The First Step

THE FIRST STEP Understanding the Skills Gap in Grey County FEBRUARY 2014 FEBRUARY Acknowledgements from Gemma Mendez-Smith, Executive Director As the economy of Ontario continues to change along with national and global impacts so too does the Four County Region. It is important to know, with some degree of certainty, what assets and liabilities are present as we fashion a workforce and economic development strategy that keeps the region progressing to the future. This Skills Gap Study was commissioned by the Four County Labour Market Planning Board and its community partners as an update to the 2005 reports completed for Bruce Grey and Huron Perth.

The information in this report will provide recommendations to set guideposts that will keep us on track to building a successful, vibrant and sustainable future.

This study was completed by Harry Cummings, Don Murray and Shannon McIntyre of Harry Cummings and Associates.

Special thanks to the study committee; Rose Austin, Dave Barrett, Meredith Bowers, Debbie Davidson, Barb Fisher, Paul Nichol, Alyson Nyiri, and Kristin Sainsbury for their time and commitment to the study.

Thanks to the administration at our 4 district school boards and the leadership at the 24 participating high schools that supported this study without whom we would not have an insight from our future workforce.

Many thanks to the survey team for their hard work and dedication to getting the answers; Inem Chahal, Mark Ferguson, Carolyn Robertson, Elena Christy, Monika Kokoszka, Bakhtawar Khan, Anna Chow, Alberto Salguero, Shawn Filson, and Mary Ellen Wales.

Much gratitude to all of the employees, employers and high school students of Bruce, Grey, Huron and Perth counties who responded to a survey or participated in a focus group or interview. Your input will help us with our future planning goals.

Funded by: Ontario Ministry of Training, Colleges and Universities – Employment Ontario

Additional Support From: City of Stratford; County of Grey; County of Huron; County of Perth; Four County Labour Market Planning Board; Huron Business Development Corporation; Perth Community Futures Development Corporation; Saugeen Economic Development Corporation

Project Partners: Avon Maitland District School Board; Bluewater District School Board; Bruce Community Futures Development Corporation; Bruce Grey Catholic District School Board; Huron Perth Catholic District School Board

The views and opinions expressed in this document do not necessarily reflect those of the Government of Ontario Executive Summary and Recommendations

The need for timely and accurate labour market information is critical in the development of a healthy and sustainable labour market. Decisions regarding labour market planning, programming and resource allocation are all based on the labour market information that helps to describe the overall context in which we work and live.

The primary undertaking of this study was to examine the existing labour force and a forecast of future skill requirements by employers to help identify labour pool gaps critical to the sustainability and growth of existing and future employers in Bruce, Grey, Huron and Perth counties.

The Four County Labour Market Planning Board, and its partners, are completing this study as an update for the labour market skills gap studies that were completed in Bruce, Grey, Huron and Perth counties in 2005.

Data for this report was derived from five major sources: • Statistics Canada databases • Three original surveys designed and administered to employees, employers and Grade 12 students in the Four County Region • Focus groups with employers and economic development stakeholders in the Four County Region

Methods Thelabour market profile was compiled using data from the 2006 Statistics Canada National Census (Census) and the 2011 Statistics Canada National Household Survey (NHS). To illustrate the various population and labour features of the Four County Region tables were prepared from the analysis of Census and NHS data. The profile features comparisons between the four counties and the Province of Ontario.

Thehigh school survey was developed and administered to Grade 12 students attending high school in the Four County Region. The survey was administered in each of the participating high schools with the assistance of teachers and/or guidance counselors. The survey focused on the current academic achievements of students; their involvement in extracurricular, volunteer and co-op and work activities; their level of skills, and their plans for future education / training and a future career. A total of 378 students from Grey County completed the survey.

Theemployee survey was conducted by telephone with the general population of the Four County Region. Eligibility for the survey was restricted to individuals who were residents of either Bruce, Grey, Huron or Perth County, over 16 years of age, and not retired. The aim of the survey was to determine the particular levels of work experience, education and skills possessed by the residents of the area, as well as information on mobility, household activities and job satisfaction. A total of 301 Grey County residents completed the survey.

