608 287 366 462 28,991

Orlando Florida 3,806 623 2,639 1,343 595 876 1,477 54,922


11,032 1,649 5,936 3,054 1,217 2,380 4,354 143,604


4,623 715 2,783 1,481 618 1,201 1,789 62,085

Salt Lake City-‐Ogden Utah 2,450 417 1,704 778 333 624 948 31,390

San Francisco California 10,539 1,718 6,038 2,902 1,243 2,560 5,252 117,920

San Jose California 3,707 886 3,006 918 330 711 3,643 45,462

St. Louis Missouri-‐Illinois 4,735 828 2,241 1,505 610 1,215 1,575 69,374


Establishment LQ (2011) Creative Industry Support


Fine Arts


SW/HW

US National 1.000 1.000 1.000 1.000 1.000 1.000 1.000








Denver Colorado 1.229 1.320 1.519 0.956 0.947 1.266 1.674







Orlando Florida 0.994 1.019 1.232 1.034 1.038 0.988 1.108








Establishment Growth (10-‐11) Creative Industry Support


Fine Arts


SW/HW Total

US National -‐1.01% -‐0.62% 0.42% -‐0.07% 0.05% -‐2.38% 1.27% -‐0.58%

Pittsburgh Pennsylvania -‐1.84% 2.37% -‐0.34% -‐2.10% 0.41% -‐1.41% 1.47% -‐0.32%

Austin-‐San Marcos Texas 1.13% 3.04% 1.83% 3.57% 3.65% 0.45% 4.75% 1.72%

Baltimore Maryland -‐2.25% -‐3.53% -‐0.18% -‐2.86% 1.93% -‐5.75% 4.47% -‐1.14%

Birmingham Alabama -‐1.40% -‐1.32% -‐2.61% -‐4.62% -‐7.58% -‐4.52% 0.00% -‐1.71%

Boulder-‐Longmont Colorado -‐1.65% -‐6.58% 0.98% -‐1.31% -‐1.80% 0.00% -‐1.56% -‐0.21%

Cincinnati Ohio-‐Kentucky-‐Indiana -‐2.49% -‐3.08% 0.38% -‐2.62% -‐2.12% -‐4.77% 2.52% -‐1.16%

Cleveland-‐Lorain-‐Elyria Ohio -‐2.90% -‐5.49% -‐0.67% 0.00% -‐2.86% -‐2.21% -‐4.84% -‐1.05%

Denver Colorado -‐0.47% 1.31% 0.25% 0.97% 0.83% -‐3.23% 0.78% -‐0.33%

Detroit Michigan -‐0.47% -‐1.88% 0.91% -‐1.04% -‐3.20% -‐0.64% 1.44% -‐0.30%

Kansas City Missouri-‐Kansas -‐1.10% -‐0.61% 2.47% 1.01% -‐1.28% -‐1.79% 0.08% -‐0.50%

Los Angeles-‐Long Beach California -‐0.49% 1.36% 2.00% 2.31% 2.03% -‐1.24% 0.30% 0.23%

Louisville Kentucky-‐Indiana -‐2.38% 5.23% -‐0.98% -‐1.98% 2.95% -‐4.14% -‐3.12% -‐2.11%


-‐4.01% -‐1.54% -‐2.11% -‐0.23% -‐1.36% -‐4.58% -‐7.71% -‐2.41%

New Orleans Louisiana -‐2.20% -‐6.25% 3.44% -‐2.09% -‐4.01% -‐1.61% -‐1.07% -‐0.36%

Orlando Florida -‐0.47% -‐1.27% 1.38% 2.44% 0.51% -‐1.02% 0.34% -‐0.28%


-‐1.93% 2.42% -‐1.26% -‐2.46% -‐2.64% -‐3.13% -‐1.65% -‐0.78%


-‐1.64% -‐1.11% 0.58% -‐1.92% 3.00% -‐0.25% 1.30% -‐0.61%

Salt Lake City-‐Ogden Utah -‐1.29% 2.21% 2.59% 4.99% 0.60% -‐3.26% -‐2.17% -‐0.50%

San Francisco California -‐0.96% 4.44% 0.97% 0.48% -‐3.49% -‐2.66% 3.73% 0.17%

San Jose California 0.11% 4.48% 0.80% 1.55% 2.17% 5.18% 4.62% 0.95%

St. Louis Missouri-‐Illinois -‐3.43% -‐4.17% -‐0.71% -‐1.57% -‐2.71% -‐3.34% -‐2.42% -‐1.40%


Establishment Growth (05-‐11 annual average)



Fine Arts


SW/HW Total

US National 0.33% -‐0.75% -‐0.15% -‐0.09% -‐0.03% -‐1.60% 1.33% -‐0.32%

Pittsburgh Pennsylvania -‐0.25% -‐0.07% -‐0.42% -‐1.24% -‐0.45% -‐2.29% 1.40% -‐0.65%

Austin-‐San Marcos Texas 2.86% 0.76% 3.40% 3.81% 3.30% 2.53% 4.74% 2.65%

Baltimore Maryland -‐0.11% -‐1.42% -‐0.27% -‐1.82% 0.48% -‐2.85% 3.77% -‐0.65%

Birmingham Alabama -‐0.80% -‐0.95% -‐0.06% -‐2.00% -‐1.50% -‐0.60% -‐0.06% -‐0.71%

Boulder-‐Longmont Colorado 1.32% -‐2.18% 2.45% 0.46% 1.81% 0.68% 1.51% 0.40%

Cincinnati Ohio-‐Kentucky-‐Indiana 0.99% -‐1.26% -‐0.84% -‐0.65% -‐1.49% -‐1.42% 0.32% -‐0.92%

Cleveland-‐Lorain-‐Elyria Ohio -‐0.69% -‐1.88% -‐2.07% -‐1.58% -‐1.63% -‐2.97% -‐1.01% -‐1.50%

Denver Colorado 0.81% -‐0.60% 1.15% 0.29% 0.17% -‐1.81% 0.85% -‐0.02%

Detroit Michigan -‐1.38% -‐4.75% -‐1.96% -‐1.72% -‐1.72% -‐2.21% 1.07% -‐1.39%

Kansas City Missouri-‐Kansas -‐0.33% -‐2.12% -‐1.15% -‐1.14% -‐1.39% -‐2.35% 1.22% -‐0.86%

Los Angeles-‐Long Beach California 0.45% -‐0.17% -‐0.46% 1.13% 2.35% -‐0.99% 0.23% -‐0.04%

Louisville Kentucky-‐Indiana -‐0.18% -‐2.18% 0.28% -‐1.32% 0.05% -‐2.27% 1.32% -‐0.56%


1.13% -‐1.41% -‐2.73% -‐0.86% -‐1.68% -‐3.71% -‐0.25% -‐0.73%

New Orleans Louisiana -‐0.06% -‐2.94% 0.65% -‐1.15% -‐1.79% -‐2.91% -‐0.63% -‐1.10%

Orlando Florida 0.56% -‐2.56% 0.70% 0.98% 0.24% -‐1.36% 2.02% -‐0.29%


-‐1.17% -‐0.23% -‐1.51% -‐0.92% -‐1.63% -‐2.36% 0.59% -‐0.55%


1.55% 0.93% 0.99% 1.29% 1.46% -‐0.57% 1.23% 0.29%

Salt Lake City-‐Ogden Utah 0.53% -‐0.26% 2.13% 0.82% 1.28% -‐0.21% 2.63% 0.32%

San Francisco California 0.97% 1.58% -‐0.15% 0.33% -‐1.62% -‐0.89% 0.33% -‐0.22%

San Jose California 0.68% 1.69% -‐0.21% 1.25% -‐0.72% -‐1.52% 0.60% -‐0.04%

St. Louis Missouri-‐Illinois -‐0.11% 0.14% -‐1.88% -‐0.58% -‐1.07% -‐2.20% 0.33% -‐0.60%


Occupational Clusters Employment (2012) Creative

Industry Support


Fine Arts


SW/HW Total

US National 8,663,710 1,523,320 2,945,800 4,743,700 476,170 2,676,070 3,966,190 130,287,780

Pittsburgh Pennsylvania 75,790 11,910 24,040 40,850 2,390 21,500 34,790 1,105,820

Austin-‐San Marcos Texas 61,340 13,790 20,920 24,050 2,040 17,940 56,530 790,570

Baltimore Maryland 102,720 20,120 28,770 43,980 3,160 23,070 50,950 1,236,510

Birmingham Alabama 27,340 7,020 8,300 20,130 700 7,960 10,110 466,700

Boulder-‐Longmont Colorado

13,360 2,930 5,580 5,220 390 4,460 12,500 147,840


55,220 9,560 20,560 31,410 2,490 24,380 31,920 957,580

Cleveland-‐Lorain-‐Elyria Ohio

61,540 10,260 20,310 28,890 2,850 23,370 33,730 979,250

Denver Colorado 90,120 18,320 31,410 43,220 3,380 28,180 56,630 1,213,540

Detroit Michigan 82,730 16,800 58,130 55,960 3,640 31,620 61,720 1,699,600

Kansas City Missouri-‐Kansas 56,530 15,670 18,580 33,500 2,960 22,080 36,140 957,270


365,330 66,380 157,210 182,740 78,940 156,990 172,250 5,241,870

Louisville Kentucky-‐Indiana 31,390 5,700 9,180 16,320 960 10,560 13,290 574,980


27,280 5,560 8,040 20,380 680 9,410 12,430 558,200

New Orleans Louisiana 31,590 4,120 10,790 24,480 4,270 5,910 7,940 490,780

Orlando Florida 54,700 11,920 18,120 49,880 5,820 22,900 27,200 989,380


188,810 32,420 50,540 98,170 7,020 58,450 88,030 2,568,020


67,210 13,020 29,160 30,680 4,720 25,510 41,510 978,580

Salt Lake City-‐Ogden Utah 36,720 7,500 14,260 17,350 1,730 18,040 26,070 596,330

San Francisco California 154,250 33,230 56,200 66,060 9,960 63,300 112,920 1,936,000

San Jose California 56,260 19,640 46,960 24,530 1,660 28,580 122,360 875,190

St. Louis Missouri-‐Illinois 76,520 16,560 24,830 49,600 3,470 26,770 45,050 1,258,350


