Cluster Atlas of Canada A data profile of resource, manufacturing, and service clusters in Canadian provinces using data from the 2011 Census and National Household Survey

March, 2014

Prepared by: Funded by:

Gregory M Spencer, M.Sc.Pl., Ph.D. Manager of Local IDEAs Munk School of Global Affairs University of Toronto [email protected]

Cluster Atlas of Canada Page 1 Report Highlights

This report identifies where the major •Key highlights include: industrial clusters exist within Canada and provides indicators of their relative- 230 cases of clusters identified in performance. The purpose is to provide a- • Canada comprehensive overview of the econom ic landscape of the country and map ar Ontario leads with 86, followed by eas of strengths and weakness in order to British Columbia (43), Québec (39), inform decisions concerning allocation- • and Alberta (30) of public resources. A well-established methodology for identifying and map There is a general lack of clusters in ping clusters is derived from the work • Atlantic Canada of Spencer et al (2010). The main data- - sources are the 2011 National Household Oil & gas and mining have been the- Survey and a 2011 universal business es best performing sets of clusters be tablishment database acquired from Dun tween 2001 and 2011 in terms of em & Bradstreet. • ployment growth and incomes - - Service clusters such as business ser vices, finance, ICT services, and cre ative & cultural industries tend to be located in the largest urban areas and • are experiencing high levels of growth-

More traditional manufacturing clus ters such as auto manufacturing, steel, plastics & rubber have generally been • struggling over the past decade - The previous two points suggest that- there is a growing prosperity gap be tween smaller/mid-sized urban re • Knowledgegions and the intensive largest manufacturing urban regions clusters such as ICT and life sciences (including pharma) have shown some- what mixed performance

Cluster Atlas of Canada Page 2 Table of Contents

Section Page 1.0 Introduction 5 1.1 Aims of the report 5 1.2 A brief survey of cluster theory 5 1.3 Criticisms of the cluster concept 6 1.4 Recent developments on clusters 7

2.0 Data & Methods 8 2.1 Cluster identification 8 2.2 Cluster indicators 8 2.3 Primary data sources 9 2.4 How to read and interpret the results 9

3.0 National Overview 10

4.0 Cluster Types 13 4.1 Agriculture 14 4.2 Maritime 15 4.3 Forestry & Wood 16 4.4 Mining 17 4.5 Oil & Gas 18 4.6 Construction 19 4.7 Logistics 20 4.8 Textiles 21 4.9 Food & Beverage 22 4.10 Aluminum 23 4.11 Steel 24 4.12 Auto Manufacturing 25 4.13 Plastics & Rubber 26 4.14 Life Sciences 27 4.15 Aerospace 28 4.16 ICT Manufacturing 29 4.17 ICT Services 30 4.18 Finance 31 4.19 Business Services 32 4.20 Creative & Cultural 33 4.21 Higher Education 34

5.0 Cluster Profiles 5.1 Atlantic Canada 35 5.1.1 St. John’s Food & Beverage 36 5.1.2 St. John’s Business Services 38

Cluster Atlas of Canada Page 3 5.1.3 Charlottetown Higher Education 40 5.1.4 Halifax Maritime 42 5.1.5 Cape Breton Mining 44 5.1.6 Moncton Logistics 46 5.1.7 Fredericton Business Services 48

5.2 Quebec 50 5.2.1 Saguenay Aluminum 52 5.2.2 Rouyn-Noranda Mining 54 5.2.3 Quebec Life Sciences 56 5.2.4 Montreal Finance 58 5.2.5 Montreal Creative & Cultural 60

5.3 Ontario 62 5.3.1 Sudbury Mining 65 5.3.2 Hamilton Steel 67 5.3.3 Windsor Auto Manufacturing 69 5.3.4 London Food & Beverage 71 5.3.5 Hamilton Life Sciences 73 5.3.6 Kitchener-Waterloo ICT Manufacturing 75 5.3.7 Toronto Finance 77 5.3.8 Toronto Creative & Cultural 79

5.4 Prairies 81 5.4.1 Brandon Agriculture 83 5.4.2 Winnipeg Life Sciences 85 5.4.3 Saskatoon Agriculture 87 5.4.4 Saskatoon Mining 89 5.4.5 Wood Buffalo Oil & Gas 91 5.4.6 Calgary Oil & Gas 93 5.4.7 Calgary Logistics 95

5.5 British Columbia 97 5.4.1 Prince George Forestry & Wood 99 5.4.2 Abottsford-Mission Food & Beverage 101 5.4.3 Vancouver ICT Services 103 5.4.4 Vancouver Creative & Cultural 105 5.4.5 Victoria Business Services 107

6.0 Discussion & Conclusions 109

Appendix A Cluster Definitions 111 Appendix B City-region Innovation Indicators 132 References 134

Cluster Atlas of Canada Page 4 1.0 Introduction 1.1 Aims of the report -

industrial activity within particular plac - es provides the basis for their economic The purpose of this report is to provide a- prosperity and growth. Policy-makers complete overview of the industrial clus- often apply the analysis of academics or ter landscape in Canada. By doing so, spe consultants in order to determine the cific areas of strength are identified with presence of specific clusters within their- in the national economy. This knowledge jurisdictions, and to benchmark their can help to inform strategic investments performance relative to competing clus made by the public sector in areas such ters in other regions or countries. The as infrastructure, education and training,- model developed by Harvard business and research and innovation. Clusters strategist Michael Porter (1990) (1998) are broadly defined as sets of interre- (2003) provides the benchmark for the- lated industries, firms, and institutions, field, having been propagated by his which benefit from being in close phys- own company, as well as affiliated orga ical proximity. A well-established and nizations outside the United States. This- consistent quantitative methodology de approach has also been replicated and veloped by Spencer et al (2010) is used to adapted by many other consultants pro identify clusters in Canada. The report is viding similar analyses worldwide. data-driven and presents indictors such - as employment, growth, and incomes in The literature on clusters exists within a order to assess the relative performance much broader body of work on the rela- of each identified cluster. tionships between innovation processes- and geography, including clusters, in The remainder of this section provides- dustrial districts, local production sys an overview of the cluster concept, its- tems, and other similar concepts, which criticisms, and recent developments. Sec has been thoroughly reviewed in recent- tion 2 presents the methodology of iden years (Moulaert & Sekia, 2003; Simmie, tifying clusters in greater detail as well as 2005; Lagendijk, 2006). For the purpos explains the data sources and how they es of this report, the following discussion should be interpreted. The third section- focuses on the literature that is specific gives a national overview of the number to clusters. - of clusters identified by type and geogra - phy. Section 4 contains comparative data- Porter (1998) defines clusters as: geo on the 20 types of clusters identified. The graphic concentrations of interconnect- fifth section presents profiles of 32 spe ed companies, specialized suppliers, cific clusters that are intended to provide- service providers, firms in related in a comprehensive cross-section of cluster dustries, and associated institutions (for types and locations. The final section dis example, trade associations, universities, cusses overall cluster trends in Canada standards agencies) in a particular field and interprets them within a pro-active that compete but also cooperate. (pp. policy framework. 197–198) The fundamental theory of- 1.2 A brief survey of cluster theory clusters suggests that interrelated firms- and industries achieve a measure of com petitive advantage by being geographi cally concentrated in certain locations. There is now widespread understanding Economists have seized upon Marshall’s thatCluster the Atlas geographical of Canada clustering of related (1927) original beliefs on the nature of Page 5 2.2 Criticisms of the cluster concept - agglomeration economies by generally agreeing on three types of supply-side ex- ternalities that contribute to the growth Direct evidence of the tangible impact- of clusters. The sources of these external of clusters on economic growth remains •ities include: - somewhat scarce. Despite their wide spread popularity with policymakers,- large, deep pools of specialized la clusters pose challenges that make their bour generated by the concentration systematic identification and measure • of firms within related industries in- ment difficult. This difficulty in turn- the same location; contributes to scepticism with which the support that firms in the same in- cluster analyses and policy prescrip dustry illicit from a large number of tions are treated. Specific criticisms of • specialized local providers of inter- the cluster concept are articulated by mediate inputs and services; and, - (Martin & Sunley, 2003) and (Asheim, the positive technological externali et al., 2006), among others, who raise- ties or spillovers that flow more eas a number of conceptual and empirical ily among co-located firms than over questions about the validity of the clus- longer distances (Krugman, 1991; ter construct. For example, they note the Cortright, 2006). vague and inexact definition of the geo- - graphical extent of the cluster concept, The advantages enjoyed by firms in such noting that it is applied at a range of spa agglomerations include traditional exter tial scales. Moreover, they question the nal economies of scale, such as shared- extent to which the supposed beneficial physical infrastructure, in addition to- impact of clusters on firm innovativeness efficiency gains from reduced transac and regional economic performance has tion costs and access to specialized la been confirmed on a systematic basis- bour. Other advantages are based on across different locations and industries. the transfer of knowledge, including the Similarly, Wolfe and Gertler (2004) pro movement of skilled labour as well as vide empirical evidence that questions inter-firm collaboration and networking the universality of some of the standard (Porter, 1998). Clusters have also been claims made in the cluster literature, for widely adopted as a policy mechanism example, concerning local competition for economic development based on the- as a driver of firm performance (see also conviction that they provide a foundation (Breschi & Malerba, 2005)). Wolfe and- for economic growth for local and region Gertler conclude that national and local al economies. Furthermore, they have- contexts are central in shaping distinc attracted the attention of policy-makers- tive evolutionary trajectories that do based on the belief that public institu not necessarily conform to Porter’s US- tions and regulations have a strong in- based cluster norms. For this reason, it fluence on cluster dynamism, thereby makes little sense to apply a conceptual- having a discernible and measurable im and methodological framework – based pact on the prosperity of local economies as it is on the specificities of the Ameri- (Information Design Associates with ICF- can context – in other empirical settings Kaiser International, 1997; Organization without significant reflection, modifica for Economic Cooperation & Develop tion or adaptation. These critiques bring ment (OECD), 1999; Porter, et al., 2001; to the fore an inherent tension between- Andersson, et al., 2004). the desire to develop and implement a conceptual framework that has wide spread applicability (thereby facilitating Cluster Atlas of Canada Page 6 comparative analysis) and the need for - - an analytical approach that is sufficiently the Canadian context by the recent re- supple to accommodate regional and na- port published by the Toronto Board of tional variations in economic structure, Trade (2012) that compares the perfor- inter-sectoral relationships, and histori mance of selected city-regions with their cal context. American counterparts. The report heav 2.3 Recent developments on clusters ily relies on and promotes clusters as a- way forward to enhancing growth in the local economy. Also, in the Canadian con- text Spencer et al (2010) provides both a The cluster concept has endured and- detailed methodology and a clear evalua thrived despite criticisms that it is overly tion of the economic benefits of clusters- vague and difficult to implement in a sys to local economies. The methodology tematic manner. These criticisms have led addresses the distinct nature of the Ca to more detailed research that focuses on nadian economy and departs somewhat- better ways to identify clusters, analyse from the standard cluster definitions their impact, and recognize best practise. provided by Porter (discussed in great Notably, Muro and Katz (2010) from the er detail in the next section). Using this Brookings Institution outline what they methodology Spencer at al identified 263- believe to be a new ‘cluster moment’ by- individual clusters in Canada using data stating that recent research has added a from the 2001 Census and show that in- significant amount of validity to the con comes were nearly $10,000/year higher- cept. Furthermore, effective clusters are- in industries that are geographically clus tangible and ‘real’ initiatives that enable tered. This work helps to provide a com both public sector policy but also pri prehensive analytical framework for the vate sector strategies for innovation and analysis in this report. growth. This thinking is also reflected in

This section has been adpated from: Spencer, GM, Morales, J. and Wolfe, DA. 2012. Locating high growth firms within Ca- nadian industrial clusters. Industry Canada.

Cluster Atlas of Canada Page 7 2.0 Data & Methods 2.1 Cluster identification - - - analysis. The second step maps the geo graphic pattern of the remaining indus One of the difficulties of performing clus tries in order to determine which groups- ter analysis is developing a systematic- tend to commonly locate together in the- methodology for identifying when and same city-regions. At this point 19 clus where they occur. Different types of in- ter types (groups of 4-digit NAICS indus dustries cluster for different reasons in tries) are identified. Aluminium has been different places. The main goal of this re added at the behest of Industry Canada port is to look at the Canadian economy as- for the purpose of this report for a total a whole through a cluster lens. Thus, the of 20 cluster types. The third and final methodology adopted is broad and inclu step involves identifying the city-regions- sive in nature rather than tailored to any where each of these cluster types are one specific case. Specifically, this report strongly evident. Individual cases of clus uses the methodology created by Spencer ters are identified if they meet all three of et al (2010) as it is well established in the •the following criteria: academic literature and has been used in a number of policy reports for Industry • SCALE: the sum of local employment Canada, various Ontario Ministries, and must be greater than 1,000; other public sector institutions. It has the SPECIALIZATION: the percent share benefit of being comprehensive in terms- of local employment in the defined- of both industries and geography while industries must be greater than the taking into account the particular struc • percent share of these industries (lo ture of the Canada economy (as opposed cation quotient > 1); and, to Porter’s methodology which is based- SCOPE: the location quotient at least on the US economy). The methodology half of the component industries is based on geographic patterns co-loca must be greater than 1. tion of employment in specific industries- (4-digit NAICS) in Census Metropolitan- These criteria are relatively strict and- Areas (CMAs) and Census Agglomera are intentionally designed to segment tions (CAs) using the 2001 Census of Pop out only the strongest cases of cluster ulation and the 2011 National Household ing. The binary nature means that some Survey (NHS). Ideally the methodology industry groups in some places that just would also include input-output linkages- fall short of meeting the criteria will not as well as labour flows but these data are be included in the analysis but it should not available at the level of disaggrega not be interpreted that there is ‘nothing’ tion required for the detailed analysis to in such places. Applying these steps to follow. - the 2011 NHS results in the identification - of 225 cases of clusters in Canada. There are three main steps to the meth 2.2 Cluster indicators odology. The first is to isolate the in- dustries that display a propensity to be geographically ubiquitous. These indus tries tend to be things such as retail and Indicators are created for each identified local government that are correlated to cluster based on cross-tabulated data residential populations. They are also between the sets of 4-digit NIACS codes non-basic industries (non-exporting) and CMA/CA in which they are located. andCluster are Atlas therefore of Canada not of interest to the As such cross-tabulations are very finely Page 8 - grained they require very large datasets is able to opt out of their dataset but in order to populate them and thus, the reportedly few do so. The data is sup- scope of indicators is somewhat limited.- plemented and updated through direct The National Household Survey (NHS) is- inquiries from D&B to the firms them used for labour market indicators includ selves. This process is done on a rolling ing incomes, employment growth, demo basis and most firms are up-to-date with graphics of the labour force, educational- six months. attainment, and occupational structure. 2.4 How to read and interpret the re- Firm data is obtained from Dun & Brad sults steet including the precise locations of business and the number of employees - at each site. 2.3 Primary data sources The Spencer et al (2010) methodolo- gy was originally intended to assess the- overall impact of clustering within a Ca- - nadian context. Therefore, it is best suit The original cluster study by Spencer et ed to addressing similarly broad ques al (2010) used the 2001 Census of Popu- tions. While it is not intended for detailed lation to map out Canadian clusters. This- case-studies it can still be useful in this report relies on the NHS in the same man regard. The primary datasets are also ner but it must be noted that the differ large and universal and so best suited to- ences between the two pose a few issues. bigger questions. Using the NAICS system- One is that change between the 2001 and- is somewhat restrictive and there will al 2011 time periods cannot be measured ways be issues about what to include/ex exactly as the data come from differ clude. The methodology uses a common ent research instruments. The second is algorithm for all cluster types in order to that the response rates are inconsistent- maintain consistency. Each cluster type across geography (and likely industry) has core industries as well as secondary/ and so there is more data suppression is supportive industries that are included in sues with the NHS. In practical terms this- the definition. It is probable that some of means that smaller industries in smaller the individual firms but not all within the- city-regions (CAs) are likely undercount- secondary industries are actively related ed somewhat in this study. Further to the within each cluster. The potential draw- point smaller clusters in smaller city-re- back of using aggregate industry data is gions may be going unrecognized and the that the size of clusters can be overstat overall number of clusters is possibly un ed. Overall, the choice has been made to derreported. be broad and inclusive with definitions rather than narrow and restrictive and The firm level data is provided by Dun the reader should keep this in mind when & Bradstreet in the form of a universal interpreting the results of the analysis. file for 2011 (approximately 1.3 million firms) in order to coincide with the 2011 Census and NHS. D&B tracks all firms (and organizations) in all industries that- they find to be financially active. Much of their information is derived from finan cial transaction data (their core business- is credit rating) obtained from partner organizations. D&B claims that they cap Cluster Atlas of Canada Page 9 ture around 97-98% of firms. Any firm 3.0 National Overview - - - - Applying the Spencer et al (2010) meth need to be well-developed. While the for odology to the 2011 NHS led to the iden tunes of such clusters are highly depen tification of 230 clusters across 21 types dent on global commodity prices, efforts (please see Table 3.0.1). In describing the to innovate in processing and logistics- overall national picture, it is best to speak can reap rewards. Canada should be a in terms of resource, manufacturing, and world leader in this area due to its abun services clusters. - dance of resources. -