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 1 Theemployer survey was used to gather labour market information at the county level for Bruce, Grey, Huron and Perth counties. The objective was to survey as many as 50 businesses using a mixed method where at least 10 major employers were to be interviewed by phone and the balance participated in an online electronic version of the survey for each County. The list of candidate businesses was developed in consultation with the steering committee. Businesses were selected that represented a variety of industry sectors including businesses that were major employers in the county. A total of 62 employers in Grey County participated in the survey as well as representatives from the Bluewater District School Board, Bruce Grey Catholic District School Board, Grey County Federation of Agriculture, and Grey Bruce Health Services.

Findings Thelabour market profile was helpful in articulating a broad picture of the labour market environment for the Four County Region, and Grey County more specifically: • Between 2006 and 2011, Grey County experienced a slight population increase of 0.2% • Grey County has an older population with a median age of 47 years vs. 40 years for Ontario • The average household income for Grey County in 2011 was $56,518 which represents the lowest average of the Four County Region • The average personal income for Grey County in 2011 was $34,314 which is comparable to Huron and Perth counties but about $8,000 lower than the average for Ontario • A smaller proportion of people in Grey County have completed high school and gone on to complete higher levels of formal education compared to Ontario • A higher proportion of the Grey County population has completed an apprenticeship or trade program compared to the province • The employment participation rate in Grey County fell from 61.2% in 2006 to 58.3% in 2011 • The unemployment rate increased from 5.2% to 7.4% between 2006 and 2011 • The top three industries by employment in 2011 by place of work in Grey County were: Health Care and Social Assistance, Retail, and Manufacturing, very similar observations compared to the previous labour market studies

Thehigh school survey found that: • In general, female students have higher levels of achievement in the core subjects of English, math and science • Males tend to favour technology education courses, females are more likely to be engaged in arts courses • Students are very much engaged in extra-curricular activities, particularly sports and/ or physical activity • A large portion of students have volunteered in the last year, spending on average 50.2 hours a year • Fewer students are working part-time or summer jobs compared to the 2005 study • The most common part-time and summer employment activities are in the following sectors: • Wholesale and Retail Trade • Accommodation and Food Services • Arts, Entertainment, Recreation • Construction and/or Specialty Trade Contractor

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 2 • Males participating in co-op were most likely to be involved in Other services which include repair and maintenance and automotive repair • Females participating in co-op were most likely to be involved in Health Care and Social Assistance and Educational Services • For skills, males score themselves the highest in analytical, decision making and problem solving skills and teamwork skills while females score themselves highest in social, interpersonal skills and reading skills • The large majority (92%) of students expect to finish high school and continue onto post-secondary school or apprenticeship program • Males are much more likely to enroll in a trade, vocational or apprenticeship with 23% of the male respondents planning to attend a trade program compared to 2.7% of females • The top industry categories that male students expect to be employed in include: 1. Professional, Scientific and Technical Services 2. Construction and/or Specialty Trade Contractor 3. Health Care and Social Assistance • The top industry categories that female students expect be employed in include: 1. Health Care and Social Assistance 2. Arts, Entertainment, Recreation 3. Professional, Scientific and Technical Services • The majority (63%) of students in Grey County intend to leave their communities to find a job

Selected findings from theemployee survey are as follows: • Approximately 20% of respondents from Grey County held multiple jobs in the last year • More than 3/4 of respondents’ primary employment was fulltime • Approximately 34% reported college or a speciality school as their highest completed education • The top five occupations held in Grey County were: 1. Sales and service 2. Trades, transport and equipment operators and related occupations 3. Business, finance and administrative occupations 4. Occupations in education, law and social, community and government services 5. Management • The top three skills in Grey County as reported by employees were: 1. Reading 2. Verbal communication 3. Teamwork • The skills cited as weak among Grey County employees were: 1. Database 2. Information technology 3. Spreadsheets • Almost 60% of respondents did not participate in any training in the last year • Almost 20% of respondents believe they are underemployed (working less than 30 hours per week, not by choice; when skills are underutilized; when wages, productivity or other job qualities are substandard relative to skill and education level)

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 3 • In the next year, 85% of the respondents from Grey County believe they will be in the same job • Almost 5% believe they will be retired in one year, 28.8% of respondents reported they believe they will be retired in five years