Employment LQ (2012) Creative Industry Support


Fine Arts


SW/HW

US National 1.00 1.00 1.00 1.00 1.00 1.00 1.00








Denver Colorado 1.12 1.29 1.14 0.98 0.76 1.13 1.53







Orlando Florida 0.83 1.03 0.81 1.38 1.61 1.13 0.90








Employment Growth (11-‐12) Creative Industry Support


Fine Arts Media/ Communications

SW/HW Total

US National -‐0.1% 45.8% 1.4% 0.7% 2.7% 2.5% -‐7.3% 1.6%

Pittsburgh Pennsylvania 3.8% 24.3% -‐9.5% -‐2.6% -‐6.6% 0.2% 0.0% 1.3%

Austin-‐San Marcos Texas 5.8% 91.8% 14.4% -‐6.3% -‐20.0% -‐3.7% -‐6.5% 4.5%

Baltimore Maryland 1.7% 68.2% -‐2.9% -‐1.0% 6.8% 7.1% -‐4.9% 1.3%

Birmingham Alabama -‐2.9% 29.5% 2.7% 1.9% -‐14.6% 8.6% -‐4.4% 2.0%

Boulder-‐Longmont Colorado 3.6% 92.8% 26.5% 1.4% 34.5% 5.7% 0.0% 6.7%

Cincinnati Ohio-‐Kentucky-‐Indiana -‐3.8% 46.2% 25.8% 3.4% 8.7% 14.0% -‐11.1% 1.5%

Cleveland-‐Lorain-‐Elyria Ohio -‐2.4% 26.8% 7.7% 12.2% -‐12.3% 13.0% 4.6% 2.2%

Denver Colorado 7.7% 66.2% 3.0% 6.7% 28.0% 3.5% -‐5.7% 4.1%

Detroit Michigan 4.0% 62.0% -‐1.7% 1.7% 6.7% 2.2% 3.2% 4.4%

Kansas City Missouri-‐Kansas 1.4% 74.1% -‐3.9% -‐1.3% -‐1.3% 2.3% -‐7.8% 1.3%


-‐1.3% 40.2% 2.2% -‐0.7% 10.2% 3.8% -‐7.9% 1.9%

Louisville Kentucky-‐Indiana 1.4% 36.0% -‐4.2% 4.1% -‐1.0% 1.5% -‐18.2% 1.2%


2.7% 40.8% 9.8% -‐3.2% -‐20.0% 1.3% 0.6% -‐0.2%

New Orleans Louisiana -‐4.5% 30.8% -‐1.1% 10.7% 121.2% 3.9% -‐6.1% -‐0.3%

Orlando Florida 2.5% 63.3% 6.8% 7.5% -‐0.5% 10.0% -‐5.8% 3.5%


2.9% 58.9% 5.6% 3.8% 14.5% 2.5% -‐8.7% 0.3%


-‐0.6% 60.0% 3.6% 3.9% 23.2% 3.4% -‐8.5% 1.7%

Salt Lake City-‐Ogden Utah -‐5.8% 97.4% 6.1% 2.6% 8.8% 10.8% -‐2.6% 3.0%

San Francisco California 8.9% 68.4% 6.6% -‐3.7% -‐0.7% 7.2% 1.7% 6.3%

San Jose California 0.7% 72.9% 0.8% 3.0% -‐4.0% 7.7% -‐2.9% 2.5%

St. Louis Missouri-‐Illinois 1.6% 58.0% 1.6% 5.0% 9.1% -‐2.3% -‐11.0% 0.6%


Employment Growth (06-‐12 annual average)



Fine Arts


SW/HW Total

US National -‐0.8% 5.0% -‐1.5% 0.0% 0.7% -‐0.6% 0.8% -‐0.3%

Pittsburgh Pennsylvania 1.7% 2.1% -‐0.2% 0.1% 0.1% 0.1% 3.3% -‐7.9%

Austin-‐San Marcos Texas 3.3% 13.8% 0.7% 2.1% 16.3% 2.8% 4.6% -‐5.9%

Baltimore Maryland -‐0.3% 7.7% 1.3% 0.3% 8.6% -‐0.6% 5.5% -‐8.2%

Birmingham Alabama -‐0.8% 6.4% -‐2.0% 4.3% -‐3.2% 3.4% -‐2.1% -‐8.5%

Boulder-‐Longmont Colorado 5.8% 17.5% 0.9% 1.1% 71.2% 4.6% 2.3% -‐6.6%

Cincinnati Ohio-‐Kentucky-‐Indiana -‐3.0% 6.2% 2.3% 0.4% 0.3% 1.1% 2.8% -‐8.8%

Cleveland-‐Lorain-‐Elyria Ohio -‐2.2% 8.3% -‐1.1% -‐2.1% 16.5% 3.2% 4.2% -‐8.9%

Denver Colorado 3.4% 6.3% 0.5% 0.8% 17.1% -‐0.8% 1.5% -‐7.4%

Detroit Michigan -‐3.4% 4.8% -‐1.3% -‐2.4% -‐0.1% -‐2.4% -‐1.3% -‐11.2%

Kansas City Missouri-‐Kansas -‐0.4% 10.3% -‐1.0% -‐0.5% 0.4% -‐0.6% 2.0% -‐8.1%

Los Angeles-‐Long Beach California -‐2.1% 7.9% -‐3.0% -‐1.3% 6.6% -‐0.1% 1.2% -‐10.8%

Louisville Kentucky-‐Indiana -‐0.4% 3.4% 1.9% -‐0.4% 11.0% -‐2.4% 1.0% -‐7.9%


-‐1.3% 6.1% 0.1% -‐3.1% 11.0% 0.2% 1.4% -‐9.0%

New Orleans Louisiana 2.1% 4.6% 1.9% 6.2% 65.5% -‐1.1% 1.9% -‐6.0%

Orlando Florida -‐1.8% 4.8% 0.2% 2.0% 6.7% -‐0.4% 1.5% -‐7.9%


-‐1.3% 10.7% -‐3.1% 0.8% 6.5% -‐0.8% -‐1.6% -‐10.4%


1.6% 7.3% 5.5% 2.4% 12.4% 5.7% 2.2% -‐7.7%

Salt Lake City-‐Ogden Utah 1.1% 13.3% 0.7% -‐3.1% 1.9% 2.2% 2.0% -‐7.2%

San Francisco California 1.2% 8.1% -‐0.6% -‐0.1% 6.0% 2.1% 3.2% -‐10.0%

San Jose California 1.0% 11.9% -‐2.0% 0.1% 4.0% 2.7% 2.6% -‐7.9%

St. Louis Missouri-‐Illinois -‐0.9% 3.7% 1.8% 0.9% 3.0% -‐0.8% 0.8% -‐8.3%


The Future of Pittsburgh’s Creative Sector The BLS provides estimates of employment growth by occupation for the 2010 to 2020 period. Using the occupation-‐based cluster and subcluster definitions, the BLS estimates can be applied to the Pittsburgh creative sector clusters to estimate job growth. These estimates provide an indication of the components of growth of Pittsburgh’s creative sector through 2022. Note that the overall employment growth for the region based solely on occupation mix shows growth of 14.3% over the ten years. Employment growth of occupations outside the creative sector will be 14.6% and within the creative sector will be 12.7%. However, several subsectors have growth rates well above the regional average. And, as the next table shows, many of the occupations in these clusters have wages well above the regional average. Many of the high-‐growth jobs are lower paying service sector jobs; job growth is not always an indicator of increasing regional prosperity. The estimated growth is for the entire ten-‐year period and is not shown on an annual basis. These estimates come with a collection of caveats. First, these estimates only reflect the occupation-‐specific growth, any variation from regional impacts on overall growth rates are not included. Second, the BLS estimates are for all occupations across the entire country over the ten-‐year period so local Pittsburgh results could vary as specific occupations may not grow at the national average. Third, the BLS estimates cover 2010 to 2020 but the ten-‐year growth rate has been applied to 2012 to 2022. Finally, these results are based on the specific employment mix and structure as it existed in Pittsburgh in 2012. The projections assume that the overall employment structure would only change as a result of specific, individual occupation growth and do not take into account structural changes in the employment distribution across the region from other factors.

Pittsburgh, PA EMP 2012

EMP 2022 Growth

Employment outside report 928,250 1,063,697 14.6% Creative Industry Support 42,090 48,211 14.5%

Post-‐Sec 12,620 15,020 19.0% R&D 10,840 12,178 12.3% Services 18,630 21,558 15.7%

DATA 11,910 13,452 12.9% Internet 7,010 8,960 27.8% R&D 1,040 1,185 13.9% Sensor 410 458 11.7% Telecomm 3,450 3,561 3.2%

Design 24,040 25,692 6.9% Arch/Eng 1,450 1,575 8.6% Architecture 620 764 23.2% Engineering 13,980 15,111 8.1% Industrial Design 330 365 10.5% Other Design 610 638 4.7% Textiles 730 609 -‐16.5%


Pittsburgh, PA EMP 2012

EMP 2022 Growth

Urban 6,320 7,329 16.0% Entertainment 40,850 45,073 10.3%

Film & Media 1,100 1,184 7.7% Recreation 39,500 43,634 10.5% Toys 250 254 1.6%

Fine Arts 2,390 2,598 8.7% Museums 230 264 14.7% Music 690 760 10.2% Performing Arts 1,060 1,157 9.2% Visual Arts 410 429 4.5%

Media/Communications 21,500 24,157 12.4% Advertising 4,220 4,767 13.0% Broadcasting 550 581 5.7% Graphic Design 1,910 2,160 13.1% Marketing 8,200 9,955 21.4% Other 40 45 11.4% Printing 2,310 2,203 -‐4.6% Public Relations 2,660 3,228 21.3% Publishing 1,610 1,675 4.0%

SW/HW 34,790 41,388 19.0% Engineering 1,280 1,360 6.3% Health Devices 2,670 3,306 23.8% Manufacturing 2,340 2,206 -‐5.7% Retail 2,530 2,944 16.4% Software 25,970 31,658 21.9%

Grand Total 1,105,820 1,263,854 14.3% The next table shows the 2012 total employment and total and average wages for each of the Creative Sector clusters and subclusters. Following that is a table that shows the same for all of the benchmark regions. Employment totals of zero do not necessarily mean that the particular region has no one in the region working in that cluster. A zero indicates that the region did not have enough people employed to be able to report any information without encountering disclosure issues.