Resource clusters, which include agricul Manufacturing clusters tend to be locat ture, forestry, mining, and oil & gas tend ed in mid-sized city-regions in Southern to be found in smaller urban areas that Ontario and Quebec. These clusters are support large surrounding hinterlands. often closely linked with one another as- The location of such clusters follow a well as similar ones in the United States. relatively straightforward logic of being- Innovation is key to the long-term sur where the resources are. That being said vival of many of these clusters as global the necessary physical infrastructure re competition is intense. For relatively low Tablequired 3.0.1 to bring the resources to market knowledge intensive clusters such as Cluster Count by Type and Province NL PEI NS NB QC ON MB SK AB BC TOT Agriculture - - - - 5 9 1 1 1 2 19 Maritime 1 - 2 - - 1 - - - 4 8 Forestry & Wood - - - 2 4 1 - - - 11 18 Mining - - 1 1 3 4 1 2 2 2 16 Oil & Gas - - - - - 1 - 1 10 1 13 Construction - - - - - 1 - 1 9 11 22 Logistics - - - 1 1 6 - - 1 1 10 Textiles - - - - 1 2 1 - - - 4 Food & Beverage 1 - - 1 4 6 - - 1 2 15 Aluminum - - - - 3 - - - - - 3 Steel - - - - 3 9 - - 2 - 14 Automotive - - - - 3 16 - - - - 19 Plastics & Rubber - - - - 6 7 - - - - 13 Life Sciences - - - - 2 3 1 - - 1 7 Aerospace - - - - 1 - 1 - - - 2 ICT Manufacturing - - - - 2 6 - - 1 - 9 ICT Services - - - 2 1 2 - - 1 1 7 Finance - - - - 1 3 - - - 1 5 Business Services 1 - - 2 1 3 - - 1 2 10 Creative & Cultural - - - - 1 1 - - - 1 3 Higher Education 1 1 - 1 - 5 - 1 1 3 13 TOTAL 4 1 3 11 39 86 5 6 30 43 230

Cluster Atlas of Canada Page 10 - - textiles the future will depend on highly- provinces with the most clusters as they specialized niche firms. For more knowl possess the vast majority of manufac edge intensive clusters such as ICT man turing clusters as well as many resource- ufacturing strong innovation ecosystems- and services clusters (please see Figure need to be built and maintained. This 3.0.1). British Columbia (43) and Alber means the active management of linkag- ta (30) are next with the former home to- es between firms, universities, research many forestry & wood clusters and the labs, governments and various commu latter with oil & gas. These are the fast nity partners. - est growing areas of the country and thus- also have an abundance of construction The majority of service clusters are lo activity. The Atlantic Provinces gener cated in large urban areas. While many ally have a dearth of clusters as they do of these clusters have key anchor firms not possess either large city-regions or a they tend to have high numbers of small wealth of resources. firms as well as a significant amount of self-employment. Service clusters have- The fastest growing types of clusters are generally been faring well over the past generally in service-based industries or ten years showing clear patterns of em mining and oil & gas (please see Figure ployment growth. The health of these- 3.0.2). The latter two boast the highest- clusters is strongly tied to the health of average full-time employment incomes.- the urban environment in which they in Most of the types of manufacturing clus habit. Liveability factors are key and in- ters have seen employment declines be particular urban transportation systems tween 2001 and 2011. This trend has- are emerging as a major issue in the larg meant trouble for mid-sized urban areas- est urban areas in Canada. in Ontario and Quebec. It also under Figure 3.0.1 scores the general shift in economic out NationalOntario (86)Cluster and Count Quebec Map (39) are the put in Canada from east to west.

Cluster Atlas of Canada Page 11 Figure 3.0.2 100.0% Average Full-time

Incomes, Growth, Higher Education and Employment Oil & Gas by Cluster Type Construction 50.0% ICT Services Business Services Biomedical

Mining

Food & Beverage Logistics Finance

Agriculture 0.0% Maritime Aerospace Aluminum

Steel

Plastics & Rubber ICT Manufacturing

Forestry & Wood -50.0% Automotive

Percent employment 2001 - 2011 changeemployment Percent Textiles

-100.0% $40,000 $60,000 $80,000 $100,000 $120,000 $140,000 Average annual FT income, 2011

Note: Size of bubbles refers to number of employed persons

Cluster Atlas of Canada Page 12 4.0 Cluster Types -

This section provides general informa- tion about clusters according to type. Clusters are mapped by location and em ployment and differentiated by incomes and growth rates. These cluster types are groups of related 4-digit NAICS industries- identified by the Spencer et al (2010) methodology (see Appendix A for spe cific definitions). The exceptions to this are aerospace and aluminum which were added at the request of Industry Canada. These did not come out of the original methodology as they are not found to be systematically associated with additional industries. Part of the reason for this is that they are concentrated in only a few- locations (aerospace = 2; aluminum = 3) and are therefore somewhat special cas es in the Canadian context.

Cluster Atlas of Canada Page 13 4.1 Agriculture

140.0%

Lethbridge

100.0%

Drummondville

Brantford 60.0% Figure 4.1.1 Granby

Agriculture Brandon

Clusters Guelph Comparison 20.0% Victoriaville Saint-Jean-sur-Richelieu Kitchener - Cambridge - Waterloo Saint-ChilliwackHyacinthe

Employment 2001 - 2011 Change Employment Saskatoon Kawartha Lakes Abbotsford - Mission

-20.0% Chatham-Kent St. Catharines - Niagara Norfolk Leamington

-60.0% $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.1.2 Agriculture Cluster Map

Cluster Atlas of Canada Page 14 4.2 Maritime 40.0%

20.0%

Halifax St. Catharines - Niagara

Figure 4.2.1 Nanaimo Maritime 0.0%

Clusters Victoria Comparison Cape Breton Prince Rupert

Vancouver

Employment 2001 - 2011 Change Employment -20.0%

St. John's

-40.0% $40,000 $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.2.2 Maritime Cluster Map

Cluster Atlas of Canada Page 15 4.3 Forestry & Wood 20.0%

Saint John

0.0%

Quesnel Vernon Kelowna

-20.0% Edmundston Figure 4.3.1 Chilliwack Forestry & Wood Kamloops Prince George Clusters Dolbeau-Mistassini -40.0% Abbotsford - Mission Comparison Nanaimo Duncan Shawinigan Saguenay Employment 2001 - 2011 Change Employment

Campbell River -60.0% Williams Lake

Thunder Bay

-80.0% $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.3.2 Forestry & Wood Cluster Map

Cluster Atlas of Canada Page 16 4.4 Mining 100.0%

Bathurst

Rouyn-Noranda 75.0% Saskatoon

Regina

Kamloops

Edmonton 50.0% Val-d'Or Figure 4.4.1 Calgary Mining Clusters Greater Sudbury Timmins Comparison Thunder Bay 25.0% Thompson North Bay Prince George Employment 2001 - 2011 Change Employment

0.0% Sept-Îles

Cape Breton

-25.0% $50,000 $80,000 $110,000 $140,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.4.2 Mining Cluster Map

Cluster Atlas of Canada Page 17 4.5 Oil & Gas

140.0% Grande Prairie

100.0% Wood Buffalo Fort St. John

Edmonton Figure 4.5.1 Regina Oil & Gas 60.0% Lloydminster Clusters Calgary Comparison Red Deer Medicine Hat Employment 2001 - 2011 Change Employment 20.0%

Cold Lake Sarnia

-20.0% $50,000 $70,000 $90,000 $110,000 $130,000 $150,000 $170,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.5.2 Oil & Gas Cluster Map

Cluster Atlas of Canada Page 18 4.6 Construction 125.0% Courtenay

Saskatoon

100.0% Chilliwack

Nanaimo Kelowna Lethbridge 75.0% Penticton Edmonton Vernon Wood Buffalo Figure 4.6.1 Medicine Hat Construction Vancouver Clusters Kamloops Calgary Comparison 50.0% Grande Prairie Victoria

Red Deer

Employment 2001 - 2011 Change Employment Prince George

25.0%

Sarnia

0.0% $40,000 $60,000 $80,000 $100,000 $120,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.6.2 Construction Cluster Map

Cluster Atlas of Canada Page 19 4.7 Logistics 100.0%

Brantford

60.0%

Figure 4.7.1

Logistics Oshawa Kitchener - Cambridge - Clusters Waterloo

Comparison Calgary 20.0% Toronto Montréal Barrie Employment 2001 - 2011 Change Employment

Hamilton

Moncton Vancouver

-20.0% $45,000 $55,000 $65,000 $75,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.7.2 Logistics Cluster Map

Cluster Atlas of Canada Page 20 4.8 Textiles 20.0%

-20.0%

Figure 4.8.1 Logistics Toronto Clusters Comparison -60.0% Montréal Employment 2001 - 2011 Change Employment Winnipeg

Kitchener - Cambridge - Waterloo

-100.0% $40,000 $50,000 $60,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.8.2 Logistics Cluster Map

Cluster Atlas of Canada Page 21 4.9 Food & Beverage 120.0% Brantford

80.0%

Lethbridge

Figure 4.9.1 Abbotsford - Mission Food & Beverage 40.0% Granby

Clusters Vancouver Saint-Jean-sur-Richelieu Montréal Comparison Toronto

Saint-Hyacinthe Kitchener - Cambridge - Employment 2001 - 2011 Change Employment 0.0% Waterloo London Hamilton

Moncton St. John's

Belleville

-40.0% $40,000 $50,000 $60,000 $70,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.9.2 Food & Beverage Cluster Map

Cluster Atlas of Canada Page 22 4.10 Aluminum 125.0%

100.0% Sept-Îles

75.0%

50.0% Figure 4.10.1 Aluminum Clusters 25.0% Comparison

Employment 2001 - 2011 Change Employment 0.0% Baie-Comeau

-25.0% Saguenay

-50.0% $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 $110,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.10.2 Aluminum Cluster Map

Cluster Atlas of Canada Page 23 4.11 Steel 60.0%

40.0%

Edmonton Calgary

Drummondville 20.0% Oshawa

Figure 4.11.1 Steel 0.0% Clusters Trois-Rivières Comparison St. Catharines - Niagara Kitchener - Cambridge - Sorel-Tracy Sarnia -20.0% Waterloo

Employment 2001 - 2011 Change Employment Norfolk

Chatham-Kent -40.0% Brantford Hamilton

Windsor

-60.0% $40,000 $60,000 $80,000 $100,000 $120,000 $140,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.11.2 Steel Cluster Map

Cluster Atlas of Canada Page 24 4.12 Auto Manufacturing 40.0%

Woodstock

Guelph Granby Drummondville

0.0%

Kitchener - Cambridge - Figure 4.12.1 Waterloo London Barrie Sherbrooke Auto Norfolk Manufacturing Toronto Brantford Clusters Hamilton

Comparison -40.0% Stratford Windsor Employment 2001 - 2011 Change Employment Leamington Oshawa

Chatham-Kent St. Catharines - Niagara

-80.0% $40,000 $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.12.2 Auto Manufacturing Cluster Map

Cluster Atlas of Canada Page 25 4.13 Plastics & Rubber 30.0%

Drummondville Granby 15.0% Victoriaville

Belleville Brantford 0.0%

Figure 4.13.1 Trois-Rivières -15.0% Plastics & Rubber Sherbrooke Montréal Clusters Barrie Comparison Guelph -30.0% Toronto

Employment 2001 - 2011 Change Employment Oshawa

Kitchener - Cambridge - -45.0% Waterloo Oshawa

-60.0% $40,000 $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.13.2 Plastics & Rubber Cluster Map

Cluster Atlas of Canada Page 26 4.14 Life Sciences 60.0%

40.0%

Vancouver

Montréal Hamilton Winnipeg

Figure 4.14.1 Toronto Québec Life Sciences 20.0% Clusters Comparison Employment 2001 - 2011 Change Employment 0.0% Kitchener - Cambridge - Waterloo

-20.0% $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.14.2 Life Sciences Cluster Map

Cluster Atlas of Canada Page 27 4.15 Aerospace 20.0%

10.0%

0.0%

Figure 4.15.1 Aerospace -10.0% Winnipeg Montréal Clusters Comparison -20.0% Employment 2001 - 2011 Change Employment

-30.0%

-40.0% $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.15.2 Aerospace Cluster Map

Cluster Atlas of Canada Page 28 4.16 ICT Manufacturing 80.0%

60.0% Kitchener - Cambridge - Waterloo

40.0%

20.0% Figure 4.16.1 ICT Oshawa

Manufacturing 0.0% Hamilton Clusters Guelph Comparison Toronto Granby

Employment 2001 - 2011 Change Employment -20.0% Calgary

Montréal -40.0% Ottawa - Gatineau

-60.0% $40,000 $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.16.2 ICT Manufacturing Cluster Map

Cluster Atlas of Canada Page 29 4.17 ICT Services 60.0%

Moncton Fredericton

40.0% Toronto Montréal

Vancouver

Figure 4.17.1 Calgary ICT Services 20.0% Clusters Comparison

Employment 2001 - 2011 Change Employment 0.0% Ottawa - Gatineau

-20.0% $50,000 $60,000 $70,000 $80,000 $90,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.17.2 ICT Services Cluster Map

Cluster Atlas of Canada Page 30 4.18 Finance 60.0%

Oshawa

40.0% Toronto

Montréal

Hamilton

Figure 4.18.1 Vancouver Finance 20.0% Clusters Comparison

Employment 2001 - 2011 Change Employment 0.0%

-20.0% $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.18.2 Finance Cluster Map

Cluster Atlas of Canada Page 31 4.19 Business Services 60.0%

St. John's

40.0% Hamilton Montréal Vancouver Calgary

Victoria Toronto Figure 4.19.1 Business Services 20.0% Fredericton Clusters Comparison Moncton

Employment 2001 - 2011 Change Employment 0.0% Ottawa - Gatineau

-20.0% $40,000 $50,000 $60,000 $70,000 $80,000 $90,000 $100,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.19.2 Business Services Cluster Map

Cluster Atlas of Canada Page 32 4.20 Creative & Cultural 60.0%

40.0% Vancouver Toronto

Montréal

Figure 4.20.1 Creative & 20.0% Cultural Clusters Comparison

Employment 2001 - 2011 Change Employment 0.0%

-20.0% $50,000 $55,000 $60,000 $65,000 $70,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.20.2 Creative & Cultural Cluster Map

Cluster Atlas of Canada Page 33 4.21 Higher Education 120.0%

100.0%

Charlottetown Toronto 80.0%

Hamilton Edmonton Vancouver

60.0% St. John's Figure 4.21.1 Fredericton London Kingston Higher Education Saskatoon Clusters 40.0% Victoria Comparison

Ottawa - Gatineau

Employment 2001 - 2011 Change Employment 20.0%

0.0%

-20.0% $50,000 $60,000 $70,000 $80,000 Average FT Employment Income

Note: Size of bubbles refers to number of employed persons

Figure 4.21.2 Higher Education Cluster Map

Cluster Atlas of Canada Page 34 5.1 Atlantic Canada - -

There is a relative lack of clusters pres business services in St. John’s, Frederic- ent in the Atlantic Provinces. Much of this- ton, and St. John along with ICT services is due to the lack of larger urban areas. in Fredericton and Moncton. These clus Halifax is the largest CMA with a popu ters all grew significantly in employment lation of 390,000 which ranks it 13th in between 2001 and 2011 and provide- Canada. St. John’s is the next largest at relatively good incomes for the region. just under 200,000 which puts it in 20th- Higher education clusters in Charlotte place. Significant service clusters are not town, Fredericton, and St. John’s (Halifax likely to be well-developed in smaller cit narrowly misses meeting the criteria)- ies and the region does not have a strong- are key sources of human capital that tradition of manufacturing largely due to support the previously mentioned busi its lack of proximity to markets and sup ness services and ICT clusters. While ply chains. This leaves resource based the higher education clusters show very- clusters (fishing is included in maritime) rapid rates of growth, there are concerns which account for 7 of the 18 clusters on that the demographic picture in the At- the east coast. The majority of these have lantic Provinces will present problems in experienced employment declines in the the future in terms of providing a grow period between 2001 and 2011 (please ing supply of students. It is essential that- see Table 5.1.1). these provinces find ways of attracting and retaining immigrants in post-sec The relatively few bright spots include ondary education and beyond. Table 5.1.1 Atlantic Canada clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Fredericton NB Business Services 8,084 16.8% $61,927 Moncton NB Business Services 9,213 14.0% $46,581 St. John's NL Business Services 14,193 46.0% $66,535 Moncton NB Food & Beverage 3,036 -12.8% $40,977 St. John's NL Food & Beverage 2,937 -6.9% $47,189 Edmundston NB Forestry & Wood 1,028 -21.8% $57,738 Saint John NB Forestry & Wood 1,796 6.6% $88,377 Charlottetown PE Higher Education 2,066 92.2% $58,099 Fredericton NB Higher Education 3,939 49.5% $61,226 St. John's NL Higher Education 6,308 57.5% $68,350 Fredericton NB ICT Services 4,785 48.4% $63,166 Moncton NB ICT Services 4,152 45.4% $56,048 Moncton NB Logistics 5,061 0.9% $49,908 Cape Breton NS Maritime 2,053 -8.3% $49,434 Halifax NS Maritime 3,300 12.4% $60,905 St. John's NL Maritime 1,728 -28.1% $74,270 Bathurst NB Mining 1,363 91.9% $95,174 Cape Breton NS Mining 1,024 -23.0% $64,211