Theemployer survey and interviews with the various sector specific representatives yielded the following findings: • The median number of years in operation in the Four County Region was 30 years • Approximately 70% of the businesses surveyed have 30 employees or less and 7% employ more than 200 • The skilled trades or skilled professionals positions are most difficult to fill • 78% of employers expect 10 retirements or less in the next five years • Employers from Grey County are looking for the following occupations skills: • Teamwork • Verbal communication • Social/interpersonal skills • Critical thinking and problem solving • Employers are having the most difficulty finding employees who have the following occupational skills: • Critical thinking and problem solving • Leadership skills • Artistic or creative skills • A small number of employers are experiencing sector specific challenges (agriculture, construction, education, health) • 44% of those surveyed offer apprenticeship opportunities in Grey County • Most companies offer a variety of occupational training to their employers on a regular basis including • Health and safety • Employee retraining • Apprenticeship programs • Classroom or vocational training

Recommendations Given the rapid pace of change in the regional job market stakeholders: businesses, educators and community partners, need to review and assess their strategies, programs and services to ensure they better reflect and address the new reality.

The following recommendations are based on the findings of the various research components of this report. These recommendations are intended to inform the decision making process for all relevant stakeholders, in Grey County, working with labour market issues.

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 4 Employers/Businesses Employers and business owners set the pace at which career decisions are made for the local workforce. They are also able to build strong connections to help with workforce attraction.

1. It is recommended that employers’ become more engaged in providing workplace training opportunities that could include co-op, apprenticeships, job shadows for the local labour force.

2. It is recommended that employers invest in ongoing training in the workplace by providing flexible hours to accommodate employee training.

3. It is recommended that employers collaborate with other businesses with similar skill requirements to provide necessary training (i.e. Health and Safety, sector specific training) to employees at a lower cost.

4. It is recommended that employers engage their workforce in training and mentoring to fill management positions and to ensure the transfer of institutional knowledge.

5. It is recommended that employers collaborate with community partners to highlight local career options and build an attraction strategy to aid in succession planning.

6. It is recommended that employers participate in a spousal employment program to help keep and attract the skilled professional.

Educators High Schools, Colleges, Universities, Private Career Colleges, Technical Delivery Agencies, etc.

Educators are able to build the skills of the future and current workforce to ensure they meet the demands of the local labour market.

1. It is recommended that guidance counsellors and those teaching the Grade 10 Careers Studies (GLC2O) in high schools must share information on the current local labour market and trends to ensure youth understand the dynamics of the local labour market to make sound education and career decisions.

2. It is recommended that the education sector should make use of resources available through community partners including the Four County Labour Market Planning Board, Saugeen Economic and Bruce Community Futures Development Corporations and employment and training service providers.

3. It is recommended that educators need to collaborate with community providers and parents to develop the soft skills in youth required by employers. These skills are not limited to but include; work ethic, leadership, teamwork, adaptability, organizational, problem solving and computer literacy.

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 5 4. It is recommended that colleges need to offer more flexibility in training to accommodate continuous learning opportunities.

5. It is recommended that guidance counsellors need to work with employers and community partners to promote the diversity of job opportunities in the area to students.

6. It is recommended that educators needs to collaborate with employers to build an attraction strategy for students who leave for post-secondary opportunities. Local high schools should develop a strategy to connect with alumni to maintain the relationship between graduates of the County and the local job market. This would include events to connect with youth when they return for holidays and vacation, newsletters and social media.

7. It is recommended that educators needs to highlight the apprenticeship opportunities to local youth, especially to females.

8. It is recommended that educators needs to incorporate business courses to help the workforce understand leadership and management in business.

9. It is recommended that educators need to collaborate with community partners to track Grade 12 graduates through post-secondary education and those who enter the workplace directly. The students’ field of work, field of study, place of study and place of residence could be tracked to maintain a database of the upcoming labour market skills, education and aspirations.

Community Partners Workforce Planning Board, Employment and Training Service Providers, Adult Learning Centres, Community Futures Development Corporations, County/Municipal Economic Development Services, Small Business Enterprise Centres, etc.

Community partners are the link between job seekers, business and education. It is important that they are involved in the strategies for workforce development.

1. It is recommended that the Planning Board needs to engage in a promotional program directed at education and employment partners to inform them about the existing and projected skills gaps and collaborate with these partners to provide support in assisting youth and job seekers in general to enhance their skills to meet the needs of the business community.

2. It is recommended that employment services need to partner with schools to promote their summer employment and other youth services in the schools to students as they look for employment related to their field of study or career of interest.

3. It is recommended that employment services need to partner with schools to offer their expertise in job development and career coaching to guidance counsellors and Career Studies teachers.

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 6 4. It is recommended that Community Futures Development Corporations (CFDCs) need to engage youth to explore the opportunities for entrepreneurship.