Pittsburgh Creative Sector Wages

Clusters Total Employment Total Wages $

Average Wage

Pittsburgh, PA 1,105,820 48,511,332,000 43,869 Creative Industry Support 42,090 2,350,760,400 55,851 Post-‐Sec 12,620 981,370,100 77,763 R&D 10,840 585,270,400 53,992


Clusters Total Employment Total Wages $

Average Wage

Services 18,630 784,119,900 42,089 DATA 11,910 725,343,100 60,902 Internet 7,010 495,682,100 70,711 R&D 1,040 65,755,100 63,226 Sensor 410 13,644,800 33,280 Telecomm 3,450 150,261,100 43,554

Design 24,040 1,759,702,800 73,199 Arch/Eng 1,450 201,419,500 138,910 Architecture 620 46,278,800 74,643 Engineering 13,980 1,043,131,300 74,616 Industrial Design 330 18,077,400 54,780 Other Design 610 19,645,700 32,206 Textiles 730 17,434,600 23,883 Urban 6,320 413,715,500 65,461

Entertainment 40,850 850,945,700 20,831 Film & Media 1,100 46,817,800 42,562 Recreation 39,500 795,060,400 20,128 Toys 250 9,067,500 36,270

Fine Arts 2,390 128,268,400 53,669 Museums 230 8,533,300 37,101 Music 690 32,878,500 47,650 Performing Arts 1,060 63,390,900 59,803 Visual Arts 410 23,465,700 57,233

Media/Communications 21,500 1,323,965,600 61,580 Advertising 4,220 386,382,600 91,560 Broadcasting 550 23,165,700 42,119 Graphic Design 1,910 76,363,600 39,981 Marketing 8,200 506,276,100 61,741 Other 40 1,739,200 43,480 Printing 2,310 76,697,900 33,203 Public Relations 2,660 173,221,400 65,121 Publishing 1,610 80,119,100 49,763

SW/HW 34,790 2,499,111,200 71,834 Engineering 1,280 107,200,000 83,750 Health Devices 2,670 150,854,100 56,500 Manufacturing 2,340 78,974,600 33,750 Retail 2,530 224,841,100 88,870 Software 25,970 1,937,241,400 74,595


Benchmark Comparison Wages

Benchmark Metro/Clusters Total Employment Total Wages $

Average Wage

Austin-‐Round Rock, TX 790,570 36,595,707,100 46,290 Creative Industry Support 29,660 1,643,318,900 55,405 Post-‐Sec 8,850 491,795,000 55,570 R&D 7,340 441,018,500 60,084 Services 13,470 710,505,400 52,747

DATA 13,790 933,085,000 67,664 Internet 9,160 702,203,500 76,660 R&D 760 61,588,800 81,038 Sensor 160 4,872,000 30,450 Telecomm 3,710 164,420,700 44,318

Design 20,920 1,506,797,900 72,027 Arch/Eng

0

Architecture 660 47,381,400 71,790 Engineering 12,540 990,639,600 78,998 Industrial Design 120 7,363,200 61,360 Other Design 510 19,430,700 38,099 Textiles 320 6,683,200 20,885 Urban 6,770 435,299,800 64,298

Entertainment 24,050 598,308,500 24,878 Film & Media 1,070 48,050,300 44,907 Recreation 22,980 550,258,200 23,945

Fine Arts 2,040 118,806,500 58,238 Music 450 22,887,000 50,860 Performing Arts 1,080 68,940,900 63,834 Visual Arts 510 26,978,600 52,899


SW/HW 56,530 4,587,347,000 81,149 Engineering 4,630 451,081,800 97,426 Health Devices 680 39,788,600 58,513 Manufacturing 6,730 201,140,600 29,887 Retail 6,880 570,627,200 82,940 Software 37,610 3,324,708,800 88,400



Average Wage

Baltimore-‐Towson, MD 1,236,510 63,236,192,600 51,141 Creative Industry Support 56,950 3,696,733,100 64,912 Post-‐Sec 17,900 1,371,838,200 76,639 R&D 15,080 1,101,868,000 73,068 Services 23,970 1,223,026,900 51,023

DATA 20,120 1,522,316,600 75,662 Communications 30 947,100 31,570 Internet 12,690 1,083,865,900 85,411 R&D 2,620 237,427,700 90,621 Sensor 320 10,828,800 33,840 Telecomm 4,460 189,247,100 42,432

Design 28,770 2,278,008,600 79,180 Arch/Eng 2,310 302,656,200 131,020 Architecture 1,210 94,924,500 78,450 Engineering 16,210 1,358,512,200 83,807 Industrial Design 220 11,666,600 53,030 Other Design 1,080 40,706,700 37,691 Textiles 2,120 55,697,300 26,272 Urban 5,620 413,845,100 73,638

Entertainment 43,980 1,074,053,400 24,421 Film & Media 980 46,371,700 47,318 Recreation 42,930 1,024,380,500 23,862 Toys 70 3,301,200 47,160



SW/HW 50,950 4,647,629,500 91,219 Engineering 3,600 367,610,400 102,114 Health Devices 3,310 216,884,300 65,524 Manufacturing 2,000 71,039,000 35,520



Average Wage

Retail 2,530 234,303,300 92,610 Software 39,510 3,757,792,500 95,110

Birmingham-‐Hoover, AL 466,700 19,450,154,700 41,676 Creative Industry Support 11,030 519,731,000 47,120 Post-‐Sec 2,890 175,520,300 60,734 R&D 1,900 111,667,100 58,772 Services 6,240 232,543,600 37,267


Design 8,300 537,004,300 64,699 Arch/Eng 730 80,643,100 110,470 Architecture 410 26,777,100 65,310 Engineering 4,010 283,644,600 70,734 Other Design 390 12,124,500 31,088 Textiles 810 18,644,600 23,018 Urban 1,950 115,170,400 59,062

Entertainment 20,130 394,505,400 19,598 Film & Media 270 12,165,600 45,058 Recreation 19,860 382,339,800 19,252

Fine Arts 700 39,219,100 56,027 Music 70 3,659,600 52,280 Performing Arts 430 24,320,100 56,558 Visual Arts 200 11,239,400 56,197

Media/Communications 7,960 419,462,200 52,696 Advertising 2,920 179,766,300 61,564 Broadcasting 340 10,560,400 31,060 Graphic Design 640 27,203,200 42,505 Marketing 1,850 103,672,400 56,039 Printing 880 26,698,900 30,340 Public Relations 850 49,554,800 58,300 Publishing 480 22,006,200 45,846

SW/HW 10,110 749,164,100 74,101 Engineering 410 37,292,300 90,957 Health Devices 320 14,416,400 45,051 Manufacturing 310 11,109,300 35,836 Retail 350 28,686,000 81,960 Software 8,720 657,660,100 75,420

Boulder, CO 147,840 8,014,782,900 54,213



Average Wage

Creative Industry Support 6,230 429,384,800 68,922 Post-‐Sec 780 56,474,100 72,403 R&D 3,420 292,522,600 85,533 Services 2,030 80,388,100 39,600

DATA 2,930 238,471,800 81,390 Internet 2,600 214,607,500 82,541 R&D 80 7,976,800 99,710 Telecomm 250 15,887,500 63,550

Design 5,580 492,130,700 88,195 Arch/Eng 340 50,235,000 147,750 Architecture 410 27,998,900 68,290 Engineering 3,540 321,923,900 90,939 Industrial Design 60 3,446,400 57,440 Other Design 50 1,468,500 29,370 Textiles 80 2,038,400 25,480 Urban 1,100 85,019,600 77,291


Fine Arts 390 20,294,300 52,037 Museums 50 2,175,500 43,510 Performing Arts 340 18,118,800 53,291

Media/Communications 4,460 298,504,400 66,929 Advertising 530 59,941,500 113,097 Broadcasting 100 4,464,400 44,644 Graphic Design 580 27,074,200 46,680 Marketing 1,910 129,531,800 67,818 Other 40 1,799,200 44,980 Printing 240 9,218,700 38,411 Public Relations 610 35,107,900 57,554 Publishing 450 31,366,700 69,704

SW/HW 12,500 1,160,784,200 92,863 Engineering 960 106,906,800 111,361 Health Devices 310 17,421,300 56,198 Manufacturing 560 20,064,800 35,830 Retail 940 86,207,400 91,710 Software 9,730 930,183,900 95,600

Cincinnati-‐Middletown, OH-‐KY-‐IN 957,580 42,364,666,200 44,241 Creative Industry Support 29,420 1,656,477,400 56,304 Post-‐Sec 6,510 449,875,100 69,105 R&D 8,080 495,223,400 61,290



Average Wage

Services 14,830 711,378,900 47,969 DATA 9,560 575,752,200 60,225 Internet 6,780 453,578,000 66,899 R&D 600 42,969,000 71,615 Sensor 380 11,320,200 29,790 Telecomm 1,800 67,885,000 37,714

Design 20,560 1,460,970,700 71,059 Arch/Eng 1,490 192,165,300 128,970 Architecture 700 49,894,300 71,278 Engineering 11,880 889,449,000 74,869 Industrial Design 570 39,888,600 69,980 Other Design 730 30,164,500 41,321 Textiles 1,600 40,933,700 25,584 Urban 3,590 218,475,300 60,857

Entertainment 31,410 676,998,800 21,554 Film & Media 460 20,428,900 44,411 Recreation 30,900 654,641,900 21,186 Toys 50 1,928,000 38,560




Cleveland-‐Elyria-‐Mentor, OH 979,250 43,994,055,100 44,926 Creative Industry Support 31,450 1,776,120,200 56,474 Post-‐Sec 7,430 506,122,300 68,119



Average Wage

R&D 7,700 467,993,400 60,778 Services 16,320 802,004,500 49,142


Design 20,310 1,482,401,200 72,989 Arch/Eng 1,620 196,668,000 121,400 Architecture 520 35,568,000 68,400 Engineering 13,730 1,038,144,900 75,611 Industrial Design 250 16,565,000 66,260 Other Design 550 18,416,600 33,485 Textiles 1,210 27,102,700 22,399 Urban 2,430 149,936,000 61,702

Entertainment 28,890 635,232,400 21,988 Film & Media 500 22,280,200 44,560 Recreation 28,320 610,591,800 21,560 Toys 70 2,360,400 33,720



SW/HW 33,730 2,439,250,300 72,317 Engineering 950 78,995,700 83,153 Health Devices 1,400 73,614,600 52,582 Manufacturing 1,890 52,712,100 27,890 Retail 5,890 513,666,900 87,210 Software 23,600 1,720,261,000 72,892

Denver-‐Aurora, CO 1,213,540 61,873,126,400 50,986 Creative Industry Support 44,250 2,897,339,800 65,477



Average Wage

Post-‐Sec 11,580 1,028,650,400 88,830 R&D 15,310 1,099,425,400 71,811 Services 17,360 769,264,000 44,312

DATA 18,320 1,304,871,800 71,227 Internet 12,940 1,019,853,600 78,814 R&D 820 53,846,300 65,666 Sensor 230 7,325,500 31,850 Telecomm 4,330 223,846,400 51,697


Entertainment 43,220 1,134,276,100 26,244 Film & Media 1,580 84,158,700 53,265 Recreation 41,640 1,050,117,400 25,219


Media/Communications 28,180 1,838,047,000 65,225 Advertising 5,360 488,578,200 91,153 Broadcasting 1,040 55,193,200 53,070 Graphic Design 2,920 131,917,200 45,177 Marketing 9,960 657,695,100 66,034 Other 220 11,437,800 51,990 Printing 2,700 98,084,500 36,328 Public Relations 3,680 245,049,400 66,590 Publishing 2,300 150,091,600 65,257