Cluster Atlas of Canada Page 35 5.1.1 St. John’s Food & Beverage -

The food & beverage cluster in St. John’s em- cluster 8th out of 15 food & beverage clusters ployed 2,937 people in 2011. This made St. in Canada. John’s the 8th largest food & beverage clus ter in Canada (out of 15). Between 2001- In 2011 Dun & Bradstreet identified 124- and 2011 employment shrank by 6.9%. The business establishments in the St. John’s food labour force was 71.6% male and 28.4% fe & beverage cluster. The average establish- male. 42.6% of the labour force was over the ment size was 29 employees. Key firms of at age of 44. least 100 employees in 2011 included: Quin lan Brothers Limited; Country Ribbon Inc;- In 2011 39.1% of the cluster labour force Ocean Choice International L.P.; Barry Group held post-secondary qualifications with Inc; Labrador Sea Products Inc; Molson Can- 6.7% having a university degree. ada; Furlong Brothers Limited; Independent Dockside Grading Inc; Labatt Brewing Com According to the 2011 NHS the average full- pany Limited. time employment income for individuals working in the St. John’s food & beverage cluster was $47,189 per year. This ranked the Figure 5.1.1.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 36 5.1.1 St. John’s Food & Beverage 35.0%

30.0% Females, 28.4%

25.0%

Figure 5.1.1.2 20.0% Labour force Males, 71.6% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 6.7% No Degree, 16.0%

Figure 5.1.1.3 College & Trades, Educational 32.4% attainment of labour force, 2011

High School, 44.8%

Management (NOC 0), 9.4%

Manuacturing & Finance & Admin Utilities (NOC 9), (NOC 1), 10.1% 30.3%

Science & Tech (NOC 2), 0.7% Figure 5.1.1.4 Occupational structure of labour force, 2011

Trades & Transport Sales & Service (NOC 7), 15.3% (NOC 6), 34.1%

Cluster Atlas of Canada Page 37 5.1.2 St. John’s Business Services -

The business services cluster in St. John’s cluster 7th out of 10 business services clus employed 14,193 people in 2011. This made ters in Canada. St. John’s the 8th largest business services cluster in Canada (out of 10). Between 2001- In 2011 Dun & Bradstreet identified 1,017- and 2011 employment grew by 46%. The business establishments in the St. John’s labour force was 56.5% male and 43.5% fe business services cluster. The average estab male. 42% of the labour force was over the lishment size was 11 employees. The largest age of 44. firms in core business services industries in- 2011 included: Shannahan’s Investigation In 2011 81.1% of the cluster labour force Security Limited; Fortis Properties Corpo- held post-secondary qualifications with ration; Canadian Corps Of Commissionaires 42.4% having a university degree. (Newfoundland); Amec Inc; Production Ser vices Network Canada Inc; The Responsive According to the 2011 NHS the average full- Marketing Group Inc.; Cabot Call Centre; Call time employment income for individuals Centre Inc; Oceaneering Canada Limited; working in the St. John’s business services John C Crosbie P.C. O.C. Q.C.; SNC-Lavalin Inc. cluster was $66,535 per year. This ranked the Figure 5.1.2.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 38 5.1.2 St. John’s Business Services 30.0%

25.0%

Females, 43.5% 20.0% Males, 56.5% Figure 5.1.2.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 3.3%

High School, 15.6%

Figure 5.1.2.3 University, 42.4% Educational attainment of labour force, 2011

College & Trades, 38.7%

Trades & Transport Management (NOC (NOC 7), 3.9% 0), 7.5%

Sales & Service (NOC 6), 16.6%

Finance & Admin (NOC 1), 21.6%

Figure 5.1.2.4 Creative & Cultural Occupational (NOC 5), 2.6% structure of labour force, 2011

Education, Law & Gov. (NOC 4), 20.8%

Science & Tech (NOC 2), 24.3% Health (NOC 3), 1.8%

Cluster Atlas of Canada Page 39 5.1.3 Charlottetown Higher Education - -

The higher education cluster in Charlotte ranked the cluster 13th out of 13 higher edu town employed 2,066 people in 2011. This- cation clusters in Canada. - made Charlottetown the 13th largest higher education cluster in Canada (out of 13). Be In 2011 Dun & Bradstreet identified 51 busi- tween 2001 and 2011 employment grew by ness establishments in the Charlottetown- 92.2%. The labour force was 41.9% male and higher education cluster. The average estab- 58.1% female. 52.3% of the labour force was lishment size was 31 employees. The Univer over the age of 44. sity of Prince Edward Island and Holland Col lege were the two main employers in 2011. In 2011 78% of the cluster labour force held post-secondary qualifications with 58.8% having a university degree.

According to the 2011 NHS the average full-- time employment income for individuals working in the Charlottetown higher edu cation cluster was $58,099 per year. This Figure 5.1.3.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 40 5.1.3 Charlottetown Higher Education 40.0%

35.0%

30.0% Males, 41.9%

25.0% Females, 58.1% Figure 5.1.3.2 Labour force 20.0% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 1.0%

High School, 21.0%

Figure 5.1.3.3 Educational attainment of labour force, 2011

University, 58.8% College & Trades, 19.2%

Sales & Service Management (NOC (NOC 6), 9.7% 0), 6.1%

Finance & Admin (NOC 1), 15.0% Creative & Cultural (NOC 5), 13.9%

Figure 5.1.3.4 Science & Tech Occupational (NOC 2), 3.1% structure of Health (NOC 3), labour force, 2011 4.2%

Education, Law & Gov. (NOC 4), 48.1% Cluster Atlas of Canada Page 41 5.1.4 Halifax Maritime

- The maritime cluster in Halifax employed In 2011 Dun & Bradstreet identified 109 3,300 people in 2011. This made Halifax the business establishments in the Halifax mar 3rd largest maritime cluster in Canada (out itime cluster. The average establishment size of 8). Between 2001 and 2011 employment was 25 employees. The largest firms in core grew by 12.4%. The labour force was 75.6% maritime industries in 2011 included: Ultra male and 24.4% female. 50.8% of the labour Electronics Canada Inc; Clearwater Seafoods force was over the age of 44. Income Fund; Irving Shipbuilding Inc; - Halterm Limited; Northern Transportation- In 2011 62.8% of the cluster labour force Company Limited; Atlantic Pilotage Author held post-secondary qualifications with ity; Bakers Point Fisheries Limited; and Hali 17.4% having a university degree. fax Port Authority.

According to the 2011 NHS the average full- time employment income for individuals working in the Halifax maritime cluster was $60,905 per year. This ranked the cluster 4th out of 8 maritime clusters in Canada. Figure 5.1.4.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 42 5.1.4 Halifax Maritime 35.0%

Females, 30.0% 24.4%

25.0%

Figure 5.1.4.2 20.0% Labour force Males, 75.6% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 13.2% University, 17.4%

Figure 5.1.4.3 Educational attainment of High School, 24.0% labour force, 2011

College & Trades, 45.5%

Manuacturing & Management (NOC Utilities (NOC 9), 0), 7.6% 10.7%

Finance & Admin (NOC 1), 10.8%

Natural Resources (NOC 8), 16.0% Figure 5.1.4.4 Occupational Science & Tech structure of (NOC 2), 12.3% labour force, 2011

Education, Law & Gov. (NOC 4), 1.1%

Creative & Cultural (NOC 5), 5.8%

Sales & Service (NOC 6), 3.1% Trades & Transport (NOC 7), 32.5%

Cluster Atlas of Canada Page 43 5.1.5 Cape Breton Mining - - - The mining cluster in Cape Breton employed In 2011 Dun & Bradstreet identified 10 busi 1,024 people in 2011. This made Cape Bret- ness establishments in the Cape Breton min on the 16th largest mining cluster in Canada ing cluster. The average establishment size (out of 16). Between 2001 and 2011 employ was 50 employees. The largest firms in core ment declined by 23%. The labour force was mining industries in 2011 were Nova Scotia 90.2% male and 9.8% female. 52.6% of the Power Incorporated and Municipal Capital labour force was over the age of 44. Incorporated.

In 2011 79.1% of the cluster labour force held post-secondary qualifications with 4.1% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals- working in the Cape Breton mining cluster was $64,211 per year. This ranked the clus ter 16th out of 16 mining clusters in Canada. Figure 5.1.5.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 44 5.1.5 Cape Breton Mining 35.0% Females, 9.8% 30.0%

25.0%

Figure 5.1.5.2 20.0% Labour force demographics, 2011 15.0% Males, 90.2% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.0% University, 4.1%

High School, 18.9%

Figure 5.1.5.3 Educational attainment of labour force, 2011

College & Trades, 75.0%

Manuacturing & Management (NOC Utilities (NOC 9), 0), 3.4% Finance & Admin 9.6% (NOC 1), 4.5% Science & Tech (NOC 2), 5.1%

Sales & Service (NOC 6), 3.9% Natural Resources (NOC 8), 15.7%

Figure 5.1.5.4 Occupational structure of labour force, 2011

Trades & Transport (NOC 7), 57.9%

Cluster Atlas of Canada Page 45 5.1.6 Moncton Logistics -

The logistics cluster in Moncton employed In 2011 Dun & Bradstreet identified 53 busi 5,061 people in 2011. This made Moncton- ness establishments in the Moncton logistics- the 9th largest logistics cluster in Canada cluster. The average establishment size was (out of 10). Between 2001 and 2011 employ 19 employees. The largest firms in core lo ment grew by 0.9%. The labour force was gistics industries in 2011 included: Canada 66.9% male and 33.1% female. 47.2% of the Post Corporation; Matrix Logistics Services- labour force was over the age of 44. Limited; Day & Ross Inc; Midland Transport Limited; Coca-Cola Bottling Company; Ar In 2011 54.4% of the cluster labour force mour Transport Inc; and Greater Moncton held post-secondary qualifications with International Airport Authority. 10.0% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Moncton logistics cluster was $49,908 per year. This ranked the cluster 10th out of 10 logistics clusters in Canada. Figure 5.1.6.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 46 5.1.6 Moncton Logistics 35.0%

30.0% Females, 33.1% 25.0%

20.0% Figure 5.1.6.2 Males, Labour force 66.9% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 8.3% University, 10.0%

Figure 5.1.6.3 Educational attainment of labour force, 2011 High School, 37.3%

College & Trades, 44.4%

Manuacturing & Utilities (NOC 9), Management (NOC 0), 10.4% Trades & Transport 1.3% (NOC 7), 17.3%

Figure 5.1.6.4 Occupational structure of Finance & Admin (NOC 1), 30.8% labour force, 2011

Sales & Service (NOC 6), 32.3%

Science & Tech (NOC 2), 7.9%

Cluster Atlas of Canada Page 47 5.1.7 Fredericton ICT Services -

The ICT services cluster in Fredericton em cluster 6th out of 7 ICT services clusters in ployed 4,785 people in 2011. This made Canada. Fredericton the 6th largest ICT services cluster in Canada (out of 7). Between 2001- In 2011 Dun & Bradstreet identified 102- and 2011 employment grew by 48.4%. The business establishments in the Fredericton labour force was 62.7% male and 37.3% fe ICT services cluster. The average establish male. 36.2% of the labour force was over the ment size was 35 employees. The largest- age of 44. firms in core ICT services industries in 2011 included: Cendant Canada Inc; Universal Sys In 2011 83.5% of the cluster labour force tems Ltd; Provinent Corp; Groupe CGI Inc; held post-secondary qualifications with Bell Aliant Regional Communications Inc; 58.6% having a university degree. Astral Media Radio Atlantic Inc; and Unisys Canada Inc.. According to the 2011 NHS the average full-- time employment income for individuals working in the Fredericton ICT services clus ter was $63,166 per year. This ranked the Figure 5.1.7.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 48 5.1.7 Fredericton ICT Services 30.0%

25.0% Females, 37.3%

20.0%

Males, Figure 5.1.7.2 62.7% Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.0%

High School, 14.4%

Figure 5.1.7.3 Educational attainment of labour force, 2011 College & Trades, 24.9% University, 58.6%

Trades & Transport Management (NOC Sales & Service (NOC 7), 2.4% 0), 11.9% (NOC 6), 10.3%

Creative & Cultural (NOC 5), 5.6% Finance & Admin (NOC 1), 13.2%

Figure 5.1.7.4 Occupational structure of labour force, 2011

Education, Law & Gov. (NOC 4), 31.2% Science & Tech (NOC 2), 25.0%

Health (NOC 3), 0.3% Cluster Atlas of Canada Page 49 5.2 Québec

- Québec has a wide range of clusters and makers as the largest cities tend to be is third to Ontario (86) and British Co- the primary drivers of this growth. A gap lumbia (43) with 39. Of these clusters 12 is emerging with mid-sized and smaller are focused in resources with five agri urban areas that have economies with culture, four forestry & wood, and three resource and manufacturing histories.- mining. The mining clusters provide Attempts to geographically spread such the highest incomes and two of three growth is not likely to succeed, yet small (Rouyn-Noranda and Val-d’Or) have seen er communities need to find ways to be significant growth between 2001 and prosperous in the 21st century global 2011. The forestry & wood clusters have- economy. experienced the greatest difficulty over this period with three of four losing sig nificant amounts of jobs.

Québec is the only province to report at- least one cluster of each manufacturing type suggesting that there is a broadly di versified industrial base. Aluminum and aerospace are specific specializations- that Québec possesses that are limited in the rest of Canada. All four food & bev erage clusters experienced employment growth between 2001 and 2011. The results for plastics & rubber (6), auto manufacturing (3), aluminum (3), steel- (3) were mixed on this measure. For the more knowledge intensive manufactur ing clusters ICT (2) reported significant declines although this can be attributed to the timeframe and the results of the dot-com crash in the early 2000s. The two life sciences (Montréal and Québec) both grew by about 25%. - All four of the Québec services clusters- are located in Montréal. All four, includ- ing ICT services, finance, business ser vices, and creative and cultural experi enced growth of around a third between- 2001 and 2011. This trend is in line with similar clusters in the other major ur ban areas of the country. It exemplifies- the overall trend of employment shifts to service industries (and away from man- ufacturing). While this may provide an aggregate benefit to the economy it pos esCluster somewhat Atlas of Canada of a conundrum for policy Page 50 Table 5.2.1 Quebec clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Montréal QC Aerospace 24,390 -8.4% $72,786 Drummondville QC Agriculture 4,525 83.6% $35,970 Granby QC Agriculture 2,836 57.1% $52,203 Saint-Hyacinthe QC Agriculture 2,863 2.1% $42,169 Saint-Jean-sur-Richelieu QC Agriculture 2,061 8.7% $42,025 Victoriaville QC Agriculture 1,925 8.2% $39,942 Saguenay QC Aluminum 3,687 -27.9% $87,418 Baie-Comeau QC Aluminum 1,621 -7.7% $78,210 Sept-Îles QC Aluminum 1,137 92.6% $96,230 Drummondville QC Automotive 2,157 12.3% $41,529 Granby QC Automotive 2,309 12.9% $41,783 Sherbrooke QC Automotive 3,332 -21.1% $47,832 Montréal QC Life Sciences 31,436 26.1% $69,624 Québec QC Life Sciences 5,542 24.0% $62,815 Montréal QC Business Services 235,300 34.4% $64,886 Montréal QC Creative & Cultural 94,427 31.8% $55,215 Montréal QC Finance 137,348 29.8% $67,867 Granby QC Food 2,421 46.3% $44,569 Montréal QC Food 56,946 9.1% $48,374 Saint-Hyacinthe QC Food 2,461 5.9% $41,781 Saint-Jean-sur-Richelieu QC Food 1,739 19.9% $44,074 Dolbeau-Mistassini QC Forestry 1,023 -31.8% $62,427 Saguenay QC Forestry 1,695 -49.5% $64,648 Saint-Georges QC Forestry 1,242 46.9% $39,768 Shawinigan QC Forestry 1,254 -44.9% $58,945 Granby QC ICT Manufacturing 2,547 -19.5% $48,253 Montréal QC ICT Manufacturing 25,341 -37.5% $66,828 Montréal QC ICT Services 133,473 32.0% $66,403 Montréal QC Logistics 131,793 8.2% $58,611 Rouyn-Noranda QC Mining 2,964 72.3% $79,237 Sept-Îles QC Mining 1,247 -5.5% $95,246 Val-d'Or QC Mining 2,593 52.1% $86,253 Drummondville QC Plastics & Rubber 2,586 17.5% $43,829 Granby QC Plastics & Rubber 2,086 14.3% $41,530 Montréal QC Plastics & Rubber 46,866 -26.8% $49,593 Sherbrooke QC Plastics & Rubber 3,789 -20.2% $45,009 Trois-Rivières QC Plastics & Rubber 1,402 -9.5% $46,627 Victoriaville QC Plastics & Rubber 1,152 14.1% $44,687 Drummondville QC Steel 1,354 27.1% $45,308 Sorel-Tracy QC Steel 1,930 -25.3% $70,903 Trois-Rivières QC Steel 2,222 -15.0% $80,992 Montréal QC Textiles 25,106 -60.5% $45,039

Cluster Atlas of Canada Page 51 5.2.1 Saguenay Aluminum - - The aluminum cluster in Saguenay employed In 2011 Dun & Bradstreet identified 20 busi 3,687 people in 2011. This made Saguenay ness establishments in the Saguenay alumi the largest aluminum cluster in Canada (out num cluster. The average establishment size of 3). Between 2001 and 2011 employment was 134 employees. The largest firms in core declined by 27.9%. The labour force was aluminum industries in 2011 included: Rio 90.0% male and 10.0% female. 63.9% of the Tinto Alcan Inc; Alfiniti Inc; Spectube Inc; labour force was over the age of 44. Novelis Inc; and Fonderie Saguenay Ltée.

In 2011 84.8% of the cluster labour force held post-secondary qualifications with 18.0% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Saguenay aluminum cluster was $87,418 per year. This ranked the cluster 2nd out of 3 aluminum clusters in Canada. Figure 5.2.1.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 52 5.2.1 Saguenay Aluminum 45.0% Females, 10.0% 40.0%

35.0%

30.0%

Figure 5.2.1.2 25.0% Labour force demographics, 2011 20.0% Males, 90.0% Percent ofPercentlabour force 15.0%

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 4.1%

High School, 11.1% University, 18.0%

Figure 5.2.1.3 Educational attainment of labour force, 2011

College & Trades, 66.8% Management (NOC 0), 5.9% Finance & Admin (NOC 1), 8.9%

Manuacturing & Utilities (NOC 9), Figure 5.2.1.4 42.2% Science & Tech Occupational (NOC 2), 15.4% structure of labour force, 2011

Education, Law & Gov. (NOC 4), 1.6% Sales & Service (NOC 6), 2.3%

Trades & Transport (NOC 7), 23.6%

Cluster Atlas of Canada Page 53 5.2.2 Rouyn-Noranda Mining - -

The mining cluster in Rouyn-Noranda em- cluster 13th out of 16 mining clusters in Can ployed 2,964 people in 2011. This made ada. - Rouyn-Noranda the 6th largest mining clus ter in Canada (out of 16). Between 2001 and- In 2011 Dun & Bradstreet identified 42 busi 2011 employment increased by 72.3%. The ness establishments in the Rouyn-Noranda labour force was 83.7% male and 16.3% fe mining cluster. The average establishment male. 43.6% of the labour force was over the size was 54 employees. The largest firms age of 44. in core mining industries in 2011 included: Xstrata Canada Corporation; Agnico-Eagle- In 2011 66.3% of the cluster labour force Mines Limited; Les Mines D’Argent ECU Inc; held post-secondary qualifications with Gestion Iamgold-Québec Inc; Services d’En 12.7% having a university degree. tretien Miniers Industriels R.N. 2000; and Bradley Frères Ltée. According to the 2011 NHS the average full-- time employment income for individuals working in the Rouyn-Noranda mining clus ter was $79,237 per year. This ranked the Figure 5.2.2.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 54 5.2.2 Rouyn-Noranda Mining 35.0% Females, 16.3% 30.0%

25.0%

Figure 5.2.2.2 20.0% Labour force demographics, 2011 15.0% Males, 83.7% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 12.7% No Degree, 21.8%

Figure 5.2.2.3 Educational attainment of labour force, 2011 High School, 12.0%

College & Trades, 53.6%

Manuacturing & Management (NOC Utilities (NOC 9), 0), 2.8% 4.4% Finance & Admin (NOC 1), 12.8%

Natural Resources Figure 5.2.2.4 (NOC 8), 33.0% Occupational Science & Tech structure of (NOC 2), 19.1% labour force, 2011

Education, Law & Gov. (NOC 4), 2.0% Sales & Service (NOC 6), 3.9%

Trades & Transport (NOC 7), 22.0% Cluster Atlas of Canada Page 55 5.2.3 Québec Life Sciences

The life sciences cluster in Québec employed In 2011 Dun & Bradstreet identified 189 5,542 people in 2011. This made Québec the- business establishments in the Québec life 4th largest life sciences cluster in Canada sciences cluster. The average establishment- (out of 7). Between 2001 and 2011 employ size was 14 employees. The largest firms in ment increased by 24.0%. The labour force core life sciences industries in 2011 includ was 53.0% male and 47.0% female. 31.8% of ed: Olympus NDT Canada Inc; ABB-Bomem the labour force was over the age of 44. Inc; GeneOhm Sciences Canada Inc; General- Electric Canada Company; Pharmalab Inc; In 2011 83.6% of the cluster labour force Multitel Inc; Orthofab Inc; Optel-Technolo held post-secondary qualifications with gies Inc; Laboratoire Dentaire Morisset Inc; 37.5% having a university degree. and DiagnoCure Inc..

According to the 2011 NHS the average full- time employment income for individuals working in the Québec life sciences cluster was $62,815 per year. This ranked the cluster 6th out of 7 life sciences clusters in Canada. Figure 5.2.3.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 56 5.2.3 Québec Life Sciences 35.0%

30.0%

25.0% Females, Males, 47.0% 53.0% Figure 5.2.3.2 20.0% Labour force demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 3.1%

High School, 13.3%

University, 37.5% Figure 5.2.3.3 Educational attainment of labour force, 2011

College & Trades, 46.2%

Manuacturing & Management (NOC Utilities (NOC 9), 0), 9.0% 11.1%

Trades & Transport (NOC 7), 5.4% Finance & Admin (NOC 1), 16.0%

Figure 5.2.3.4 Occupational

structure of Sales & Service labour force, 2011 (NOC 6), 19.3%

Education, Law & Gov. (NOC 4), 2.3% Science & Tech (NOC 2), 24.4%

Health (NOC 3), 12.5%

Cluster Atlas of Canada Page 57 5.2.4 Montréal Finance

- The finance cluster in Montréal employed In 2011 Dun & Bradstreet identified 6,263 137,348 people in 2011. This made Montréal- business establishments in the Montréal fi the 2nd largest finance cluster in Canada nance cluster. The average establishment- (out of 5). Between 2001 and 2011 employ size was 16 employees. The largest firms ment increased by 29.8%. The labour force in core finance industries in 2011 includ was 44.0% male and 56.0% female. 41.8% of ed: RBC; Bank of Montréal; Fédération Des- the labour force was over the age of 44. Caisses Desjardins Du Québec; Financière Banque Nationale & Cie Inc; Sun Life Assur In 2011 79.5% of the cluster labour force ance Company Of Canada; Sécurité Nationale- held post-secondary qualifications with Compagnie D’Assurance; Valeurs Mobilieres 42.4% having a university degree. Desjardins Inc; Les Associés Services Finan ciers du Canada Ltée; Banque Laurentienne According to the 2011 NHS the average full- Du Canada; Power Financial Corporation; time employment income for individuals Ernst & Young Inc; INTRIA Items Inc; The working in the Montréal finance cluster was Manufacturers Life Insurance Company; and $67,867 per year. This ranked the cluster 5th Ernst & Young LLP. out of 5 finance clusters in Canada. Figure 5.2.4.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 58 5.2.4 Montréal Finance 30.0%

25.0%

Males, 44.0% 20.0% Females, 56.0% Figure 5.2.4.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.9%

High School, 17.6%

Figure 5.2.4.3 University, 42.4% Educational attainment of labour force, 2011

College & Trades, 37.2%

Trades & Transport (NOC 7), 2.5% Management (NOC 0), 14.9%

Sales & Service (NOC 6), 21.7%

Figure 5.2.4.4 Occupational

structure of Creative & Cultural labour force, 2011 (NOC 5), 3.9% Education, Law & Gov. (NOC 4), 2.1%

Science & Tech (NOC 2), 7.4%

Finance & Admin (NOC 1), 47.1%

Cluster Atlas of Canada Page 59 5.2.5 Montréal Creative & Cultural -

The creative & cultural cluster in Montréal cluster 3rd out of 3 creative & cultural clus employed 94,427 people in 2011. This made ters in Canada. Montréal the 2nd largest creative & cultural - cluster in Canada (out of 3). Between 2001 In 2011 Dun & Bradstreet identified 7,059- and 2011 employment increased by 31.8%. business establishments in the Montréal cre The labour force was 51.6% male and 48.4% ative & cultural cluster. The average estab female. 35.5% of the labour force was over lishment size was 9 employees. The largest- the age of 44. firms in core creative & cultural industries in 2011 included: Canadian Broadcasting Cor In 2011 80.7% of the cluster labour force poration; Académie de Coiffure Laval Inc; held post-secondary qualifications with Cirque Du Soleil Inc; L’ Arena des Canadiens- 40.5% having a university degree. Inc; L-3 Communications MAS (Canada) Inc; Bellevue Pathe Holdings Ltd; Zone3 Inc; Cos According to the 2011 NHS the average full- sette Inc; Corus Entertainment Inc; Cogeco time employment income for individuals Inc; and Astral Media Inc. working in the Montréal creative & cultural cluster was $55,215 per year. This ranked the Figure 5.2.5.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 60 5.2.5 Montréal Creative & Cultural 35.0%

30.0%

25.0% Females, Males, 48.4% 51.6% Figure 5.2.5.2 20.0% Labour force demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 4.3%

High School, 15.0%

Figure 5.2.5.3 University, 40.5% Educational attainment of labour force, 2011

College & Trades, 40.2%

Trades & Transport Management (NOC Sales & Service (NOC 7), 2.2% 0), 11.8% (NOC 6), 8.8%

Finance & Admin (NOC 1), 17.6% Figure 5.2.5.4 Occupational structure of labour force, 2011

Creative & Cultural (NOC 5), 41.3% Science & Tech (NOC 2), 8.9%

Education, Law & Gov. (NOC 4), 8.3%

Cluster Atlas of Canada Page 61 5.3 Ontario -

Ontario has the most clusters of any- The related pattern is that new employ province with 86 in total. They are also ment opportunities are being creating quite varied by type with 16 in resourc predominantly in the largest cities. This- es, 49 in manufacturing, 14 in services, poses a problem for many of the smaller as well as 7 in construction and logistics.- and mid-sized urban areas, particular Mining in the north and agriculture in ly in the southwest of the province, that- the south make up the majority of the re are seeing their industrial base erode. source clusters. The four mining clusters It is not clear what types of jobs will re in Ontario experienced healthy growth place the ones being lost to automation rates between 2001 and 2011 while the and off-shoring. Pitfalls exist with trying agriculture clusters show mixed results. to retain manufacturing employment just - as they exist with trying to compete with- Manufacturing remains a very important big cities for service industry jobs. Such part of the Ontario economy. In particu- places must navigate this issues with de lar auto manufacturing is the backbone termination if they are to prosper going of many local economies, particular forward. ly from the GTA to the southwest of the- province. The methodology identified 16 auto manufacturing clusters in On tario. Worryingly the vast majority of- these endured significant employment decline between 2001 and 2011. The pic ture was fairly similar for the nine steel- clusters in the province as well as the seven plastics & rubber clusters. The pic- ture was somewhat better for the more knowledge intensive manufacturing clus- ters. The Kitchener-Waterloo ICT cluster grew rapidly between 2001 and 2011 al though the Ottawa-Gatineau and Toronto clusters declined. This is likely due to the relative performance of key anchor firms- in each instance. Life sciences performed somewhat better with two of three (To ronto and Hamilton) growing by roughly 25%. -

There were 14 service clusters identi fied in Ontario. These clusters tend to be large, rapidly growing and located in the major urban centres. The only service- cluster to experience decline between 2001 and 2011 was ICT in Ottawa-Gatin- eau, and this was a marginal amount at 3.4%. As with Québec there is a fair ly clear pattern of overall employment shiftingCluster Atlas from of Canada manufacturing to services. Page 62 Table 5.3.1 Ontario clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Brantford ON Agriculture 3,377 62.4% $49,878 Centre Wellington ON Agriculture 1,387 NA $44,343 Chatham-Kent ON Agriculture 5,330 -14.4% $45,912 Guelph ON Agriculture 3,149 28.3% $55,343 Kawartha Lakes ON Agriculture 2,147 -7.1% $24,777 Kitchener - Waterloo ON Agriculture 9,449 0.3% $55,159 Leamington ON Agriculture 3,844 -35.9% $43,831 Norfolk ON Agriculture 4,498 -31.3% $33,878 St. Catharines - Niagara ON Agriculture 7,780 -22.4% $45,830 Barrie ON Automotive 5,005 -23.2% $64,036 Brantford ON Automotive 3,508 -27.4% $58,649 Chatham-Kent ON Automotive 3,324 -63.9% $55,117 Guelph ON Automotive 7,238 14.5% $63,528 Hamilton ON Automotive 10,523 -35.3% $66,351 Ingersoll ON Automotive 1,065 NA $68,965 Kitchener - Waterloo ON Automotive 16,861 -23.8% $58,466 Leamington ON Automotive 1,805 -45.0% $64,623 London ON Automotive 11,326 -27.0% $62,539 Norfolk ON Automotive 1,611 -23.8% $52,828 Oshawa ON Automotive 8,170 -49.1% $70,554 St. Catharines - Niagara ON Automotive 6,608 -52.3% $66,318 Stratford ON Automotive 1,947 -42.1% $52,140 Toronto ON Automotive 75,280 -26.9% $62,675 Windsor ON Automotive 19,902 -45.0% $68,114 Woodstock ON Automotive 2,871 29.3% $62,377 Hamilton ON Life Sciences 4,021 31.4% $76,883 Kitchener - Waterloo ON Life Sciences 2,522 -1.7% $66,334 Toronto ON Life Sciences 43,810 23.1% $72,704 Hamilton ON Business Services 37,150 37.3% $68,709 Ottawa - Gatineau ON Business Services 80,365 0.6% $75,758 Toronto ON Business Services 378,458 29.1% $79,178 Sarnia ON Construction 2,057 12.1% $84,638 Toronto ON Creative & Cultural 158,249 37.8% $64,115 Hamilton ON Finance 25,357 27.4% $77,065 Oshawa ON Finance 12,884 47.3% $76,458 Toronto ON Finance 307,963 35.6% $89,388 Belleville ON Food & Beverage 1,400 -23.7% $45,449 Brantford ON Food & Beverage 2,804 103.2% $46,263 Hamilton ON Food & Beverage 11,138 -3.9% $65,406 Kitchener - Waterloo ON Food & Beverage 9,494 15.1% $52,296 London ON Food & Beverage 6,972 -5.0% $48,513 Toronto ON Food & Beverage 94,010 23.3% $57,230 Thunder Bay ON Forestry & Wood 1,706 -67.0% $65,795