Detroit-‐Warren-‐Livonia, MI 1,699,600 79,513,060,700 46,783 Creative Industry Support 46,800 2,534,888,700 54,164



Average Wage

Post-‐Sec 13,080 892,536,300 68,237 R&D 8,310 482,764,700 58,094 Services 25,410 1,159,587,700 45,635

DATA 16,800 1,015,942,000 60,473 Internet 10,640 751,103,600 70,592 R&D 750 55,981,300 74,642 Sensor 540 16,470,000 30,500 Telecomm 4,870 192,387,100 39,505

Design 58,130 4,266,206,600 73,391 Arch/Eng 5,360 638,483,200 119,120 Architecture 1,180 79,321,500 67,222 Engineering 39,620 2,900,246,800 73,202 Industrial Design 2,310 165,696,300 71,730 Other Design 720 27,066,000 37,592 Textiles 2,310 61,333,700 26,551 Urban 6,630 394,059,100 59,436

Entertainment 55,960 1,377,778,500 24,621 Film & Media 1,760 86,575,100 49,190 Recreation 54,200 1,291,203,400 23,823 Toys

0

Fine Arts 3,640 208,398,600 57,252 Museums 210 10,148,400 48,326 Music 690 37,142,700 53,830 Performing Arts 1,690 101,087,100 59,815 Visual Arts 1,050 60,020,400 57,162



Kansas City, MO-‐KS 957,270 43,571,515,300 45,516



Average Wage

Creative Industry Support 28,360 1,502,156,300 52,967 Post-‐Sec 5,020 335,262,900 66,785 R&D 7,810 465,387,500 59,589 Services 15,530 701,505,900 45,171


Design 18,580 1,302,498,100 70,102 Arch/Eng 1,280 152,384,000 119,050 Architecture 930 66,364,800 71,360 Engineering 9,420 703,814,200 74,715 Industrial Design 170 11,019,400 64,820 Other Design 780 27,293,400 34,992 Textiles 1,110 26,876,800 24,213 Urban 4,890 314,745,500 64,365

Entertainment 33,500 740,144,900 22,094 Film & Media 580 25,444,100 43,869 Recreation 32,920 714,700,800 21,710 Toys

0






Average Wage

Los Angeles-‐Long Beach-‐Santa Ana, CA 5,241,870 270,234,435,600 51,553 Creative Industry Support 186,670 12,015,101,900 64,365 Post-‐Sec 48,410 4,207,966,800 86,924 R&D 43,230 3,169,731,300 73,322 Services 95,030 4,637,403,800 48,799

DATA 66,380 4,373,861,000 65,891 Communications 150 5,884,500 39,230 Internet 32,840 2,573,091,700 78,352 R&D 5,020 499,607,200 99,523 Sensor 4,590 129,116,700 28,130 Telecomm 23,780 1,166,160,900 49,040

Design 157,210 11,504,612,500 73,180 Arch/Eng 10,320 1,552,644,000 150,450 Architecture 5,090 442,755,900 86,985 Engineering 69,470 6,245,395,800 89,901 Industrial Design 1,640 99,777,600 60,840 Other Design 4,620 248,469,800 53,781 Textiles 44,630 1,204,599,000 26,991 Urban 21,440 1,710,970,400 79,803

Entertainment 182,740 5,627,955,200 30,798 Film & Media 17,910 1,401,855,000 78,272 Recreation 164,610 4,219,062,400 25,631 Toys 220 7,037,800 31,990

Fine Arts 78,940 6,723,562,900 85,173 Museums 1,140 61,585,200 54,022 Music 4,410 295,778,700 67,070 Performing Arts 65,000 5,684,913,500 87,460 Visual Arts 8,390 681,285,500 81,202

Media/Communications 156,990 12,025,190,900 76,598 Advertising 39,510 3,968,277,300 100,437 Broadcasting 11,350 729,231,900 64,250 Graphic Design 14,120 798,974,200 56,585 Marketing 46,380 3,544,599,300 76,425 Other 6,690 432,508,500 64,650 Printing 14,410 513,432,400 35,630 Public Relations 11,770 975,001,500 82,838 Publishing 12,760 1,063,165,800 83,320

SW/HW 172,250 15,032,584,300 87,272 Engineering 13,980 1,460,902,800 104,499 Health Devices 11,970 856,900,300 71,587 Manufacturing 10,710 303,784,300 28,365



Average Wage

Retail 16,890 1,406,768,100 83,290 Software 118,700 11,004,228,800 92,706

Louisville-‐Jefferson County, KY-‐IN 574,980 23,614,121,000 41,069 Creative Industry Support 16,960 856,056,300 50,475 Post-‐Sec 4,830 330,280,100 68,381 R&D 2,660 136,438,700 51,293 Services 9,470 389,337,500 41,113




Fine Arts 960 53,256,700 55,476 Museums

0

Music 30 1,699,200 56,640 Performing Arts 750 42,009,400 56,013 Visual Arts 180 9,548,100 53,045

Media/Communications 10,560 577,045,600 54,644 Advertising 2,880 211,960,200 73,597 Broadcasting 250 8,325,000 33,300 Graphic Design 940 35,453,600 37,717 Marketing 2,310 141,488,600 61,250 Other 50 2,681,000 53,620 Printing 2,300 83,406,900 36,264 Public Relations 1,040 58,863,600 56,600 Publishing 790 34,866,700 44,135

SW/HW 13,290 979,963,900 73,737 Engineering 500 39,408,200 78,816 Health Devices 740 28,674,200 38,749 Manufacturing 140 4,676,000 33,400



Average Wage

Retail 2,400 214,656,000 89,440 Software 9,510 692,549,500 72,823

Memphis, TN-‐MS-‐AR 558,200 22,734,212,700 40,728 Creative Industry Support 14,970 859,973,600 57,446 Post-‐Sec 4,130 310,835,500 75,263 R&D 2,820 167,932,000 59,550 Services 8,020 381,206,100 47,532




Fine Arts 680 31,373,100 46,137 Museums 40 1,137,200 28,430 Music 40 1,685,200 42,130 Performing Arts 460 21,012,100 45,678 Visual Arts 140 7,538,600 53,847

Media/Communications 9,410 544,288,400 57,841 Advertising 2,490 202,937,000 81,501 Broadcasting 270 10,419,000 38,589 Graphic Design 810 31,152,800 38,460 Marketing 3,410 196,984,300 57,767 Printing 1,140 37,631,400 33,010 Public Relations 740 38,467,600 51,983 Publishing 550 26,696,300 48,539

SW/HW 12,430 972,602,800 78,246 Engineering 240 20,930,400 87,210 Health Devices 1,000 49,968,900 49,969 Manufacturing 380 15,819,600 41,631 Retail 1,950 189,598,500 97,230



Average Wage

Software 8,860 696,285,400 78,588 New Orleans-‐Metairie-‐Kenner, LA 490,780 20,633,746,900 42,043

Creative Industry Support 14,160 737,588,900 52,090 Post-‐Sec 3,160 233,341,400 73,842 R&D 3,750 218,857,400 58,362 Services 7,250 285,390,100 39,364


Design 10,790 954,003,600 88,416 Arch/Eng 890 136,659,500 153,550 Architecture 330 23,733,600 71,920 Engineering 6,060 569,647,100 94,001 Other Design 330 12,358,400 37,450 Textiles 290 6,510,800 22,451 Urban 2,890 205,094,200 70,967



Media/Communications 5,910 320,105,200 54,163 Advertising 1,510 115,360,700 76,398 Broadcasting 290 14,844,900 51,189 Graphic Design 680 24,679,200 36,293 Marketing 1,390 79,988,600 57,546 Other 50 2,302,000 46,040 Printing 770 21,478,600 27,894 Public Relations 660 34,147,400 51,738 Publishing 560 27,303,800 48,757

SW/HW 7,940 535,319,000 67,421 Engineering 450 38,882,000 86,404 Health Devices 350 11,494,100 32,840 Manufacturing 80 3,472,700 43,409 Retail 1,140 74,955,000 65,750 Software 5,920 406,515,200 68,668



Average Wage

Orlando-‐Kissimmee, FL 989,380 38,832,751,000 39,250 Creative Industry Support 27,350 1,364,354,400 49,885 Post-‐Sec 6,300 465,701,100 73,921 R&D 4,540 250,379,200 55,150 Services 16,510 648,274,100 39,266


Design 18,120 1,168,872,000 64,507 Arch/Eng 1,360 155,842,400 114,590 Architecture 850 63,466,800 74,667 Engineering 8,390 553,564,600 65,979 Industrial Design 120 7,778,400 64,820 Other Design 1,160 37,133,400 32,012 Textiles 1,220 28,480,200 23,344 Urban 5,020 322,606,200 64,264

Entertainment 49,880 1,034,404,600 20,738 Film & Media 1,570 57,296,100 36,494 Recreation 48,310 977,108,500 20,226






Average Wage

Philadelphia-‐Camden-‐Wilmington, PA-‐NJ-‐DE-‐MD 2,568,020 128,480,049,300 50,031

Creative Industry Support 105,670 6,595,023,200 62,411 Post-‐Sec 20,680 1,793,515,700 86,727 R&D 30,390 2,195,268,100 72,237 Services 54,600 2,606,239,400 47,733

DATA 32,420 2,316,889,900 71,465 Communications 70 3,448,200 49,260 Internet 19,390 1,617,298,200 83,409 R&D 2,770 217,616,600 78,562 Sensor 800 28,752,000 35,940 Telecomm 9,390 449,774,900 47,899


Entertainment 98,170 2,328,043,400 23,714 Film & Media 2,420 118,573,000 48,997 Recreation 95,580 2,203,158,300 23,050 Toys 170 6,312,100 37,130

Fine Arts 7,020 481,514,300 68,592 Museums 550 29,034,300 52,790 Music 610 35,020,100 57,410 Performing Arts 4,720 339,460,800 71,920 Visual Arts 1,140 77,999,100 68,420

Media/Communications 58,450 4,228,548,300 72,345 Advertising 12,460 1,222,458,700 98,111 Broadcasting 860 44,876,200 52,182 Graphic Design 5,680 262,200,900 46,162 Marketing 20,040 1,585,101,300 79,097 Other 280 12,636,400 45,130 Printing 7,860 296,191,000 37,683 Public Relations 6,350 498,761,000 78,545 Publishing 4,920 306,322,800 62,261

SW/HW 88,030 7,668,908,500 87,117 Engineering 2,800 258,596,000 92,356 Health Devices 5,600 472,085,200 84,301