Cluster Atlas of Canada Page 63 Table 5.3.1 Ontario clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Hamilton ON Higher Education 13,894 68.3% $67,821 Kingston ON Higher Education 8,165 51.5% $71,435 London ON Higher Education 11,987 50.4% $68,259 Ottawa - Gatineau ON Higher Education 30,389 20.8% $74,893 Toronto ON Higher Education 106,354 85.8% $70,429 Guelph ON ICT Manufacturing 1,361 -15.7% $71,938 Hamilton ON ICT Manufacturing 4,486 -5.9% $72,803 Kitchener - Waterloo ON ICT Manufacturing 11,371 58.7% $76,933 Oshawa ON ICT Manufacturing 3,047 10.6% $76,800 Ottawa - Gatineau ON ICT Manufacturing 13,879 -50.2% $95,423 Toronto ON ICT Manufacturing 54,805 -19.9% $78,034 Ottawa - Gatineau ON ICT Services 44,033 -3.4% $80,144 Toronto ON ICT Services 192,759 34.1% $78,364 Barrie ON Logistics 5,442 14.6% $69,067 Brantford ON Logistics 3,819 84.5% $51,366 Hamilton ON Logistics 21,506 10.8% $69,600 Kitchener - Waterloo ON Logistics 13,438 27.2% $63,895 Oshawa ON Logistics 10,317 36.9% $64,120 Toronto ON Logistics 215,599 14.8% $65,744 St. Catharines - Niagara ON Maritime 2,068 5.5% $57,222 Greater Sudbury ON Mining 8,057 35.9% $85,842 North Bay ON Mining 1,230 22.4% $89,760 Thunder Bay ON Mining 1,963 26.2% $77,394 Timmins ON Mining 3,547 25.8% $90,689 Sarnia ON Oil & Gas 1,916 -3.3% $112,242 Barrie ON Plastics & Rubber 2,721 -25.1% $55,019 Belleville ON Plastics & Rubber 1,421 7.6% $59,494 Brantford ON Plastics & Rubber 2,864 0.5% $52,076 Guelph ON Plastics & Rubber 1,919 -25.0% $58,683 Kitchener - Waterloo ON Plastics & Rubber 6,846 -38.5% $53,744 Oshawa ON Plastics & Rubber 4,708 -35.1% $59,045 Toronto ON Plastics & Rubber 75,465 -30.1% $56,076 Brantford ON Steel 1,754 -31.4% $63,766 Chatham-Kent ON Steel 2,273 -42.7% $75,710 Hamilton ON Steel 12,463 -44.8% $73,070 Kitchener - Waterloo ON Steel 5,640 -27.5% $58,750 Norfolk ON Steel 1,525 -27.4% $71,810 Oshawa ON Steel 8,175 14.7% $98,049 Sarnia ON Steel 2,128 -24.0% $93,306 St. Catharines - Niagara ON Steel 4,891 -27.9% $64,183 Windsor ON Steel 5,449 -44.9% $71,384 Kitchener - Waterloo ON Textiles 1,341 -70.1% $42,007 Toronto ON Textiles 18,115 -47.9% $45,041

Cluster Atlas of Canada Page 64 5.3.1 Sudbury Mining -

The mining cluster in Sudbury employed In 2011 Dun & Bradstreet identified 72 busi 8,057 people in 2011. This made Sudbury ness establishments in the Sudbury mining- the 3rd largest mining cluster in Canada (out cluster. The average establishment size was of 16). Between 2001 and 2011 employment 34 employees. The largest firms in core min increased by 35.9%. The labour force was ing industries in 2011 included: First Nickel 93.4% male and 6.6% female. 43.9% of the Inc; Layne Christensen Canada Limited; Vale labour force was over the age of 44. Inco Limited; Technica Group Inc; Northcote Industrial Products Inc; and Ethier Sand And In 2011 72.1% of the cluster labour force Gravel Limited. held post-secondary qualifications with 14.0% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Sudbury mining cluster was $85,842 per year. This ranked the cluster 12th out of 16 mining clusters in Canada. Figure 5.3.1.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 65 5.3.1 Sudbury Mining 35.0% Females, 6.6%

30.0%

25.0%

Figure 5.3.1.2 20.0% Labour force demographics, 2011 15.0% Males, 93.4% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 7.4% University, 14.0%

High School, 20.5%

Figure 5.3.1.3 Educational attainment of labour force, 2011

College & Trades, 58.1%

Manuacturing & Management (NOC Utilities (NOC 9), 0), 3.8% 4.1% Finance & Admin (NOC 1), 5.8%

Science & Tech (NOC 2), 15.4%

Figure 5.3.1.4 Natural Resources (NOC 8), 36.2% Occupational structure of labour force, 2011 Sales & Service (NOC 6), 2.1%

Trades & Transport (NOC 7), 31.3%

Cluster Atlas of Canada Page 66 5.3.2 Hamilton Steel

The steel cluster in Hamilton employed In 2011 Dun & Bradstreet identified 359 12,463 people in 2011. This made Hamilton business establishments in the Hamilton the 3rd largest steel cluster in Canada (out steel cluster. The average establishment size- of 14). Between 2001 and 2011 employment was 51 employees. The largest firms in core decreased by 44.8%. The labour force was steel industries in 2011 included: Arcelor 85.1% male and 14.9% female. 62.1% of the Mittal Dofasco Inc; U. S. Steel Canada Inc; labour force was over the age of 44. Tempel Canada Company; Nalco Canada Co.; Walter’s Inc; Baycoat Limited; Harris Steel In 2011 61.3% of the cluster labour force ULC; Associated Materials Canada Limited; held post-secondary qualifications with Orlick Industries Limited; and Sobotec Ltd. 17.0% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Hamilton steel cluster was $73,070 per year. This ranked the cluster 7th out of 14 steel clusters in Canada. Figure 5.3.2.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 67 5.3.2 Hamilton Steel 45.0% Females, 40.0% 14.9%

35.0%

30.0%

Figure 5.3.2.2 25.0% Labour force demographics, 2011 20.0% Males, 85.1%

Percent ofPercentlabour force 15.0%

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 8.8% University, 17.0%

Figure 5.3.2.3

Educational High School, 29.9% attainment of labour force, 2011

College & Trades, 44.3%

Management (NOC 0), 9.6%

Manuacturing & Utilities (NOC 9), 27.7% Finance & Admin (NOC 1), 12.1%

Figure 5.3.2.4 Occupational structure of

labour force, 2011 Science & Tech (NOC 2), 13.0%

Education, Law & Gov. (NOC 4), 0.9% Sales & Service (NOC 6), 4.2%

Trades & Transport (NOC 7), 32.0%

Cluster Atlas of Canada Page 68 5.3.3 Windsor Auto Manufacturing

The auto manufacturing cluster in Windsor the cluster 3rd out of 19 auto manufacturing employed 19,902 people in 2011. This made clusters in Canada. Windsor the 2nd largest auto manufacturing cluster in Canada (out of 19). Between 2001 In 2011 Dun & Bradstreet identified 384- and 2011 employment decreased by 45.0%. business establishments in the Windsor auto The labour force was 77.9% male and 22.1% manufacturing cluster. The average estab female. 46.3% of the labour force was over lishment size was 74 employees. The largest- the age of 44. firms in core auto manufacturing industries in 2011 included: Chrysler Canada Inc; Gen In 2011 56.1% of the cluster labour force eral Motors of Canada Limited; Ford Motor held post-secondary qualifications with Company of Canada Limited; Ventra Group 15.9% having a university degree. Co; Magna Seating Inc; A.P. Plasman Inc; Kautex Corporation; Quality Safety Systems According to the 2011 NHS the average full- Company; Nemak of Canada Corporation; time employment income for individuals and A.P. Plasman Inc. working in the Windsor auto manufacturing cluster was $68,114 per year. This ranked Figure 5.3.3.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 69 5.3.3 Windsor Auto Manufacturing 40.0%

Females, 35.0% 22.1%

30.0%

25.0% Figure 5.3.3.2 20.0% Labour force Males, demographics, 2011 77.9% 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 7.6% University, 15.9%

Figure 5.3.3.3 Educational

attainment of High School, 36.3% labour force, 2011

College & Trades, 40.2%

Management (NOC 0), 6.7% Finance & Admin (NOC 1), 6.6%

Science & Tech (NOC 2), 11.2% Figure 5.3.3.4 Occupational Manuacturing & Utilities (NOC 9), structure of 48.5% Sales & Service labour force, 2011 (NOC 6), 2.5%

Trades & Transport (NOC 7), 24.0%

Cluster Atlas of Canada Page 70 5.3.4 London Food & Beverage - - The food & beverage cluster in London em cluster 5th out of 15 food & beverage clusters ployed 6,972 people in 2011. This made Lon in Canada. don the 6th largest food & beverage cluster in Canada (out of 15). Between 2001 and- In 2011 Dun & Bradstreet identified 231- 2011 employment decreased by 5.0%. The business establishments in the London food labour force was 60.9% male and 39.1% fe & beverage cluster. The average establish male. 50.9% of the labour force was over the ment size was 24 employees. The largest- age of 44. firms in core food & beverage industries in 2011 included: Cuddy International Corpo In 2011 40.7% of the cluster labour force ration; Cargill Limited; Nestle Canada Inc; La- held post-secondary qualifications with Cie McCormick Canada Co.; Labatt Brewing 10.7% having a university degree. Company Limited; Coca-Cola Bottling Com pany; Canada Starch Operating Company Inc; According to the 2011 NHS the average full-- and Bonduelle Ontario Inc. time employment income for individuals working in the London food & beverage clus ter was $48,513 per year. This ranked the Figure 5.3.4.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 71 5.3.4 London Food & Beverage 40.0%

35.0%

Females, 30.0% 39.1%

25.0% Males, Figure 5.3.4.2 60.9% Labour force 20.0% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 10.7% No Degree, 17.1%

Figure 5.3.4.3 Educational attainment of College & Trades, labour force, 2011 30.0%

High School, 42.2%

Management (NOC 0), 7.5%

Finance & Admin Manuacturing & (NOC 1), 12.9% Utilities (NOC 9), 32.1%

Figure 5.3.4.4 Science & Tech (NOC 2), 3.8% Occupational structure of labour force, 2011

Sales & Service (NOC 6), 24.3% Trades & Transport (NOC 7), 19.3%

Cluster Atlas of Canada Page 72 5.3.5 Kitchener-Waterloo ICT Manufacturing -

The ICT manufacturing cluster in Kitchen turing clusters in Canada. er-Waterloo employed 11,371 people in - 2011. This made Kitchener-Waterloo the 4th- In 2011 Dun & Bradstreet identified 174 largest ICT manufacturing cluster in Canada business establishments in the Kitchen- (out of 9). Between 2001 and 2011 employ er-Waterloo ICT manufacturing cluster. The- ment increased by 58.7%. The labour force average establishment size was 52 employ was 65.9% male and 34.1% female. 27.3% of ees. The largest firms in core ICT manufac- the labour force was over the age of 44. turing industries in 2011 included: COM DEV- International Ltd; Babcock & Wilcox Cana In 2011 79.5% of the cluster labour force da Ltd; Rockwell Automation Canada Con held post-secondary qualifications with trol Systems; NCR Canada Ltd; Research In- 47.8% having a university degree. Motion Limited; Raytheon Canada Limited; Strite Industries Limited; Von Weise Of Cana According to the 2011 NHS the average full-- da Company; Unitron Hearing Ltd; Sandvine- time employment income for individuals Incorporated ULC; ATS Automation Tooling working in the Kitchener-Waterloo ICT man- Systems Inc; ATC-Frost Magnetics Inc; Sie ufacturing cluster was $76,933 per year. This mens Canada Limited; and EGS Electrical Figureranked 5.3.5.1the cluster 4th out of 9 ICT manufac Group Canada Ltd. Size and location of business establishments, 2011

Cluster Atlas of Canada Page 73 5.3.5 Kitchener-Waterloo ICT Manufacturing 40.0%

35.0%

Females, 30.0% 34.1%

25.0% Figure 5.3.5.2 Males, 65.9% Labour force 20.0% demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.5%

High School, 18.0%

Figure 5.3.5.3 Educational attainment of University, 47.8% labour force, 2011

College & Trades, 31.8%

Management (NOC Manuacturing & 0), 14.3% Utilities (NOC 9), 17.4%

Trades & Transport (NOC 7), 4.6% Finance & Admin Figure 5.3.5.4 (NOC 1), 14.6% Occupational Sales & Service structure of (NOC 6), 3.8% Creative & Cultural labour force, 2011 (NOC 5), 1.6% Education, Law & Gov. (NOC 4), 1.7%

Science & Tech (NOC 2), 41.3% Cluster Atlas of Canada Page 74 5.3.6 Hamilton Life Sciences -

The life sciences cluster in Hamilton em- 1st out of 7 life sciences clusters in Canada. ployed 4,021 people in 2011. This made- Hamilton the 6th largest life sciences in Can In 2011 Dun & Bradstreet identified 180 ada (out of 7). Between 2001 and 2011 em business establishments in the Hamilton life ployment increased by 31.4%. The labour sciences cluster. The average establishment- force was 38.9% male and 61.1% female. size was 14 employees. The largest firms in 51.7% of the labour force was over the age core life sciences industries in 2011 includ- of 44. ed: ABB Inc; Patheon Inc; Rotsaert Dental Laboratory Services Inc; Cedarlane Corpora In 2011 81.2% of the cluster labour force tion; Widex Canada Ltd; Gulfstream Plastics; held post-secondary qualifications with Hamilton Health Sciences Corporation; and 40.6% having a university degree. Islip Flow Controls Inc.

According to the 2011 NHS the average full- time employment income for individuals working in the Hamilton life sciences cluster was $76,883 per year. This ranked the cluster Figure 5.3.6.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 75 5.3.6 Hamilton Life Sciences 35.0%

30.0%

Males, 38.9% 25.0%

Females, Figure 5.3.6.2 20.0% 61.1% Labour force demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 1.0%

High School, 17.8%

Figure 5.3.6.3 University, 40.6% Educational attainment of labour force, 2011

College & Trades, 40.6%

Manuacturing & Utilities (NOC 9), Trades & Transport 4.9% Management (NOC (NOC 7), 2.6% 0), 18.8% Sales & Service (NOC 6), 11.5%

Figure 5.3.6.4 Education, Law & Occupational Gov. (NOC 4), 4.3% structure of labour force, 2011

Finance & Admin (NOC 1), 23.0%

Health (NOC 3), 23.3%

Science & Tech (NOC 2), 11.5% Cluster Atlas of Canada Page 76 5.3.7 Toronto Finance

- - The finance cluster in Toronto employed In 2011 Dun & Bradstreet identified 12,495 307,963 people in 2011. This made Toron business establishments in the Toronto fi to the largest finance cluster in Canada (out nance cluster. The average establishment- of 8). Between 2001 and 2011 employment size was 16 employees. The largest firms in increased by 35.6%. The labour force was core life sciences industries in 2011 includ 47.6% male and 52.4% female. 40.2% of the ed: The Toronto-Dominion Bank; Royal Bank labour force was over the age of 44. Inc; Canadian Imperial Bank Of Commerce; BMO Nesbitt Burns Inc; Intact Financial In 2011 80.2% of the cluster labour force Corporation; The Bank Of Nova Scotia; The held post-secondary qualifications with Workplace Safety & Insurance Board; Amex- 52.0% having a university degree. Canada Inc; The Great-West Life Assurance Company; The Canada Life Assurance Com According to the 2011 NHS the average full- pany; TD Securities Inc; Jones Edward D & time employment income for individuals Co. Canada Holding Co.; The Manufacturers working in the Toronto finance cluster was Life Insurance Company; Citi Cards Canada $89,388 per year. This ranked the cluster 1st Inc; RBC Insurance Holdings Inc; The Bank out of 8 finance clusters in Canada. of Nova Scotia Trust Company; and INTRIA Figure 5.3.7.1 Items Inc. Size and location of business establishments, 2011

Cluster Atlas of Canada Page 77 5.3.7 Toronto Finance 30.0%

25.0%

Males, 20.0% 47.6% Females, 52.4% Figure 5.3.7.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.5%

High School, 17.3%

Figure 5.3.7.3 Educational attainment of labour force, 2011 University, 52.0%

College & Trades, 28.2%

Trades & Transport (NOC 7), 1.7% Management (NOC 0), 18.2% Sales & Service (NOC 6), 18.7%

Figure 5.3.7.4 Creative & Cultural (NOC 5), 2.2% Occupational Education, Law & structure of Gov. (NOC 4), 2.6% labour force, 2011

Science & Tech (NOC 2), 10.1%

Finance & Admin (NOC 1), 46.1%

Cluster Atlas of Canada Page 78 5.3.8 Toronto Creative & Cultural - -

The creative & cultural cluster in Toron cluster 1st out of 4 creative & cultural clus to employed 158,249 people in 2011. This ters in Canada. made Toronto the largest creative & cultural cluster in Canada (out of 4). Between 2001 In 2011 Dun & Bradstreet identified 12,865 and 2011 employment increased by 37.8%. business establishments in the Hamilton life The labour force was 49.5% male and 50.5% sciences cluster. The average establishment- female. 36.1% of the labour force was over size was 8 employees. The largest firms in the age of 44. core life sciences industries in 2011 includ- ed: Canadian Broadcasting Corporation; CTV- In 2011 76.7% of the cluster labour force Inc; Cinram International Inc; Woodbine En held post-secondary qualifications with tertainment Group; Mood Media Corpora 46.1% having a university degree. tion; MacLaren McCann Canada Inc; Natmar Holdings Inc; CW Media Inc; and Maple Leaf According to the 2011 NHS the average full- Sports & Entertainment Ltd. time employment income for individuals working in the Toronto creative & cultural cluster was $64,115 per year. This ranked the Figure 5.3.8.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 79 5.3.8 Toronto Creative & Cultural 30.0%

25.0%

Males, 20.0% Females, 49.5% 50.5%

Figure 5.3.8.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 5.1%

High School, 18.2%

Figure 5.3.8.3 Educational University, 46.1% attainment of labour force, 2011

College & Trades, 30.7%

Trades & Transport Manuacturing & (NOC 7), 1.6% Utilities (NOC 9), 1.3% Management (NOC Sales & Service 0), 12.9% (NOC 6), 9.6%

Finance & Admin Figure 5.3.8.4 (NOC 1), 17.8% Occupational structure of labour force, 2011

Creative & Cultural (NOC 5), 39.4% Science & Tech (NOC 2), 7.9%

Education, Law & Gov. (NOC 4), 9.1%

Cluster Atlas of Canada Page 80 5.4 Prairies

The economic landscape of Manitoba, and one in Saskatoon. Calgary is home Saskatchewan, and Alberta is dominated to a business services cluster and an ICT by resources which account for 19 of the- services cluster. Both are growing at a 41 clusters in total. Specifically, there are healthy pace. If these provinces are going 11 oil & gas clusters of which 10 are in Al to diversify their economies away from berta, 5 mining clusters and 3 agriculture being resource-dependent, building on clusters. It is important to note that this knowledge intensive manufacturing and report captures economic activities that service industries is likely the best way- exist within city-regions and thus a great- forward due to the lack of an industrial deal, particularly in resources, is not heritage. This means as the key cities ex presented. Both the oil & gas and min pand they must be able to maintain their ing sectors have experienced extremely- currently very high standard of living. high rates of growth between 2001 and Public investments in infrastructure such 2011. The both also boast very high av- as urban transportation system will be erage wages. It is clear that these clusters- vital. have been very important for not just lo cal economic outcome but have had sig nificant national implications. There are 10 construction clusters, 9 in Alberta and 1 in Saskatchewan. They tend to be co-located with rapidly growing oil & gas clusters, likely due for the expansion of infrastructure and growing demand for housing. -

There is not a strong tradition of man ufacturing in these provinces and thus- there are only seven clusters identified. There are two well performing steel clus ters (which includes metal products) in Calgary and Edmonton which are likely- linked to the expansion of the oil & gas industry and its demand for new infra- structure. Winnipeg is home to a growing- life sciences cluster as well as an aero space cluster that has shown a slight de- cline in employment between 2001 and 2011. Calgary has the lone ICT manu facturing cluster which lost roughly one- quarter of its jobs in the ten years after- 2001. This is partly explained by the spe cific time period when the industry expe rienced retraction in most places.

There are four service clusters in the Prairie Provinces. Two higher education clustersCluster Atlas are of Canada present, one in Edmonton Page 81 Table 5.4.1 Prairie clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Winnipeg MB Aerospace 3,585 -9.7% $60,373 Brandon MB Agriculture 3,433 39.8% $44,729 Lethbridge AB Agriculture 5,505 127.9% $49,362 Saskatoon SK Agriculture 7,717 -2.4% $56,351 Winnipeg MB Life Sciences 4,358 28.5% $57,832 Calgary AB Business Services 100,406 36.3% $88,855 Calgary AB Construction 56,358 52.9% $91,621 Edmonton AB Construction 38,449 62.2% $80,784 Grande Prairie AB Construction 1,796 49.7% $65,961 Lethbridge AB Construction 2,493 81.3% $58,511 Lloydminster AB Construction 1,097 213.5% $71,492 Medicine Hat AB Construction 1,952 61.3% $60,633 Okotoks AB Construction 1,072 $79,427 Red Deer AB Construction 2,559 30.9% $66,897 Saskatoon SK Construction 7,943 109.6% $68,529 Wood Buffalo AB Construction 2,606 68.7% $105,810 Lethbridge AB Food & Beverage 2,236 56.9% $46,724 Edmonton AB Higher Education 27,561 69.4% $71,847 Saskatoon SK Higher Education 9,762 47.3% $69,871 Calgary AB ICT Manufacturing 7,853 -24.5% $83,332 Calgary AB ICT Services 39,231 24.9% $78,340 Calgary AB Logistics 40,817 16.7% $66,133 Calgary AB Mining 20,918 42.5% $122,993 Edmonton AB Mining 20,580 55.5% $92,857 Regina SK Mining 2,619 64.7% $89,360 Saskatoon SK Mining 5,623 73.5% $102,531 Thompson MB Mining 1,766 22.2% $93,429 Calgary AB Oil & Gas 53,707 64.0% $142,199 Cold Lake AB Oil & Gas 1,568 1.5% $105,502 Edmonton AB Oil & Gas 27,036 68.7% $97,660 Grande Prairie AB Oil & Gas 5,449 131.9% $91,272 Lloydminster AB Oil & Gas 3,780 58.8% $113,384 Medicine Hat AB Oil & Gas 3,687 47.8% $90,985 Okotoks AB Oil & Gas 1,313 $136,604 Red Deer AB Oil & Gas 5,189 50.4% $82,686 Regina SK Oil & Gas 2,464 61.6% $106,656 Sylvan Lake AB Oil & Gas 1,357 $87,737 Wood Buffalo AB Oil & Gas 15,069 99.5% $156,582 Calgary AB Steel 13,315 31.6% $115,420 Edmonton AB Steel 14,293 20.3% $86,362 Winnipeg MB Textiles 2,026 -65.6% $50,295

Cluster Atlas of Canada Page 82 5.4.1 Brandon Agriculture - - The agriculture cluster in Brandon employed In 2011 Dun & Bradstreet identified 19 busi 3,433 people in 2011. This made Brandon- ness establishments in the Brandon agricul the 10th largest agriculture cluster in Canada ture cluster. The average establishment size- (out of 18). Between 2001 and 2011 employ was 129 employees. The cluster is heavily ment increased by 39.8%. The labour force dominated by Maple Leaf Foods which em was 75.6% male and 24.4% female. 28.5% of ploys a majority of all workers. the labour force was over the age of 44.

In 2011 39.1% of the cluster labour force held post-secondary qualifications with 7.3% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Brandon agriculture cluster was $44,729 per year. This ranked the cluster 10th out of 18 agriculture clusters in Canada. Figure 5.4.1.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 83 5.4.1 Brandon Agriculture 40.0%

35.0% Females, 24.4%

30.0%

25.0% Figure 5.4.1.2 Labour force 20.0% Males, demographics, 2011 75.6% 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 7.3%

No Degree, 20.6%

Figure 5.4.1.3 College & Trades, Educational 31.8% attainment of labour force, 2011

High School, 40.3%

Management (NOC 0), 15.0%

Finance & Admin (NOC 1), 8.7% Figure 5.4.1.4 Occupational

structure of Sales & Service labour force, 2011 Manuacturing & (NOC 6), 3.7% Utilities (NOC 9), 55.9%

Trades & Transport (NOC 7), 10.3%

Natural Resources (NOC 8), 6.0%

Cluster Atlas of Canada Page 84 5.4.2 Winnipeg Life Sciences - - The life sciences cluster in Winnipeg em 7th out of 7 life sciences clusters in Canada. ployed 4,358 people in 2011. This made Win nipeg the 5th largest life sciences cluster in In 2011 Dun & Bradstreet identified 171 Canada (out of 7). Between 2001 and 2011 business establishments in the Winnipeg life employment increased by 28.5%. The labour sciences cluster. The average establishment- force was 39.9% male and 60.1% female. size was 12 employees. The largest firms in 46.4% of the labour force was over the age core life sciences industries in 2011 includ of 44. ed: Vita Health Products Inc; NAV Canada; Apotex Fermentation Inc; IMRIS Inc; and Rix In 2011 75.9% of the cluster labour force Ltd. held post-secondary qualifications with 40.0% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Winnipeg life sciences cluster was $57,832 per year. This ranked the cluster Figure 5.4.2.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 85 5.4.2 Winnipeg Life Sciences 35.0%

30.0%

Males, 39.9% 25.0%

Females, Figure 5.4.2.2 20.0% 60.1% Labour force demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 4.8%

High School, 19.3%

University, 40.0% Figure 5.4.2.3 Educational attainment of labour force, 2011

College & Trades, 35.9%

Manuacturing & Utilities (NOC 9), Management (NOC 14.9% 0), 12.8%

Trades & Transport (NOC 7), 2.0%

Finance & Admin Figure 5.4.2.4 Sales & Service (NOC 1), 16.7% (NOC 6), 10.8% Occupational structure of labour force, 2011 Education, Law & Gov. (NOC 4), 3.5%

Science & Tech (NOC 2), 13.5%

Health (NOC 3), 25.4%

Cluster Atlas of Canada Page 86 5.4.3 Saskatoon Agriculture - - - The agriculture cluster in Saskatoon em In 2011 Dun & Bradstreet identified 113 ployed 7,717 people in 2011. This made Sas business establishments in the Saskatoon ag katoon the 4th largest agriculture cluster in riculture cluster. The average establishment Canada (out of 18). Between 2001 and 2011 size was 30 employees. The largest firms in employment decreased by 2.4%. The labour core agriculture industries in 2011 included: force was 75.4% male and 24.6% female. CNH Canada Ltd; Maple Leaf Foods Inc; New- 44.3% of the labour force was over the age Food Classics; Prairie Machine & Parts MFG- of 44. Partnership; Norseman Structures Inc; Prai rie Pride Natural Foods Ltd; Vicwest Operat In 2011 49.1% of the cluster labour force ing Limited Partnership; Dow AgroSciences held post-secondary qualifications with Canada Inc; Wheatheart Manufacturing Ltd;- 18.7% having a university degree. JNE Welding; Advanced Ag. & Industrial Ltd; Prairie Machine & Parts Mfg (1978) Ltd; Har According to the 2011 NHS the average full- mon International Industries Inc; Bourgault time employment income for individuals F.P. Tillage Tools Ltd; Nutana Machine Ltd; working in the Saskatoon agriculture cluster and Supreme Steel Ltd. was $56,351 per year. This ranked the cluster Figure1st out 5.4.3.1of 18 agriculture clusters in Canada. Size and location of business establishments, 2011

Cluster Atlas of Canada Page 87 5.4.3 Saskatoon Agriculture 30.0%

Females, 25.0% 24.6%

20.0%

Figure 5.4.3.2 Labour force 15.0% Males, demographics, 2011 75.4%

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 14.6% University, 18.7%

Figure 5.4.3.3 Educational attainment of labour force, 2011

High School, 36.2% College & Trades, 30.4%

Manuacturing & Utilities (NOC 9), 20.6% Management (NOC 0), 26.9%

Figure 5.4.3.4 Occupational structure of Natural Resources (NOC 8), 10.3% labour force, 2011

Finance & Admin (NOC 1), 9.8%

Trades & Transport Science & Tech (NOC 7), 18.8% (NOC 2), 6.8% Sales & Service (NOC 6), 6.1% Cluster Atlas of Canada Page 88 5.4.4 Saskatoon Mining - - The mining cluster in Saskatoon employed In 2011 Dun & Bradstreet identified 76 busi 5,623 people in 2011. This made Saskatoon ness establishments in the Saskatoon min the 4th largest mining cluster in Canada (out ing cluster. The average establishment size of 16). Between 2001 and 2011 employment was 55 employees. The largest firms in core increased by 73.5%. The labour force was mining industries in 2011 included: AREVA 83.5% male and 16.5% female. 41.5% of the Resources Canada Inc; Agrium Inc; Cameco labour force was over the age of 44. Corporation; Mosaic Potash Colonsay ULC; Potash Corporation of Saskatchewan Inc; In 2011 66.2% of the cluster labour force Claude Resources Inc; and Shore Gold Inc. held post-secondary qualifications with 20.9% having a university degree.

According to the 2011 NHS the average full- time employment income for individuals working in the Saskatoon mining cluster was $102,531 per year. This ranked the cluster 2nd out of 16 mining clusters in Canada. Figure 5.4.4.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 89 5.4.4 Saskatoon Mining 35.0%

Females, 16.5% 30.0%

25.0%

Figure 5.4.4.2 20.0% Labour force demographics, 2011 15.0% Males, 83.5% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 8.3%

University, 20.9%

Figure 5.4.4.3 High School, 25.4% Educational attainment of labour force, 2011

College & Trades, 45.4% Manuacturing & Management (NOC Utilities (NOC 9), 0), 9.5% 3.0%

Natural Resources (NOC 8), 20.0%

Finance & Admin (NOC 1), 15.3%

Figure 5.4.4.4 Occupational structure of labour force, 2011

Science & Tech (NOC 2), 18.4%

Trades & Transport (NOC 7), 30.2%

Education, Law & Gov. (NOC 4), 2.4%

Cluster Atlas of Canada Page 90 5.4.5 Wood Buffalo Oil & Gas -

The oil & gas cluster in Wood Buffalo em- ter 1st out of 13 oil & gas clusters in Canada.- ployed 15,069 people in 2011. This made Wood Buffalo the 3rd largest oil & gas clus In 2011 Dun & Bradstreet identified 45 busi ter in Canada (out of 13). Between 2001 and- ness establishments in the Wood Buffalo oil 2011 employment increased by 99.5%. The & gas cluster. The average establishment size labour force was 79.8% male and 20.2% fe was 88 employees. These figures suggest male. 37.5% of the labour force was over the that the D&B data is not capturing many of- age of 44. the firms in this instance. The largest firms- in core oil & gas industries in 2011 includ In 2011 73.1% of the cluster labour force ed: Syncrude Canada Ltd; Landing Trail Pe held post-secondary qualifications with troleum Co; Matthews Equipment Limited; 18.6% having a university degree. Big Eagle Limited Partnership; Cardium Vac Services Ltd; Myshak Crane and Rigging Ltd;- According to the 2011 NHS the average full- BP Canada Energy Company; Brandt Tractor time employment income for individuals- Ltd; Inter Pipeline (Corridor) Inc; Ameco Ser working in the Wood Buffalo oil & gas cluster vices Inc; and ATCO Gas And Pipelines Ltd. was $156,582 per year. This ranked the clus Figure 5.4.5.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 91 5.4.5 Wood Buffalo Oil & Gas 35.0%

Females, 30.0% 20.2%

25.0%

Figure 5.4.5.2 20.0% Labour force Males, demographics, 2011 15.0% 79.8% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 5.2%

University, 18.6%

High School, 21.7%

Figure 5.4.5.3 Educational attainment of labour force, 2011

College & Trades, 54.5% Manuacturing & Management (NOC Utilities (NOC 9), 0), 6.9% 12.4%

Finance & Admin (NOC 1), 12.6% Natural Resources (NOC 8), 6.8%

Figure 5.4.5.4 Occupational structure of

labour force, 2011 Science & Tech (NOC 2), 17.4%

Trades & Transport (NOC 7), 38.9% Sales & Service (NOC 6), 2.9%

Cluster Atlas of Canada Page 92 5.4.6 Calgary Oil & Gas

The oil & gas cluster in Calgary employed In 2011 Dun & Bradstreet identified 2,826 53,707 people in 2011. This made Calgary business establishments in the Calgary oil & the largest oil & gas cluster in Canada (out gas cluster. The average establishment size- of 13). Between 2001 and 2011 employment was 27 employees. The largest firms in core- increased by 64.0%. The labour force was oil & gas industries in 2011 included: Impe 60.9% male and 39.1% female. 40.3% of the rial Oil; Cenovus Energy Inc; BP Canada En labour force was over the age of 44. ergy Company; Canadian Natural Resources Limited; ConocoPhillips Canada Resources In 2011 83.4% of the cluster labour force Corp; Talisman (Asia) Ltd; Nexen Holdings held post-secondary qualifications with (USA) Inc; Shell Canada Limited; Husky Oil 50.8% having a university degree. Operations Limited; Trican Well Service Ltd; and CGG Veritas. According to the 2011 NHS the average full- time employment income for individuals working in the Calgary oil & gas cluster was $142,199 per year. This ranked the cluster 2nd out of 13 oil & gas clusters in Canada. Figure 5.4.6.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 93 5.4.6 Calgary Oil & Gas 30.0%

25.0% Females, 39.1%

20.0%

Males, Figure 5.4.6.2 60.9% Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.8%

High School, 13.8%

Figure 5.4.6.3 Educational attainment of University, 50.8% labour force, 2011

College & Trades, 32.6%

Manuacturing & Natural Resources Utilities (NOC 9), 2.5% Management (NOC (NOC 8), 5.7% 0), 12.9% Trades & Transport (NOC 7), 5.2% Sales & Service (NOC 6), 2.4% Education, Law & Gov. (NOC 4), 3.8% Figure 5.4.6.4 Occupational structure of labour force, 2011