Average Wage

Manufacturing 3,780 133,401,600 35,291 Retail 9,210 949,919,400 103,140 Software 66,640 5,854,906,300 87,859

Portland-‐Vancouver-‐Beaverton, OR-‐WA 978,580 47,408,943,600 48,447 Creative Industry Support 33,170 1,989,226,600 59,971 Post-‐Sec 7,290 523,975,800 71,876 R&D 12,010 773,359,600 64,393 Services 13,870 691,891,200 49,884


Design 29,160 2,287,077,800 78,432 Arch/Eng 2,500 339,425,000 135,770 Architecture 1,510 105,312,400 69,743 Engineering 16,110 1,277,864,800 79,321 Industrial Design 200 16,844,000 84,220 Other Design 860 36,044,800 41,913 Textiles 1,180 37,512,100 31,790 Urban 6,800 474,074,700 69,717

Entertainment 30,680 834,797,900 27,210 Film & Media 1,440 68,723,100 47,724 Recreation 29,240 766,074,800 26,200 Toys

0

Fine Arts 4,720 279,110,600 59,134 Museums 100 4,775,500 47,755 Music 1,190 51,776,900 43,510 Performing Arts 2,630 174,454,600 66,333 Visual Arts 800 48,103,600 60,130


SW/HW 41,510 3,212,707,000 77,396 Engineering 2,250 234,112,500 104,050



Average Wage

Health Devices 1,450 82,418,500 56,840 Manufacturing 6,500 224,280,800 34,505 Retail 4,310 405,700,300 94,130 Software 27,000 2,266,194,900 83,933

Salt Lake City, UT 596,330 26,506,586,900 44,450 Creative Industry Support 18,120 861,070,900 47,520 Post-‐Sec 2,330 140,728,600 60,399 R&D 4,860 288,448,100 59,351 Services 10,930 431,894,200 39,515



Entertainment 17,350 427,011,500 24,612 Film & Media 1,440 62,253,900 43,232 Recreation 15,910 364,757,600 22,926


Media/Communications 18,040 945,921,900 52,435 Advertising 4,110 304,061,800 73,981 Broadcasting 540 19,921,600 36,892 Graphic Design 1,570 65,383,500 41,646 Marketing 7,060 328,436,600 46,521 Printing 1,710 53,056,800 31,027 Public Relations 1,460 93,909,800 64,322 Publishing 1,590 81,151,800 51,039

SW/HW 26,070 1,925,147,600 73,845 Engineering 1,820 149,313,000 82,040 Health Devices 1,390 67,349,500 48,453



Average Wage

Manufacturing 1,360 50,090,000 36,831 Retail 3,790 321,998,400 84,960 Software 17,710 1,336,396,700 75,460

San Francisco-‐Oakland-‐Fremont, CA 1,936,000 121,129,646,700 62,567 Creative Industry Support 81,900 6,319,085,600 77,156 Post-‐Sec 20,390 1,758,510,900 86,244 R&D 29,820 2,668,791,700 89,497 Services 31,690 1,891,783,000 59,697

DATA 33,230 2,807,288,600 84,481 Communications

0

Internet 21,800 2,070,068,000 94,957 R&D 2,860 281,977,700 98,594 Sensor 890 31,684,000 35,600 Telecomm 7,680 423,558,900 55,151

Design 56,200 5,229,699,500 93,055 Arch/Eng 5,090 831,095,200 163,280 Architecture 3,240 320,852,600 99,029 Engineering 26,180 2,507,290,600 95,771 Industrial Design 570 42,522,000 74,600 Other Design 2,320 125,610,100 54,142 Textiles 4,910 154,599,200 31,487 Urban 13,890 1,247,729,800 89,829

Entertainment 66,060 2,119,084,600 32,078 Film & Media 4,210 269,487,400 64,011 Recreation 61,770 1,846,199,600 29,888 Toys 80 3,397,600 42,470

Fine Arts 9,960 797,529,500 80,073 Museums 520 29,529,100 56,787 Music 1,400 86,100,000 61,500 Performing Arts 5,920 486,742,400 82,220 Visual Arts 2,120 195,158,000 92,056

Media/Communications 63,300 5,827,616,800 92,063 Advertising 15,610 1,693,404,300 108,482 Broadcasting 1,530 100,674,900 65,801 Graphic Design 5,330 352,103,400 66,061 Marketing 23,280 2,415,704,000 103,767 Other 660 38,339,400 58,090 Printing 3,920 175,999,200 44,898 Public Relations 6,420 624,106,800 97,213 Publishing 6,550 427,284,800 65,234

SW/HW 112,920 11,570,996,000 102,471



Average Wage

Engineering 6,330 695,125,200 109,814 Health Devices 8,090 738,544,300 91,291 Manufacturing 3,960 157,498,600 39,772 Retail 7,930 802,833,200 101,240 Software 86,610 9,176,994,700 105,958

San Jose-‐Sunnyvale-‐Santa Clara, CA 875,190 61,251,854,400 69,987 Creative Industry Support 31,230 2,303,941,000 73,773 Post-‐Sec 7,170 547,486,900 76,358 R&D 11,340 1,003,391,500 88,482 Services 12,720 753,062,600 59,203

DATA 19,640 1,842,871,000 93,833 Internet 12,750 1,304,204,100 102,291 R&D 2,840 319,789,300 112,602 Sensor 540 17,031,600 31,540 Telecomm 3,510 201,846,000 57,506

Design 46,960 5,047,153,000 107,478 Arch/Eng 6,790 1,211,675,500 178,450 Architecture 590 54,940,000 93,119 Engineering 34,770 3,448,253,900 99,173 Industrial Design 200 16,424,000 82,120 Other Design 480 21,929,700 45,687 Textiles 880 22,460,200 25,523 Urban 3,250 271,469,700 83,529


Fine Arts 1,660 114,363,000 68,893 Museums 30 1,864,800 62,160 Music 380 24,327,600 64,020 Performing Arts 910 55,718,300 61,229 Visual Arts 340 32,452,300 95,448

Media/Communications 28,580 3,099,905,600 108,464 Advertising 6,720 904,534,000 134,603 Broadcasting 410 25,833,000 63,007 Graphic Design 1,820 119,088,600 65,433 Marketing 13,680 1,622,615,100 118,612 Other 130 6,705,400 51,580 Printing 1,440 51,196,000 35,553 Public Relations 1,960 178,954,800 91,303 Publishing 2,420 190,978,700 78,917

SW/HW 122,360 13,851,871,400 113,206



Average Wage

Engineering 16,880 2,138,622,000 126,696 Health Devices 2,930 288,370,100 98,420 Manufacturing 7,000 250,398,700 35,771 Retail 8,130 948,933,600 116,720 Software 87,420 10,225,547,000 116,970

St. Louis, MO-‐IL 1,258,350 56,059,127,600 44,550 Creative Industry Support 39,820 2,081,000,700 52,260 Post-‐Sec 11,620 711,617,200 61,241 R&D 9,450 558,962,400 59,149 Services 18,750 810,421,100 43,222

DATA 16,560 1,079,031,700 65,159 Internet 10,780 815,931,500 75,689 R&D 900 52,918,300 58,798 Sensor 450 14,161,500 31,470 Telecomm 4,430 196,020,400 44,248

Design 24,830 1,808,440,800 72,833 Arch/Eng 1,690 208,698,100 123,490 Architecture 1,470 104,597,400 71,155 Engineering 14,180 1,122,922,600 79,191 Industrial Design 150 12,172,500 81,150 Other Design 840 33,499,200 39,880 Textiles 2,100 51,969,300 24,747 Urban 4,400 274,581,700 62,405

Entertainment 49,600 1,115,970,200 22,499 Film & Media 1,590 77,743,400 48,895 Recreation 48,010 1,038,226,800 21,625 Toys

0





Average Wage



Asking Questions

The Creative Sector Survey Between August 16, 2013 and November 21, 2013, 388 people completed the Pittsburgh Regional Workforce & Quality of Life Survey. Only completed surveys were retained and included in the analysis below. The survey and all marketing materials designed to attract respondents were targeted at members of Pittsburgh’s Creative Sector. Individuals working in the industries represented by the seven major cluster categories we asked to complete a series of questions about their work, work experience, and opinion on their individual quality of life in the Pittsburgh region. In some cases, the number of respondents for a particular question may not total 388 as some questions were only asked selectively based on previous responses. Both charts and table are presented in the following section. When a chart is provided, it is followed by a table with the specific data presented in the chart. First basic demographic information about those who completed the survey is presented. This is followed by information about the interaction among the creative industries, live and work locations, quality of place, mobile application development, social media usage, and employment conditions. It should be strongly emphasized that this is a survey whose participants are a “convenience sample”. The results only accurately reflect the participants who completed the survey and do not statistically represent the entire workforce of the Creative Sector. As much as possible, efforts were made to include individuals from across the entire Creative Sector and from throughout the entire region. However, as the results below show, either Creative Sector workers are very different from other workers in the region (this is probably quite true) or the respondents aren’t very representative. Given the convenience sampling that was possible within the desired timeframe and budget, it cannot be determined which of these conditions apply. Based on the industry and some of the other results, it seems as if the 388 participants are generally representative of Pittsburgh’s Creative Sector workers, but that opinion cannot be supported by statistical evidence. The basic demographic data looks at industry, company type, sex, age, race, wages, marital status and education. Information from outside the survey is also presented on race and education level. US Census data is also provided to be able to compare the survey participants to the general population.


Primary Industry Count % Communications 84 21.6% Other 63 16.2% Fine Arts 55 14.2% Creative Industry Support Services 54 13.9% Software & Hardware 51 13.1% Design 49 12.6% Entertainment 27 7.0% Data Science 5 1.3% Grand Total 388 While “other” was the second most selected industry, the list of industries provided by the participants (below) shows that many of what they listed would actually fit within one of the major industry clusters. In general, the survey marketing was successful in reaching people across all of the various clusters of the Creative Sector. While the participation percentages do not exactly match to the employment distribution, in general, fewer participants were from industries that have fewer total employees across the Pittsburgh region. Selected “Other” Response Count Education 6 Non-‐Profit 2


Response Count 4-‐year public university 1 Academic/Higher Education/Innovation Commercialization

1

Affective Computing 1 Banking 1 Building services 1 Career Development 1 Community services 1 Community-‐ based Non-‐profit 1 Corporate Relocation 1 Creative consulting and Art & Design 1 Cultural/Informational library 1 Cutting-‐edge semiconductor and next-‐generation electronics design and implementation

1

Data related business 1 Defense Contracting 1 Economic and Community Development 1 Finance 1 Financial services 1 Food Service/Retail 1 Government 1 Healthcare 1 Higher Education 1 Hi-‐tech consulting -‐ technology implementation and optimization, competitve advantage

1

Human Services 1 I am associated with a major real estate sales organization

1

I work pt as an online teacher, but am working on my own to develop educational technology

1

I'm a freelance artist. No primary employer. 1 I'm a self employed-‐full time artist-‐sole proprietor 1 Investment in entrepreneurs 1 Landscaping 1 Law 1 Libraries 1 Libraries. 1 Manufacturing 1 MEMS and Nanotech hardware 1 Most of the above as a career training center 1 Multimedia -‐ Web Design 1


Response Count Non-‐profit (education, networking, knowledge, resources)

1

Non-‐profit reuse retailer 1 Non-‐profit youth services 1 Non-‐profit, environmentally-‐conscious provider of resources for artists, makers, and educators

1

Organic Skin Care 1 Photographer 1 Printed Corrugated Pop-‐up Displays 1 Process Development for Reuse of Waste Materials

1

Real Estate 1 research education 1 Retail 1 Retailer 1 Self employed 1 Self employed artist 1 Self-‐employed artist 1 Signage, graphics, interiors, product, packaging 1 Spectrometer sales and services 1 University 1 Visual Art Teacher K-‐4 1 We sell creative technologies such as software, 3D printers and other related hardware and curriculu

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Company Type

Count %

For-‐profit company 182 46.9% Not specified/Self-‐Employed 100 25.8% Not for profit / charitable organization 58 14.9% Educational institution 43 11.1% Government 5 1.3% Grand Total 388 About half the participants were employees at a for-‐profit company. Most of the one-‐quarter who were not from one of the listed categories, said that they were self-‐employed or working as a freelancer. Interesting, those same respondents when given the option did not chose to identify as being from a place with a profit motive. It is likely that they focused more on the “company” aspect. As freelancers were more specifically identified in the survey, they were not included here, but these results align with those results and suggest that roughly one-‐quarter of the survey participants are primarily self-‐employed in some way.


Sex Count % Female 198 51.0% Male 188 48.5% (blank) 2 0.5% Grand Total 388

Row Labels Count % 18 -‐ 24 13 3.4% 25 -‐ 29 45 11.6% 30 -‐ 34 49 12.6% 35 -‐ 44 90 23.2% 45 -‐ 54 104 26.8% 55 -‐ 64 63 16.2% 65 or older 22 5.7% (blank) 2 0.5% Grand Total 388


Row Labels Count % African-‐American 14 3.6% Asian 5 1.3% Caucasian 346 89.2% Hispanic 5 1.3% Native-‐American 1 0.3% Other 12 3.1% (blank) 5 1.3% Grand Total 388 Obviously, survey participants are by and large a group of white men and women. While sex split almost 50-‐50 and the all age ranges were represented, nearly 90% of the participants identified as white. So, while striking, the graph below provides roughly the same information for Pittsburgh as estimated by the 2012 American Communities Survey (ACS). As Census collects separate date on race and Hispanic status, the results are not directly comparable, but they are very close. While the city of Pittsburgh has a large and significant African-‐American population, the same cannot be said of the Pittsburgh region. As the Census data reveals, nearly 90% of the population of the Pittsburgh region self-‐identifies as white. While the survey participants may not be racially representative of the city of Pittsburgh, they can be considered as roughly representative of the Pittsburgh region.


Pittsburgh, PA

Metro Area; Pennsylvania

Estimate % Total: 2,357,981 100.0% White alone 2,071,435 87.8% Black or African American alone 193,925 8.2% American Indian and Alaska Native alone 2,348 0.1% Asian alone 42,126 1.8% Native Hawaiian and Other Pacific Islander alone 434 0.0% Some other race alone 6,991 0.3% Two or more races 40,722 1.7%


Count % Under20 29 7.5% 20-‐40 68 17.5% 40-‐75 114 29.4% 75-‐100 64 16.5% Over 100 86 22.2% (blank) 27 7.0% Grand Total 388 As reported above, the average wages outside the Creative Sector in Pittsburgh are roughly $44,000. For the seven creative clusters, average wages range from $21,000 to $73,000 per year. Most are in the upper 50’s to lower 60’s. The survey results are generally in line with the objective, independent information lending additional support to the argument that the survey participants are representative of Pittsburgh’s Creative Sector workforce.


Row Labels Count % Divorced/Separated 26 6.7% Married/Partnered 249 64.2% Single 100 25.8% Widowed 6 1.5% (blank) 7 1.8% Grand Total 388 Marital status is shown and generally reflects the “family” orientation that many in Pittsburgh frequently put forward, but it also shows that nearly one-‐third of the respondents are single.


Row Labels Count % High school graduate or less 2 0.5% Some college 15 4.0% Associate or junior college degree 26 7.0% Bachelor's degree 137 36.9% Post-‐graduate work or degree 203 54.7% (blank) 5 1.3% Grand Total 371 Clearly, respondents are highly educated. Over half report completing some education beyond a bachelor’s degree. This is significantly different than for the Pittsburgh region overall, where according to the 2012 ACS, just under 11% of the population has completed a graduate or professional degree. As noted above, it is unclear because of the sampling method employed for the survey whether that difference is simply an artifact of the sample of people who completed the survey or if it is a structural difference between the general population and individuals working in the Creative Sector. The comparability of other results in the survey to more objective data supports the argument that these results are structural. And, generally those working in the creative sector are more educated. And, while the results support that argument, it cannot be interpreted as being statistically or in any other way a significant result – just really interesting.


Subject Pittsburgh, PA Metro

Area EDUCATIONAL ATTAINMENT Estimate Percent Population 25 years and over 1,668,898 1,668,898 Less than 9th grade 41,444 2.50% 9th to 12th grade, no diploma 102,536 6.10% High school graduate (includes equivalency) 612,319 36.70% Some college, no degree 282,857 16.90% Associate's degree 148,222 8.90% Bachelor's degree 300,215 18.00% Graduate or professional degree 181,305 10.90%


Interconnectivity between the Creative Industries Participants were asked based on their reported industry how often they interacted with people from the other creative sector clusters. They indicated whether they interacted rarely/never (1), monthly (2), weekly (3), or daily (4) with the other industry sectors. The two tables below summarize those results. The first table considers by industry how frequently people reported working with the other industries. The columns are as follows:

Industry In which of the seven clusters does the respondent work? Avg What is average of all the responses scored on the 1 to 4

scale? The higher the number, the more often someone in that industry reported interacting with someone in one of the industry clusters/subclusters.

Over 2 For each industry cluster, the respondent was presented with a list of all the industry subclusters and asked to report the frequency of their interaction with those subclusters. Depending on the cluster, the number of subclusters varied (see Total next). This column reports the number of times that the average of all reported interactions for that cluster with the other subclusters was greater than 2. Effectively, this is a count of the number of subclusters with which the average respondent reported either weekly or daily interaction with another creative cluster or subcluster.

Total The total number of possible interactions based on the current cluster.

% Count over 2 The percentage of weekly or daily interactions (on average) across all possible interactions. This percentage represents the spillover potential an industry. The higher the percentage, the more likely that a firm in that industry is frequently engaging with firms in other industries across the creative spectrum.

Over 2 (not own ind)

Since the subclusters where included, a person also reported interactions with firms in their same cluster but in a different subcluster. For example Design firms in Architecture reported interactions with Design firms in Engineering. While clearly a good thing, one would expect that firms within the same high-‐level cluster would be more likely to interact with each other than with firms in a different cluster. This count excludes interactions with firms that are in the same cluster and only counts interactions with firms in other clusters.

% Count over 2 (not own ind)

This is the percentage of possible inter-‐cluster interactions that occur on average on a weekly or daily basis. The higher this percentage, the more likely that a firm in that industry is frequently engaging with firms in other clusters. Effectively, this is a measure of the potential for “spill-‐acrosses” instead of just spillovers.


1=rarely/never;4=daily Industry Avg Over 2 Total % Count

over 2 Over 2 (not own ind)

% Count over 2 (not own ind)

COMM 2.31 36 63 57.1% 28 44.4% ARTS 1.94 16 49 32.7% 9 18.4% CISPT 1.83 26 77 33.8% 17 22.1% SW 1.70 8 42 19.0% 5 11.9% DESIGN 1.60 7 49 14.3% 3 6.1% ENTER 1.59 11 49 22.4% 6 12.2% DATA 1.48 4 42 9.5% 3 7.1% This next table shows the average interaction frequencies between someone working in one of the industry clusters (the high-‐level clusters) in the columns and the specific industry subclusters, listed in the rows. For example, on average people working in the Cultural Industry Support Industry (CISPT), reported interacting with someone working in Media/Communications (COMM) advertising with between monthly (3) and weekly (2) frequency (the reported average is 2.4). For this table, the higher the number the more frequent the interactions between the creative cluster and the specific subcluster. Keep in mind that the score could not be lower than 1 or higher than 4 so a score at or near 1 indicates little or no interaction while a score above 3 indicates frequent interaction. The data is repeated in the following table but in a “heat map” format – the darker the red background, the more frequent and more likely there is an interaction between the creative industries clusters and subclusters. 1=rarely/never;4=daily Interacts with Industry/Subcluster COMM CISPT DATA DESIGN ENTER ARTS Other SW COMM-‐Advertising 3.2 2.4 2.0 1.9 2.3 2.3 2.2 1.9 COMM-‐Audio Services 2.0 1.4 2.0 1.1 2.1 1.6 1.6 1.3 COMM-‐Marketing 3.5 2.6 2.2 2.7 2.6 2.6 2.6 2.4 COMM-‐Public Relation 2.9 2.4 1.8 1.9 2.2 2.4 2.4 1.9 COMM-‐Print Productio 2.6 2.2 2.0 2.0 2.1 2.3 2.3 1.6 COMM-‐Publishing 2.4 1.9 2.2 1.5 2.1 1.8 2.1 1.4 COMM-‐Video Productio 2.5 1.9 2.0 1.5 2.3 1.8 1.8 1.4 COMM-‐Social Media 3.6 2.9 1.8 2.7 3.2 3.4 2.9 2.3 COMM-‐Graphic Design 3.5 2.5 1.8 2.4 2.5 2.4 2.5 2.3 DESIGN-‐Architecture 1.5 1.6 1.2 2.2 1.4 1.5 1.8 1.1 DESIGN-‐Industrial Desi 1.4 1.7 2.0 2.1 1.5 1.4 1.6 1.6 DESIGN-‐Advanced Manufa 1.6 1.8 1.4 2.2 1.4 1.3 1.6 1.7 DESIGN-‐Engineering 1.6 2.1 2.4 2.8 1.7 1.4 2.2 2.2 DESIGN-‐Making 1.4 1.9 2.0 2.7 1.7 1.9 1.8 1.5 DESIGN-‐Textiles 1.1 1.2 1.4 1.7 1.3 1.5 1.4 1.1 DESIGN-‐Urban Systems 1.3 1.4 2.0 1.6 1.1 1.2 1.5 1.1 ENTER-‐Education IT/Te 2.1 2.5 2.2 1.9 2.5 2.0 2.5 2.0