Finance & Admin (NOC 1), 35.0%

Science & Tech (NOC 2), 32.2%

Cluster Atlas of Canada Page 94 5.4.7 Calgary Logistics

- The logistics cluster in Calgary employed In 2011 Dun & Bradstreet identified 541 40,817 people in 2011. This made Calgary- business establishments in the Calgary logis the 4th largest logistics cluster in Canada tics cluster. The average establishment size (out of 10). Between 2001 and 2011 employ was 17 employees. The largest firms in core- ment increased by 16.7%. The labour force logistics industries in 2011 included: SCM was 65.4% male and 34.6% female. 40.3% of Supply Chain Management Inc; Sears Can the labour force was over the age of 44. ada Inc; HBC Logistics; Borek Kenn Air Ltd;- Sunwest Aviation Ltd; Bison Transport Inc; In 2011 55.2% of the cluster labour force Canada Safeway Limited; Horizon North Lo held post-secondary qualifications with gistics Inc; Borek Kenn Air Ltd; Avmax Group 20.8% having a university degree. Inc; United Parcel Service Canada Ltd; and Matrix Logistics Services Limited. According to the 2011 NHS the average full- time employment income for individuals working in the Calgary logistics cluster was $66,133 per year. This ranked the cluster 3rd out of 10 logistics clusters in Canada. Figure 5.4.7.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 95 5.4.7 Calgary Logistics 30.0%

25.0% Females, 34.6%

20.0%

Figure 5.4.7.2 Males, 65.4% Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 11.1%

University, 20.8%

Figure 5.4.7.3 Educational attainment of labour force, 2011 High School, 33.7%

College & Trades, 34.4%

Manuacturing & Utilities (NOC 9), 2.1% Management (NOC 0), 13.7% Trades & Transport (NOC 7), 19.5%

Figure 5.4.7.4 Occupational structure of labour force, 2011 Finance & Admin (NOC 1), 26.7%

Sales & Service (NOC 6), 25.8%

Science & Tech (NOC 2), 11.3% Cluster Atlas of Canada Page 96 5.5 British Columbia - -

The British Columbia economy is charac- is affordability which may crimp its abili terized by many resource clusters as well ty to attract and retain younger workers. as a strong set of service clusters. Forest ry & wood clusters are plentiful with 11 cases. Unfortunately, all 11 experienced employment declines between 2001 and 2011. Trade issues particularly with the- United States as well in slumping demand from the housing crash are likely key rea sons for these problems. BC also has four maritime clusters (includes fishing), two agriculture, two mining, and one oil & gas. Construction is also prominent with 11 clusters in the province. This is likely largely due to housing demand driven by population gains. -

The only manufacturing clusters in Brit ish Columbia are two in food & beverage (Abottsford-Mission and Vancouver) and one life sciences (Vancouver). All of these- clusters have shown strong growth over the 2001 to 2011 time period. The gen eral lack of manufacturing clusters in the province is a sign of the limited industrial history. There are likely some emerging technologies such as fuel cells and other environmental technologies that do not yet show up in the data due to the legacy of the industrial classifications systems. - British Columbia possesses eight service clusters, five of which are located in Van couver. There are also higher education clusters in Victoria and Nanaimo which- have grown at very high rates. Victoria additionally is home to a business ser vices cluster that grew by 30% between 2001 and 2011. All five types of service clusters are found in Vancouver. Each of these clusters employ at least 50,000 people and have grown by substantial amounts of the ten year period. As with other large cities, maintaining liveability is an important factor to these clusters as they are essentially driven by human capital.Cluster Atlas A seriousof Canada concern for Vancouver Page 97 Table 5.5.1 British Columbia clusters and key indicators Employment Average Employment Change Annual City Region Prov Cluster Type 2011 2001-2011 FT Income Abbotsford - Mission BC Agriculture 8,027 -5.0% $45,239 Chilliwack BC Agriculture 3,191 1.6% $44,155 Vancouver BC Life Sciences 11,910 34.8% $63,727 Vancouver BC Business Services 155,022 38.0% $74,328 Victoria BC Business Services 22,334 30.8% $67,368 Abbotsford - Mission BC Construction 4,139 62.3% $53,930 Chilliwack BC Construction 1,927 98.6% $47,976 Courtenay BC Construction 1,375 120.0% $51,668 Kamloops BC Construction 2,314 52.3% $59,965 Kelowna BC Construction 5,981 86.3% $58,642 Nanaimo BC Construction 2,468 82.8% $53,246 Penticton BC Construction 1,083 76.0% $45,313 Prince George BC Construction 1,959 30.6% $59,979 Vancouver BC Construction 64,446 53.6% $72,282 Vernon BC Construction 1,368 68.9% $50,286 Victoria BC Construction 8,034 44.5% $63,822 Vancouver BC Creative & Cultural 67,916 35.3% $57,927 Vancouver BC Finance 95,557 26.2% $76,962 Abbotsford - Mission BC Food & Beverage 2,885 47.5% $48,499 Vancouver BC Food & Beverage 39,271 21.0% $51,362 Abbotsford - Mission BC Forestry & Wood 2,288 -38.5% $57,964 Campbell River BC Forestry & Wood 1,187 -56.9% $67,112 Chilliwack BC Forestry & Wood 1,016 -31.3% $60,175 Duncan BC Forestry & Wood 1,230 -47.8% $70,520 Kamloops BC Forestry & Wood 1,748 -30.8% $68,881 Kelowna BC Forestry & Wood 2,136 -16.7% $67,597 Nanaimo BC Forestry & Wood 1,350 -43.9% $67,048 Prince George BC Forestry & Wood 4,504 -34.7% $75,838 Quesnel BC Forestry & Wood 2,951 -10.6% $69,931 Vernon BC Forestry & Wood 1,287 -11.6% $79,340 Williams Lake BC Forestry & Wood 1,507 -52.2% $65,643 Nanaimo BC Higher Education 2,075 273.9% $65,032 Vancouver BC Higher Education 58,301 62.4% $68,251 Victoria BC Higher Education 9,862 44.7% $65,519 Vancouver BC ICT Services 78,231 29.8% $72,196 Vancouver BC Logistics 81,261 4.8% $62,567 Nanaimo BC Maritime 1,300 1.1% $59,697 Prince Rupert BC Maritime 1,245 -6.4% $69,786 Vancouver BC Maritime 12,390 -14.3% $66,637 Victoria BC Maritime 3,621 -5.9% $59,879 Kamloops BC Mining 2,749 53.2% $87,653 Prince George BC Mining 1,356 12.6% $73,617 Fort St. John BC Oil & Gas 2,670 88.7% $95,575 Cluster Atlas of Canada Page 98 5.5.1 Prince George Forestry & Wood

The forestry & wood cluster in Prince George ranked the cluster 3rd out of 18 forestry & employed 4,504 people in 2011. This made wood clusters in Canada. Prince George the largest forestry & wood cluster in Canada (out of 18). Between 2001 In 2011 Dun & Bradstreet identified 144- and 2011 employment decreased by 34.7%. business establishments in the Prince George The labour force was 87.3% male and 12.7% forestry & wood cluster. The average estab female. 51.8% of the labour force was over lishment size was 16 employees. The largest the age of 44. firms in core forestry & wood industries in 2011 included: Canadian Forest Products In 2011 49.5% of the cluster labour force Ltd; Carrier Forest Products Ltd; Winton- held post-secondary qualifications with Global Lumber Ltd; Brink Forest Products- 10.7% having a university degree. Ltd; Parallel Wood Products Ltd; North - west Wood Preservers Ltd; Industrial For According to the 2011 NHS the average estry Service Ltd; Dollar Saver Lumber Ltd; full-time employment income for individ Warmac Ventures Ltd; Spruce Capital Homes uals working in the Prince George forestry Ltd; and Frost Lake Logging Ltd. & wood cluster was $75,838 per year. This Figure 5.5.1.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 99 5.5.1 Prince George Forestry & Wood 35.0% Females, 12.7% 30.0%

25.0%

Figure 5.5.1.2 20.0% Labour force demographics, 2011 15.0% Males, 87.3% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 10.7% No Degree, 17.1%

Figure 5.5.1.3 Educational attainment of labour force, 2011

College & Trades, 38.7%

High School, 33.4%

Management (NOC 0), 6.2% Finance & Admin Manuacturing & (NOC 1), 8.0% Utilities (NOC 9), 27.1%

Science & Tech Figure 5.5.1.4 (NOC 2), 12.5% Occupational structure of labour force, 2011 Sales & Service (NOC 6), 1.3%

Natural Resources (NOC 8), 16.9%

Trades & Transport (NOC 7), 28.0%

Cluster Atlas of Canada Page 100 5.5.2 Abbotsford - Mission Food & Beverage -

The food & beverage cluster in Abbotsford- ranked the cluster 6th out of 15 food & bev - Mission employed 2,885 people in 2011. erage clusters in Canada. - This made Abbotsford - Mission the 9th larg - est food & beverage cluster in Canada (out of In 2011 Dun & Bradstreet identified 64 busi 15). Between 2001 and 2011 employment ness establishments in the Abbotsford - Mis increased by 47.5%. The labour force was sion food & beverage cluster. The average- 62.6% male and 37.4% female. 31.9% of the establishment size was 16 employees. The labour force was over the age of 44. largest firms in core food & beverage in dustries in 2011 included: Lilydale Inc; A & In 2011 37.3% of the cluster labour force P Fruit Growers Ltd; Vanderpol’s Eggs Ltd; held post-secondary qualifications with Omstead Foods Limited; Valley Berries Inc; I 10.3% having a university degree. & G Bismarkating Ltd; Klassic Catering Ltd; Smith E.D. Foods Ltd; Anglo American Cedar According to the 2011 NHS the average full- Products Ltd; and B.C. Frozen Foods Ltd. time employment income for individuals working in the Abbotsford - Mission food & beverage cluster was $48,499 per year. This Figure 5.5.2.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 101 5.5.2 Abbotsford - Mission Food & Beverage 35.0%

30.0%

Females, 37.4% 25.0%

20.0% Males, Figure 5.5.2.2 62.6% Labour force demographics, 2011 15.0% Percent ofPercentlabour force

10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

University, 10.3% No Degree, 18.9%

Figure 5.5.2.3 Educational College & Trades, attainment of 27.0% labour force, 2011

High School, 43.8%

Management (NOC 0), 7.1%

Finance & Admin Manuacturing & (NOC 1), 12.2% Utilities (NOC 9), 32.1%

Science & Tech Figure 5.5.2.4 (NOC 2), 1.3% Occupational structure of labour force, 2011

Natural Resources Sales & Service (NOC 8), 0.0% (NOC 6), 22.6%

Trades & Transport (NOC 7), 24.7% Cluster Atlas of Canada Page 102 5.5.3 Victoria Business Services -

The business services cluster in Victoria em ters in Canada. ployed 22,334 people in 2011. This made - Victoria the 7th largest business services In 2011 Dun & Bradstreet identified 2,779- cluster in Canada (out of 10). Between 2001 business establishments in the Victoria busi and 2011 employment increased by 30.8%. ness services cluster. The average estab The labour force was 56.3% male and 43.7% lishment size was 8 employees. The largest- female. 51.0% of the labour force was over firms in core business services industries in- the age of 44. 2011 included: The Canadian Corps Of Com- missionaires National Off; The Land Con In 2011 81.3% of the cluster labour force servancy Enterprise Ltd; Agropur Coopera held post-secondary qualifications with tive; A.R.C. Accounts Recovery Corporation; 54.1% having a university degree. HP Advanced Solutions Inc; Sierra Systems- Group Inc; Land Title & Survey Authority of- According to the 2011 NHS the average full- British Columbia; Paretologic Inc; Total De time employment income for individuals livery Systems Inc; Rai Enterprise Ltd A; Dev working in the Victoria business services- on Properties Ltd; Coast Forest Management cluster was $67,368 per year. This ranked the Ltd; and Axys Analytical Services Ltd. Figurecluster 5.5.3.16th out of 10 business services clus Size and location of business establishments, 2011

Cluster Atlas of Canada Page 103 5.5.3 Victoria Business Services 30.0%

25.0%

Females, 43.7% 20.0% Males, 56.3% Figure 5.5.3.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 3.4%

High School, 15.3%

Figure 5.5.3.3 Educational attainment of

labour force, 2011 University, 54.1%

College & Trades, 27.2%

Trades & Transport Management (NOC Sales & Service (NOC 7), 2.5% 0), 8.8% (NOC 6), 8.3%

Creative & Cultural (NOC 5), 4.1%

Finance & Admin Figure 5.5.3.4 (NOC 1), 25.2% Occupational structure of Education, Law & labour force, 2011 Gov. (NOC 4), 22.1%

Health (NOC 3), 0.5%

Science & Tech (NOC 2), 27.8% Cluster Atlas of Canada Page 104 5.5.4 Vancouver ICT Services -

The ICT services cluster in Vancouver em- cluster 4th out of 7 ICT services clusters in ployed 78,231 people in 2011. This made Canada. Vancouver the 3rd largest ICT services clus ter in Canada (out of 7). Between 2001 and- In 2011 Dun & Bradstreet identified 2,567- 2011 employment increased by 29.8%. The business establishments in the Vancouver- labour force was 62.2% male and 37.8% fe ICT services cluster. The average estab male. 35.2% of the labour force was over the lishment size was 21 employees. The larg age of 44. est firms in core ICT services industries in 2011 included: TELUS Communications Inc; In 2011 83.6% of the cluster labour force Business Objects Corp; MDA Systems Ltd; held post-secondary qualifications with MacDonald Dettwiler And Associates Ltd; 56.4% having a university degree. McKesson Medical Imaging Company; NAV Canada; Rogers Cable Communications Inc; According to the 2011 NHS the average full-- and E-Comm Emergency Communications. time employment income for individuals working in the Vancouver ICT services clus ter was $72,196 per year. This ranked the Figure 5.5.4.1 Size and location of business establishments, 2011

Cluster Atlas of Canada Page 105 5.5.4 Vancouver ICT Services 30.0%

25.0% Females, 37.8%

20.0%

Males, Figure 5.5.4.2 62.2% Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 2.1%

High School, 14.3%

Figure 5.5.4.3 Educational attainment of labour force, 2011 University, 56.4% College & Trades, 27.2%

Trades & Transport (NOC 7), 4.0% Management (NOC Sales & Service 0), 12.0% (NOC 6), 9.4%

Creative & Cultural (NOC 5), 7.2% Finance & Admin (NOC 1), 14.9% Figure 5.5.4.4 Occupational structure of labour force, 2011

Education, Law & Gov. (NOC 4), 18.0%

Science & Tech (NOC 2), 33.4%

Cluster Atlas of Canada Page 106 5.5.5 Vancouver Creative & Cultural

The creative & cultural cluster in Vancouver ters in Canada. employed 67,916 people in 2011. This made Vancouver the 3rd largest creative & cultural In 2011 Dun & Bradstreet identified 4,601- cluster in Canada (out of 3). Between 2001 business establishments in the Vancouver and 2011 employment increased by 35.3%. creative & cultural cluster. The average estab The labour force was 52.6% male and 47.4% lishment size was 7 employees. The largest female. 36.3% of the labour force was over firms in core creative & cultural industries- the age of 44. in 2011 included: Canadian Broadcasting Corporation; B.C. Pavilion Corporation; Han In 2011 74.5% of the cluster labour force nah-Rachel Production Services Limited;- held post-secondary qualifications with Hastings Entertainment Inc; Grosvenor Park 41.3% having a university degree. Impact Productions Inc; Orangeville Race- way Limited; Canadian Tourism Commission- According to the 2011 NHS the average full- Fincentric Corporation; Mainframe Enter- time employment income for individuals tainment Inc; Postmedia Network Inc; Rain working in the Vancouver creative & cultural- maker Entertainment Inc; Pegasus Produc cluster was $57,927 per year. This ranked the tions V Inc; Black Street Productions Ltd; and Figurecluster 5.5.5.12nd out of 3 creative & cultural clus CTV Inc. Size and location of business establishments, 2011

Cluster Atlas of Canada Page 107 5.5.5 Vancouver Creative & Cultural 30.0%

25.0%

Females, 20.0% Males, 47.4% 52.6% Figure 5.5.5.2 Labour force 15.0% demographics, 2011

Percent ofPercentlabour force 10.0%

5.0%

0.0% Ages 15-24 Ages 25-34 Ages 35-44 Ages 45-54 Ages 55-64 Ages 65+

No Degree, 5.3%

High School, 20.1%

Figure 5.5.5.3 University, 41.3% Educational attainment of labour force, 2011

College & Trades, 33.2%

Trades & Transport Management (NOC (NOC 7), 1.8% Sales & Service 0), 9.6% (NOC 6), 8.8%

Finance & Admin (NOC 1), 13.9%

Figure 5.5.5.4 Occupational structure of labour force, 2011 Science & Tech (NOC 2), 9.3%