1=rarely/never;4=daily Interacts with Industry/Subcluster COMM CISPT DATA DESIGN ENTER ARTS Other SW ENTER-‐Animation 1.7 1.4 1.6 1.3 2.6 1.3 1.4 1.3 ENTER-‐Gaming 1.3 1.6 1.4 1.2 2.4 1.2 1.4 1.2 ENTER-‐Post-‐Production 2.0 1.4 1.6 1.3 2.7 1.4 1.4 1.1 ENTER-‐Theme Parks & R 1.2 1.2 1.0 1.2 1.8 1.1 1.2 1.0 ENTER-‐Toys 1.2 1.2 1.2 1.2 1.7 1.2 1.3 1.0 ENTER-‐Film & Digital 2.5 1.9 2.0 1.6 3.1 2.0 2.1 1.5 ARTS-‐Arts Organizati 2.1 2.1 1.0 1.8 2.6 3.4 2.3 1.2 ARTS-‐Arts Venues 1.9 2.0 1.0 1.7 2.3 3.2 2.0 1.2 ARTS-‐Music 1.8 1.7 1.2 1.4 2.4 2.8 1.9 1.1 ARTS-‐Performing Arts 1.8 1.8 1.0 1.4 2.6 3.0 1.9 1.0 ARTS-‐Visual Arts 2.0 1.9 1.0 1.9 2.1 2.9 2.3 1.3 ARTS-‐Interactive Art 1.9 1.7 1.2 1.6 2.2 2.5 1.8 1.3 ARTS-‐Museums & Galle 1.9 1.7 1.0 1.8 2.0 2.6 2.0 1.1 SW-‐Augmented Reali 1.3 1.3 1.8 1.1 1.6 1.1 1.2 1.4 SW-‐Health IT/Medic 1.7 1.7 2.2 1.7 1.4 1.1 1.6 2.3 SW-‐Robotics 1.3 1.6 2.0 1.4 1.4 1.2 1.4 1.4 SW-‐Mobile Applicat 2.3 1.9 2.6 1.7 2.3 1.6 2.0 2.8 SW-‐Responsive Envi 1.8 1.5 2.0 1.5 1.4 1.2 1.4 1.9 SW-‐Software Develo 2.1 2.4 3.2 2.0 2.1 1.4 2.0 3.6 DATA-‐Big Sensor 1.1 1.6 2.6 1.2 1.1 1.1 1.4 1.5 DATA-‐Big Data 1.8 1.9 2.8 1.5 1.3 1.4 1.7 2.1 DATA-‐Pervasive Compu 1.2 1.6 2.4 1.3 1.4 1.1 1.3 1.6 DATA-‐Embedded Comput 1.1 1.6 2.8 1.4 1.3 1.1 1.5 1.7 DATA-‐Telecommunicati 1.6 2.1 3.0 1.7 1.9 1.6 1.9 2.3 DATA-‐Parallel Comput 1.1 1.5 2.8 1.3 1.4 1.2 1.3 1.5 CISPT-‐Consulting 2.5 2.9 2.0 2.5 1.9 1.8 2.2 2.7 CISPT-‐Co-‐Working Spac 1.6 2.0 2.4 1.4 1.6 1.5 1.5 1.7 CISPT-‐Incubators/Acce 1.4 2.0 1.5 1.4 1.6 1.3 1.3 1.6 CISPT-‐University R&D 1.4 2.6 3.0 1.7 1.7 1.4 1.8 1.6 CISPT-‐Government R&D 1.2 1.9 2.0 1.4 1.3 1.2 1.5 1.5 CISPT-‐Corporate R&D 1.5 2.2 1.8 1.8 1.2 1.2 1.5 2.0 CISPT-‐Post-‐Secondary 1.7 2.6 1.0 1.7 2.0 1.8 2.3 1.6 CISPT-‐Related Service 2.2 2.7 1.4 2.4 2.2 1.9 2.2 2.4 CISPT-‐Trade Associati 2.0 2.2 1.5 2.3 1.9 1.8 1.9 2.0 CISPT-‐Professional So 2.1 2.5 1.5 2.5 1.9 1.9 2.3 1.9 CISPT-‐Seed & Venture 1.4 1.9 1.8 1.4 1.5 1.2 1.5 1.5


Creative Industry Interactivity Heat Map Interacts with Industry ARTS CISPT COMM DATA DSGN ENTR SW Other ARTS-‐Arts Organizati 3.4 2.1 2.1 1.0 1.8 2.6 1.2 2.3 ARTS-‐Arts Venues 3.2 2.0 1.9 1.0 1.7 2.3 1.2 2.0 ARTS-‐Interactive Art 2.5 1.7 1.9 1.2 1.6 2.2 1.3 1.8 ARTS-‐Museums & Galle 2.6 1.7 1.9 1.0 1.8 2.0 1.1 2.0 ARTS-‐Music 2.8 1.7 1.8 1.2 1.4 2.4 1.1 1.9 ARTS-‐Performing Arts 3.0 1.8 1.8 1.0 1.4 2.6 1.0 1.9 ARTS-‐Visual Arts 2.9 1.9 2.0 1.0 1.9 2.1 1.3 2.3 CISPT-‐Consulting 1.8 2.9 2.5 2.0 2.5 1.9 2.7 2.2 CISPT-‐Corporate R&D 1.2 2.2 1.5 1.8 1.8 1.2 2.0 1.5 CISPT-‐Co-‐Working Spac 1.5 2.0 1.6 2.4 1.4 1.6 1.7 1.5 CISPT-‐Government R&D 1.2 1.9 1.2 2.0 1.4 1.3 1.5 1.5 CISPT-‐Incubators/Acce 1.3 2.0 1.4 1.5 1.4 1.6 1.6 1.3 CISPT-‐Post-‐Secondary 1.8 2.6 1.7 1.0 1.7 2.0 1.6 2.3 CISPT-‐Professional So 1.9 2.5 2.1 1.5 2.5 1.9 1.9 2.3 CISPT-‐Related Service 1.9 2.7 2.2 1.4 2.4 2.2 2.4 2.2 CISPT-‐Seed & Venture 1.2 1.9 1.4 1.8 1.4 1.5 1.5 1.5 CISPT-‐Trade Associati 1.8 2.2 2.0 1.5 2.3 1.9 2.0 1.9 CISPT-‐University R&D 1.4 2.6 1.4 3.0 1.7 1.7 1.6 1.8 COMM-‐Advertising 2.3 2.4 3.2 2.0 1.9 2.3 1.9 2.2 COMM-‐Audio Services 1.6 1.4 2.0 2.0 1.1 2.1 1.3 1.6 COMM-‐Graphic Design 2.4 2.5 3.5 1.8 2.4 2.5 2.3 2.5 COMM-‐Marketing 2.6 2.6 3.5 2.2 2.7 2.6 2.4 2.6 COMM-‐Print Productio 2.3 2.2 2.6 2.0 2.0 2.1 1.6 2.3 COMM-‐Public Relation 2.4 2.4 2.9 1.8 1.9 2.2 1.9 2.4 COMM-‐Publishing 1.8 1.9 2.4 2.2 1.5 2.1 1.4 2.1 COMM-‐Social Media 3.4 2.9 3.6 1.8 2.7 3.2 2.3 2.9 COMM-‐Video Productio 1.8 1.9 2.5 2.0 1.5 2.3 1.4 1.8 DATA-‐Big Data 1.4 1.9 1.8 2.8 1.5 1.3 2.1 1.7 DATA-‐Big Sensor 1.1 1.6 1.1 2.6 1.2 1.1 1.5 1.4 DATA-‐Embedded Comput 1.1 1.6 1.1 2.8 1.4 1.3 1.7 1.5 DATA-‐Parallel Comput 1.2 1.5 1.1 2.8 1.3 1.4 1.5 1.3 DATA-‐Pervasive Compu 1.1 1.6 1.2 2.4 1.3 1.4 1.6 1.3 DATA-‐Telecommunicati 1.6 2.1 1.6 3.0 1.7 1.9 2.3 1.9 DESIGN-‐Advanced Manufa 1.3 1.8 1.6 1.4 2.2 1.4 1.7 1.6 DESIGN-‐Architecture 1.5 1.6 1.5 1.2 2.2 1.4 1.1 1.8 DESIGN-‐Engineering 1.4 2.1 1.6 2.4 2.8 1.7 2.2 2.2 DESIGN-‐Industrial Desi 1.4 1.7 1.4 2.0 2.1 1.5 1.6 1.6 DESIGN-‐Making 1.9 1.9 1.4 2.0 2.7 1.7 1.5 1.8 DESIGN-‐Textiles 1.5 1.2 1.1 1.4 1.7 1.3 1.1 1.4 DESIGN-‐Urban Systems 1.2 1.4 1.3 2.0 1.6 1.1 1.1 1.5 ENTER-‐Animation 1.3 1.4 1.7 1.6 1.3 2.6 1.3 1.4 ENTER-‐Education IT/Te 2.0 2.5 2.1 2.2 1.9 2.5 2.0 2.5 ENTER-‐Film & Digital 2.0 1.9 2.5 2.0 1.6 3.1 1.5 2.1 ENTER-‐Gaming 1.2 1.6 1.3 1.4 1.2 2.4 1.2 1.4 ENTER-‐Post-‐Production 1.4 1.4 2.0 1.6 1.3 2.7 1.1 1.4 ENTER-‐Theme Parks & R 1.1 1.2 1.2 1.0 1.2 1.8 1.0 1.2 ENTER-‐Toys 1.2 1.2 1.2 1.2 1.2 1.7 1.0 1.3 SW-‐Augmented Reali 1.1 1.3 1.3 1.8 1.1 1.6 1.4 1.2 SW-‐Health IT/Medic 1.1 1.7 1.7 2.2 1.7 1.4 2.3 1.6 SW-‐Mobile Applicat 1.6 1.9 2.3 2.6 1.7 2.3 2.8 2.0 SW-‐Responsive Envi 1.2 1.5 1.8 2.0 1.5 1.4 1.9 1.4 SW-‐Robotics 1.2 1.6 1.3 2.0 1.4 1.4 1.4 1.4 SW-‐Software Develo 1.4 2.4 2.1 3.2 2.0 2.1 3.6 2.0


Live/Work Locations Respondents were asked to provide the zip code of where the live and the zip code where they do most of their work. Nearly a third (122 or 31.8%) reported the same zip code for both live and work. This does not necessarily mean that they are working from home but does indicate that they are most likely living and working at locations that are a short walk, bike ride, or drive from each other. Overall, about two-‐thirds of respondents live in the City of Pittsburgh (152xx) and nearly three-‐quarters work in the City. Most of the others are in the area right around the City of Pittsburgh (151xx) while a few are scattered throughout the region. Row Labels Live3 Row Labels Work3 Location

Other 20 5.2% Other 26 6.7% 150 28 7.2% 150 22 5.7% Pittsburgh North 151 44 11.3% 151 28 7.2% Pittsburgh Vicinity 152 256 66.0% 152 284 73.2% Pittsburgh City 153 11 2.8% 153 8 2.1% Pittsburgh Southwest 154 1 0.3% 154 1 0.3% Pittsburgh Southeast 156 14 3.6% 156 12 3.1% Greensburg 160 14 3.6% 160 7 1.8% New Castle

Grand Total 388 Grand Total 388 Quality of Living – Pittsburgh Participants were asked the rate the Pittsburgh region on a series of factors. For each of the factors (listed below) they were to score the region’s performance on that factor ranging from poor (1) to ideal (4). This was clearly put forward as a subjective evaluation. Each respondent was to provide his/her opinion of how they saw the Pittsburgh region based on the factors. Average 1 -‐ Poor 2 3 4 -‐ Ideal (blank) Cost of living 2.92 1 14 151 221 1 Overall 2.89 2 34 271 78 3 Availability of education 2.86 1 22 130 233 2 Sense of community 2.82 8 40 181 158 1 Quality of education 2.79 5 39 145 198 1 Social environment 2.74 10 80 230 66 2 Providing a healthy environment 2.73 18 79 219 70 2 The environment 2.72 24 85 224 51 4 Financial issues 2.71 8 91 220 56 13 Career opportunities 2.51 26 158 165 38 1


Two Most Important Assets of the Pittsburgh Region They were then asked to identify the two factors that they thought were most important to them personally. The first table shows the average of the responses across all ten factors. The region scores highest on cost of living and lowest on career opportunities. But, for all of the listed factors, the average performance was above 2 (fair). Cost of living and career opportunities were also identified as the most important factors as shown in the second table. No Yes %yes Cost of living 152 236 60.8% Career opportunities 180 208 53.6% Sense of community 206 182 46.9% Providing a healthy environment 256 132 34.0% Social environment 300 88 22.7% Quality of education 316 72 18.6% The environment 321 67 17.3% Overall 342 46 11.9% Availability of education 353 35 9.0% Financial issues 362 26 6.7% Mobile Development The table below incorporates the results of two interrelated questions. The first question (“do mobile” in the blue rows) was whether or not a person currently does mobile application development. Respondents could answer yes (21.4%), no (55.7%), or no, but I would like to learn (22.4%). The second question asked of all respondents was about whether they wanted to do mobile application development. The possible answers were yes or no. For the second question, the responses were split nearly 50-‐50 with 198 answering yes and 189 answering no. The table below shows the answers as provided based on whether people are currently doing mobile app development. Essentially, about half of the respondents would like to do mobile app development and about half of them or a quarter of the total are currently doing mobile app development. Row Labels Count % Do Mobile No 216 55.7% Would like No 154 71.3% Would like Yes 61 28.2% Would like (blank) 1 0.5% Do Mobile No, but want to learn 87 22.4% Would like No 14 16.1% Would like Yes 73 83.9% Do Mobile Yes 83 21.4% Would like No 19 22.9% Would like Yes 64 77.1% Do Mobile (blank) 2 0.5% Would like No 2 Do Mobile Grand Total 388


Social Media Visits The table below indicates the average and specific answer counts for the respondents in terms of visiting social media sites. Facebook is the most visited, averaging visits multiple days every week, with most people visiting it daily. Twitter is used either daily or not at all while Linked-‐In is used daily or weekly. The other sites are not visited frequently by many of the respondents. A few of the “other” responses were indicated by multiple people and are shown in the second table. Average 1 -‐ Seldom

or Never 2 -‐ About once a week

3 -‐ Several days a week

4 -‐ Daily/Almost every day

(blank)

Facebook 3.19 55 54 37 241 1 Twitter 2.37 151 58 51 125 3 Linked-‐In 2.74 63 101 87 134 3 Pinterest 1.66 233 76 33 40 6 Snap Chat 1.13 349 10 7 12 10 Google + 1.79 208 90 40 47 3 Other 0.76 142 10 9 26 201 Select Other Sites Row Labels Count Instagram 14 tumblr 7 vine 4 YouTube 2 About.me 1 academia.edu 1 Angel.co 1 Freelance Work Freelance work or “free agent” or subcontracting work is often seen as a primary means of employment within the creative sector. A series of three questions were asked with variation based on the respondent’s answers. The results are in the two tables, chart, and table shown below. The first asked if a person received most of their income from freelance work. Nearly one-‐quarter of the respondents indicated that they mostly worked freelance. This is nearly four times the general share of self-‐employment (6%) reported by the Census in the ACS for the Pittsburgh region. When someone indicated their primary source of income was not from freelancing, they were asked if they earned any income from freelance work. Of the 292 people who had major income outside of freelancing, over half (51.7%) indicated that they still earned some money from freelancing. Of the 388 people who completed the survey three in five (59.5%) earned some income from freelance work. The chart and the final table show, for all respondents who indicated that they did any freelance work, whether as primary or supplementary income, the average number of hours worked each week. While over half worked ten hours or less each week, nearly a quarter (22.2%) worked forty hours or more each week. As this number is lower than the share who said the majority of their income was from freelance work, a small number of people are doing freelance work for the majority of their income but working less than 40 hours a week.


Q15 Row Labels Count Mostly Freelance No 292 75.3% Yes 96 24.7% Grand Total 388 Q21 Row Labels Count FT plus freelance No 151 51.7% Yes 135 46.2% (blank) 6 2.1% Grand Total 292 100.0%

Freelance Hours Count 0 3 1.3% 1-‐10 117 50.9% 11-‐25 43 18.7% 26-‐39 16 7.0% 40 26 11.3% 40+ 25 10.9% (blank) 158 Grand Total 388 Along with freelance work, respondents reported that nearly three in ten of their employers have hired transient (non-‐local) workers to assist with specific skills or on projects.


Q18 Row Labels Count Hire Transients No 182 46.9% Yes 110 28.4% (blank) 96 24.7% Grand Total 388 The final tables and charts in this section look at employment situations for those working in the Creative Sector. The first chart and table show the results of how often respondents have changed employers over the past five years. Only about one-‐third have not changed employers – although the large number of blank responses suggests that people who had not changed employers at all simply skipped this question rather than selecting the “never” option. If that is the case, then over half have not switched employers. However, one in five have switched employers once and one in ten have switched two times and one in ten has switched three times.

Row Labels Count Never 138 35.6% Once 72 18.6% Twice 36 9.3% Three times 33 8.5% Four times 11 2.8% Five or more times 1 0.3% (blank) 97 25.0% Grand Total 388


Respondents were asked to select their top two factors that would lead them to change their job from a list of 10 (with an added “other” option available but not really used). Money and type of work were the clear favorites. Over 40% selected at least one of the two. Hours/work balance and professional growth were each mentioned by one in six respondents while one in ten mentioned location. The other factors were not mentioned very frequently. Top Two Factors to Change Current Job No Yes %yes Salary / Hourly Rate 225 163 42.0% Type or Quality of Work 227 161 41.5% Hours (work-‐life balance& 319 69 17.8% Professional Growth (lear 326 62 16.0% Location 351 37 9.5% Room for Advancement 367 21 5.4% Health & Dental Benefits 375 13 3.4% Other 375 13 3.4% Employer’s Reputation 378 10 2.6% Education or Professional 381 7 1.8% Retirement Fund (employer 386 2 0.5% Finally, the respondents were asked if they would be interested in attending peer-‐to-‐peer, networking, summit and other similar events. Over three-‐quarters indicated that they would be somewhat or very interested in finding ways of connecting with others working in Pittsburgh’s Creative Sector. Interested in Peer-‐to-‐Peer, Summits, Events Row Labels Count Not at all interested 24 6.2% Not too interested 60 15.5% Somewhat interested 192 49.5% Very interested 111 28.6% (blank) 1 0.3% Grand Total 388


Focus Groups Seven focus groups, one for each of the major creative sector clusters, were held with sixty-‐nine participants. The participants were asked to generate positive, negative and creative/innovative ideas with regard to Pittsburgh’s Creative Sector. The detailed notes from all sessions are available. The table below summarizes the number of different ideas and comments made at each of the focus group sessions and indicates if the comment was focused around workforce (talent), culture and diversity (Inclusiveness), innovation (technology) or quality of life (territory assets). These comments and creative ideas were used to assist in the formulation of the various recommendations assembled for this report. PTC Creative Industries Study Cluster Focus Group Analysis v3.0

Fine Arts = 11 (Participants)

Strengths Challenges

New Ideas Total

Workforce 24 14 18 56 Culture & Diversity 14 22 13 49 Innovation 9 4 5 18 Quality of Life 21 12 13 46 Totals 68 52 49 169 Software/ Hardware & Big Data = 10


New Ideas Total

Workforce 15 20 15 50 Culture & Diversity 5 8 9 22 Innovation 12 6 3 75 Quality of Life 11 6 7 24 Totals 43 40 34 171 Entertainment = 14


New Ideas Total

Workforce 22 24 16 62 Culture & Diversity 9 17 8 34 Innovation 9 3 6 18 Quality of Life 27 16 17 60 Totals 67 60 47 174 Design = 16


New Ideas Total

Workforce 18 9 14 41 Culture & Diversity 7 8 3 18 Innovation 4 4 2 10 Quality of Life 22 20 13 55 Totals 51 41 32 124 CI Support = 17



New Ideas Total

Workforce 24 22 5 51 Culture & Diversity 6 16 7 29 Innovation 8 6 1 15 Quality of Life 18 10 5 33 Totals 56 54 18 128 Communications = 16


New Ideas Total

Workforce 29 11 14 54 Culture & Diversity 12 12 9 33 Innovation 18 11 12 41 Quality of Life 22 20 9 52 Totals 81 54 44 180

Total Participants = 69 Sub-Total Ideas 366 301 224 946

Other/Unclassified Ideas 28 164 55 83 TOTAL IDEAS 394 465 279 1138

Workforce 314 Culture & Diversity 185 Innovation 177 Quality of Life 270 Total 946


Focus Groups: The Future of the Creative Industries in our Region Challenges

Opportunities

Strengths

inclusion, innovation, and integrative design pittsburgh’s creative … · 2014-02-19 ·...

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