Creative & Cultural (NOC 5), 43.1%

Education, Law & Gov. (NOC 4), 11.9%

Cluster Atlas of Canada Page 108 6.0 Discussion & Conclusions

- This report provides a comprehensive some, as does economies of scale and overview of what industries are perform networks. It is important to consider that ing well and specifically where they are- certain clusters may be in decline due performing well in Canada. Pockets of- to a change in demand (e.g. coal mining strength and weakness are evident with- and certain forestry clusters), increased in the national economy and national ge global competition, or difficulties with ography. The information presented al attracting new younger workers. Further- lows for a sober view on where strategic research is needed to better understand investments are needed and where they- these complex dynamics in order to de may be most impactful. That being said velop effective policies that can balance there are some dilemmas that become ev the goals of maximizing aggregate growth ident when looking at the bigger trends. with those that are geared to distributing In particular, the 2001 to 2011 period growth across all parts of the country. was very difficult for manufacturing and some resource sectors such as forestry Current areas of strength are mainly the and wood. There are numerous reasons- aforementioned service based clusters as for this, namely the rise in the value of well as oil & gas and mining. Support for- the Canadian dollar, stronger global com the former largely depends on ensuring petition, and generally poor performance that the larger urban areas are well func- on innovation. tioning, highly liveable, and affordable. - Urban transportation systems and hous This generalized decline is a problem ing costs have been recent key issues for in its outright, but also one that is com such places. With oil & gas and mining- pounded by geography. The significant- public support is needed in achieving declines in traditional manufacturing- physical access to markets. Transpor- and resource sectors has mean signif tation investments including ports and icant decline for communities that de pipelines are key. These are the relative- pend on them. These communities tend ly straightforward interventions, more to be smaller and mid-sized cities that difficult decisions lie with many manu are often highly specialized in certain facturing clusters. While innovation is- economic activities. The decline of these essential across the entire spectrum of industries is only half of the problem. economic sectors, it is arguably most im There has been very strong employment portant in manufacturing. Furthermore,- growth in service industries and some the knowledge intensive clusters such as resource sectors such as oil & gas and ICT and life sciences receive a substan mining. While the latter are wedded to tial amount of attention in this area, but- certain locations for obvious reasons,- it is the next tier of industries that may the former provide hope that jobs can be be most crucial. Areas such as auto man created that replace the ones lost in oth ufacturing, steel, aluminum, and other er parts of the economy. The issue with- materials are under heavy pressure from- this however is that the rapid growth global competition that have a significant in services is occurring disproportion cost element. Long-term local industri- ately in the largest urban centres. There- al change in many clusters shows that- are different reasons why clusters exist- there is a trend away from manufactur where they do. Some are more cost sensi ing employment. This raises the poten- tive, some depend on specific infrastruc tial for deindustrialization and growing ture,Cluster access Atlas of Canadato markets matters more to disparity in regional economies that de Page 109 pend on such industries. Some regional- economies, particularly in Ontario and Quebec that rely on traditional manufac turing industries could face important challenges in rejuvenating themselves. Thus, effective innovation policies must be put in place in order to increase the- chances of longer term prosperity, not- just for the industries but for the com munities as a whole. This does not nec essarily mean trying to maintain what currently exists but also finding ways to- evolve to new and emerging technologies while building clusters of whole new in dustries. Overall, a balance needs to be struck between supporting clusters that are clearly drivers of growth and those that need assistance in order to provide sustainable foundations for communities in the future.

Cluster Atlas of Canada Page 110 Appendix A - Cluster Definitions - Agriculture

Fruit & vegetable Support activities Farms preserving & for farms specialty food mfg

Farm product wholesaler- Pesticide, fertilizer distributors Agricultural Animal food Dairy product & other agric. supplies manufacturing manufacturing chemical mfg Farm, lawn & wholesaler-dist. garden equip. wholesaler-dist.

Motor vehicle Boiler, tank Meat product body & trailer & shipping manufacturing manufacturing container mfg

Architectural & Agricultural, Warehousing Metal service structural metals construction & & storage centres manufacturing mining mach. mfg

Cluster Atlas of Canada Page 111 Appendix A - Cluster Definitions - Maritime

Inland water Ship and Heritage transportation boat building institutions

Scenic & Deep-sea, coastal sightseeing & … lakes water Fishing transport., water transportation

Support activities Seafood product for water preparation & transportation packaging Scenic & sightseeing transport., land

Cluster Atlas of Canada Page 112 Appendix A - Cluster Definitions - Forestry & Wood

Support activities for air transportation

Non-scheduled air transportation

Support Logging activities for forestry

Sawmills Veneer, plywood Pulp, paper & Other wood & wood & engineered paperboard mills product mfg preservation wood prod. mfg

Forest nurseries Timber tract & gathering of operations forest products

Cluster Atlas of Canada Page 113 Appendix A - Cluster Definitions - Mining

Support activities Electric power Non-metallic Rail for rail generation, mineral mining transportation transportation trans. & dist. & quarrying

Metal ore mining Coal Mining

Support act. for Mining mining & oil & gas (unspecified) extraction

Cluster Atlas of Canada Page 114 Appendix A - Cluster Definitions - Oil & Gas

Pipeline Other pipeline transportation transportation of natural gas

Support act. for Commercial & ind. Natural gas mining & oil & gas machinery & equip. distribution extraction rental & leasing

Pipeline Oil and gas Petroleum & coal transportation extraction products mfg of crude oil

Boiler, tank & shipping container mfg

Cluster Atlas of Canada Page 115 Appendix A - Cluster Definitions - Construction

Commercial & ind. Land subdivision machinery & equip. & land dvlpmt rental & leasing

Offices of Construction Building real estate management construction agents & brokers

Architectural, engineering & related services

Cluster Atlas of Canada Page 116 Appendix A - Cluster Definitions - Logistics

Home furnishings Home ent. equip. Metal service wholesaler- & hhold appliance centres distributors wholesaler-dist.

Cigarette & Textile, clothing Other support Used motor vehicle Warehousing Postal service tobacco product & footwear activities for parts & access. and storage wholesaler-dist. wholesaler-dist. transportation wholesaler-dist.

Pharma, toilet., Lumber … & other Electrical, Freight Chemical & Couriers cosm. & sundries building supplies … & A/C supplies transportation allied products wholesaler-dist. wholesaler-dist. wholesaler-dist. arrangement wholesaler-dist.

Other machinery, Food Beverage Wholesale Scheduled Non-scheduled equip. & supplies wholesaler- wholesaler- agents & brokers air transportation air transportation wholesaler-dist. distributors distributors

Computer & comm. Paper, paper prod. Other Personal goods Support equip. & supplies & plastic products miscellaneous wholesaler- activities for air wholesaler-dist. wholesaler-dist. wholesaler-dist. distributors transportation

Cluster Atlas of Canada Page 117 Appendix A - Cluster Definitions - Textiles

Textiles, clothing Leather & Clothing Fabric mills & footwear hide tanning accessories & wholesaler-dist. & finishing other clothing mfg

Cut & sew Other leather & Fibre, yarn & Other textile clothing allied product thread mills product mills manufacturing manufacturing

Textile & fabric Textile Clothing Footwear finishing & furnishings mills knitting mills manufacturing fabric coating

Cluster Atlas of Canada Page 118 Appendix A - Cluster Definitions - Food & Beverage

Beverage Sugar & Beverage Special food wholesaler- confectionery manufacturing services distributors product mfg

Fruit & vegetable Bakeries & Food Dairy product preserving & tortilla wholesaler- manufacturing specialty food mfg manufacturing distributors

Seafood product Warehousing Meat product Other food preparation & & storage manufacturing manufacturing packaging

Cluster Atlas of Canada Page 119 Appendix A - Cluster Definitions - Aluminum

Alumina and Aluminum Foundries Production and Processing

Cluster Atlas of Canada Page 120 Appendix A - Cluster Definitions - Steel

Other fabricated metal product Metalworking manufacturing machinery manufacturing

Foundries

Architectural & Coating, engraving Forging and structural metals heat treating & stamping manufacturing allied activities

Iron & steel mills Steel product Basic chemical & ferro-alloy mfg from manufacturing manufacturing purchased steel

Electric power Spring & Natural gas generation wire product distribution Trans. & dist. manufacturing

Cluster Atlas of Canada Page 121 Appendix A - Cluster Definitions - Auto Manufacturing

Machine shops Rubber product Plastic product … & screw, manufacturing manufacturing nut & bolt mfg

Paint, coating Motor vehicle Motor vehicle & adhesive Foundries manufacturing parts mfg manufacturing

Forging and stamping Spring & Metalworking wire product machinery manufacturing manufacturing Other fabricated Used motor vehicle metal product parts & access. manufacturing wholesaler-dist.

Coating, engraving heat treating & allied activities

Cluster Atlas of Canada Page 122 Appendix A - Cluster Definitions - Plastics & Rubber

Glass & Other Resin, synthetic Clay product & glass product miscellaneous rubber… mfg refractory mfg manufacturing manufacturing

Forging and Plastic product Rubber product Hardware stamping manufacturing manufacturing manufacturing

Soap, cleaning Converted Other chemical Printing & related compound & paper product product mfg support activities toilet prep. mfg manufacturing

Chemical & Paint, coating & allied products adhesive mfg wholesaler-dist.

Cluster Atlas of Canada Page 123 Appendix A - Cluster Definitions - Life Sciences

Pharma, toilet., Semiconductor & cosm. & sundries other electronic wholesaler-dist. component mfg

Nav., measuring, Pharmaceutical Medical equipment medical & control & medicine mfg & supplies mfg instruments mfg

Medical & Grant-making & diagnostic giving services laboratories

Cluster Atlas of Canada Page 124 Appendix A - Cluster Definitions - Aerospace

Aerospace Product and Parts Manufacturing

Cluster Atlas of Canada Page 125 Appendix A - Cluster Definitions - ICT Manufacturing

Electrical Computer & comm. equipment equip. & supplies manufacturing wholesaler-dist.

Computer & Semiconductor & Medical equipment peripheral equip. other electronic & supplies mfg manufacturing component mfg

Nav., measuring, Spring & Communications medical & control wire product equipment instruments mfg manufacturing manufacturing

Other electrical equipment & component mfg

Cluster Atlas of Canada Page 126 Appendix A - Cluster Definitions - ICT Services

Mfg & reproducing magnetic & optical media

Elect. & precision Software equipment repair publishers & maintenance

Bus. schools & Radio & television Data processing computer & broadcasting services mngmt training

Computer systems Universities Telecoms design & related services

Cluster Atlas of Canada Page 127 Appendix A - Cluster Definitions - Finance

Non-depository Agencies, … & Other funds & credit & other insurance Couriers financial intermediation related activities vehicles

Securities & Depository Insurance Pension funds commodities credit carriers … brokerage intermediation

Other financial Activities related Securities and Bus. schools & investment to credit commodity comp. & mngmt activities intermediation exchanges training

Accounting, tax Data processing Software prep, bookkeeping services publishers & payroll services

Cluster Atlas of Canada Page 128 Appendix A - Cluster Definitions - Business Services

Information Data processing Lessors of Investigation & services services real estate security services

Mngmt, scientific Computer systems Elect. & precision Business Couriers & technical design & related equipment repair support services consulting serv. services & maintenance

Bus schools & Architectural, Employment Legal services comp & mngmt Universities engineering & services training related services

Scientific research Technical & & development trade schools services

Cluster Atlas of Canada Page 129 Appendix A - Cluster Definitions - Creative & Cultural

Elect. & precision Mfg & reproducing equipment repair magnetic & & maintenance optical media

Motion picture & Radio & television Software Other schools video industries broadcasting publishers & instruction

Independent Technical & Specialized artists, writers & trade schools design services performers

Performing arts Sound recording Grant-making & companies industries giving services

Promoters of Agents … Advertising & Spectator performing arts for artists, related services sports & similar events entertainers…

Cluster Atlas of Canada Page 130 Appendix A - Cluster Definitions - Higher Education

Scientific research Information & development services services

Bus. schools & Technical & Universities comp. & mngmt trade schools training

Facilities Educational Other schools support support & instruction services services

Cluster Atlas of Canada Page 131 Appendix B - City-region Innovation Finance Indicators

Public R&D Private R&D Funding Expendiature Venture Capital Overall Business Public Enterprise R&D $ per R&D $ per VC $ per CMA Adult Pop. Rank Adult Pop. Rank Adult Pop. Rank Rank Guelph $3,230 2 $1,799 2 $763.4 1 1 Ottawa - Gatineau $818 13 $3,468 1 $315.7 2 2 Montréal $765 14 $1,443 3 $188.4 6 3 Sherbrooke $1,384 6 $264 16 $188.5 5 4 Kitchener $877 12 $1,241 5 $91.3 10 4 Calgary $644 17 $1,427 4 $112.2 8 6 Vancouver $682 15 $828 8 $145.0 7 7 Victoria $913 11 $264 17 $200.9 4 8 Québec $1,323 7 $489 12 $68.0 14 9 Toronto $505 18 $1,171 6 $84.5 11 10 Saskatoon $1,900 3 $223 20 $84.4 12 10 Kingston $3,683 1 $303 15 $6.2 21 12 Winnipeg $659 16 $342 13 $97.0 9 13 Edmonton $1,216 8 $224 19 $50.2 15 14 London $1,459 5 $245 18 $0.7 23 15 Halifax $945 10 $183 21 $41.8 16 16 Hamilton $1,510 4 $161 23 $3.0 22 17 St. John's $1,129 9 $137 27 $9.4 19 18 Saint John - 28 $678 9 $6.6 20 19 Moncton $204 25 $22 31 $206.4 3 20 Peterborough $402 19 $311 14 - 26 20 Windsor $241 24 $660 10 - 26 22 Oshawa - 28 $1,104 7 - 26 23 St. Catharines-Niagara $113 26 $144 26 $70.3 13 24 Brantford - 28 $573 11 - 26 24 Saguenay $300 22 $104 29 $27.4 18 26 Regina $322 21 $159 24 $0.1 24 26 Trois-Rivières $279 23 $76 30 $34.1 17 28 Barrie - 28 $178 22 $0.0 25 29 Thunder Bay $400 20 - 32 - 26 30 Kelowna - 28 $148 25 - 26 31 Abbotsford $22 27 $107 28 - 26 32 Greater Sudbury - 28 - 32 - 26 33

Original data sources: CAUBO; Impact Group/Statistic Canada; Thomson-Reuters Data are averages for 2005-2007

Cluster Atlas of Canada Page 132 Appendix B - City-region Innovation Output Indicators

Technological High-tech Innovation Entrepreneurship Incomes Overall High-tech Patents business Median per 10,000 formation Emp. CMA adult pop. Rank rate Rank Income Rank Rank Ottawa - Gatineau 16.8 1 12.8 2 $33,892 1 1 Toronto 6.0 8 13.1 1 $30,350 6 2 Calgary 5.5 9 12.8 3 $31,572 3 2 Kitchener 13.9 2 7.5 11 $30,719 5 4 Guelph 6.5 6 7.1 13 $31,470 4 5 Vancouver 9.2 3 11.2 4 $27,596 16 5 Windsor 7.5 4 6.5 16 $30,060 9 7 Kingston 6.6 5 10.5 6 $26,663 20 8 Hamilton 3.8 18 8.9 8 $30,186 7 9 Edmonton 4.9 11 7.0 15 $30,115 8 10 London 4.7 12 7.0 14 $28,727 12 11 Montréal 4.6 13 10.4 7 $26,731 19 12 Québec 4.3 14 6.4 17 $28,192 15 13 Halifax 2.1 24 8.9 9 $27,219 17 14 Barrie 3.7 19 5.1 23 $30,059 10 15 Oshawa 1.5 25 3.9 28 $33,863 2 16 Sherbrooke 3.9 17 8.0 10 $24,303 30 17 St. John's 0.7 32 11.0 5 $26,022 23 18 Saskatoon 5.5 10 4.3 27 $25,702 24 19 Kelowna 6.1 7 5.5 21 $23,692 33 19 Brantford 3.7 20 3.2 29 $28,311 13 21 Victoria 4.0 16 4.5 26 $26,329 22 22 Peterborough 4.2 15 5.1 22 $24,497 29 23 Moncton 1.0 30 7.1 12 $25,068 25 24 St. Catharines-Niagara 2.7 21 5.9 19 $24,750 27 24 Thunder Bay 0.6 33 5.7 20 $28,213 14 24 Winnipeg 2.6 22 5.0 24 $26,624 21 24 Regina 1.4 27 3.1 32 $29,210 11 28 Greater Sudbury 1.3 28 3.2 30 $26,793 18 29 Trois-Rivières 1.1 29 6.4 18 $24,059 31 30 Saint John 0.8 31 4.9 25 $24,981 26 31 Abbotsford 2.4 23 3.1 31 $24,541 28 31 Saguenay 1.5 26 2.6 33 $23,999 32 33

Original data sources: USPTO/Dieter Kogler UCD; Canadian Business Patterns; Census of Population 2006 Patent & income data is for 2006; HT formation is for 2001-2006

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