5. It is recommended that Small Business Enterprise Centres (SBECs) and CFDCs need to promote their training opportunities to local businesses.

6. It is recommended that County and Municipal Economic Development departments need to work with employers to build a strong workforce attraction strategy to fill immediate skills gaps.

7. It is recommended that adult education services need to promote their computer and education upgrading programs to local businesses.

8. It is recommended that community partners need to offer employment readiness programs to youth through a variety of options that could include Junior Achievement and Job Readiness Program offered by Owen Sound YMCA Employment Services.

9. It is recommended that community partners need to develop a strategy to connect with expatriates to communicate business and careers opportunities in Grey County. The target audience could include youth who go off to post-secondary or employment.

10. It is recommended that community partners must work together to study rural transportation issues and opportunities to encourage strategies related to improving accessibility to and from the workplace from those with limited access to a vehicle.

11. It is recommended that community partners should use the findings from this study and others to develop a strategic plan for local recruitment and retention including promotion of the rural lifestyle and recreational amenities, and spousal support for dual income households new to the area.

Overall, it will take a unified approach among the three key stakeholder groups to ensure economic and workforce development success for Grey County.

EXECUTIVE SUMMARY AND RECOMMENDATIONS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 7 Table of Contents Executive Summary and Recommendations 1 1.0 Introduction 10 2.0 Grey Labour Market Profile 12 2.1 Introduction 12 2.1.1 Limitations 12 2.2 Grey County Population Profile 13 2.2.1 Population 13 2.2.2 Age and Gender Distribution 14 2.2.3 Ethnic Origin 15 2.2.4 Household and Personal Income 17 2.2.5 Education 20 2.2.6 Personal Income by Education 23 2.3 Grey County Labour Force Profile 25 2.3.1 Labour Force Participation 25 2.3.2 Employment Rate 26 2.3.3 Unemployment 27 2.3.4 Employment by Industrial Sector 27 2.3.5 Labour Force by Occupation 33 2.3.6 Personal Income by Industrial Sector 37 2.4 Summary 38 Fact Sheet - Grey County High School Student Profile 39 3.0 Grey High School Student Survey 42 3.1 Introduction 42 3.2 Methodology 42 3.2.1 Survey Design 42 3.2.2 Population 43 3.2.3 Sampling Strategy 44 3.2.4 Survey Administration 44 3.3 Results 45 3.3.1 Response Rates 45 3.3.2 Respondent Profiles 46 3.3.3 Courses 46 3.3.4 Extra-Curricular Activities 51 3.3.5 Volunteer Activities 54 3.3.6 Paid Work 59 3.3.7 School Co-op Activities 67 3.3.8 Work at Home Activities 69 3.3.9 Overall Skills 71 3.3.10 Plans for Future Education 73 3.3.11 Plans for Future Career 80 3.3.12 Future Place of Work and Residence 83 3.4 Summary 85

TABLE OF CONTENTS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 8 Fact Sheet - Grey County Employee Experiences 87 4.0 Grey Employee Survey 90 4.1 Introduction 90 4.2 Methodology 90 4.2.1 Survey Design 90 4.2.2 Survey Process 91 4.2.3 Sampling Strategy 91 4.3 Survey Analysis 92 4.3.1 Response Rate 92 4.3.2 Respondent Profile 92 4.3.3 Labour Market Features 94 4.3.4 Community Characteristics 116 4.4 Employee Summary 119 Fact Sheet - Grey County Employer Experiences 121 5.0 Grey Employer Survey 124 5.1 Introduction 124 5.2 Methodology 124 5.2.1 Survey Design 124 5.2.2 Survey Process 125 5.3 Survey Analysis 125 5.3.1 Respondent Profile 125 5.3.2 Employees’ Status 129 5.3.3 Employees’ Skills Assessment 130 5.3.4 Current and Future Workforce 133 5.3.5 Training 138 5.4 Focus Group Results 140 5.5 Employer Summary 142 6.0 Summary of Findings 144 List of Tables 153

TABLE OF CONTENTS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 9 1.0 Introduction

Bruce, Grey, Huron and Perth Counties, like rural Ontario more generally, have experienced a changing labour market including youth out migration, centralization of services and jobs to urban centres and changes in the education system. Given the ever changing environment, the Four County Labour Market Planning Board, and its partners, recognize that current and comprehensive labour market information is critical in the development of a healthy and sustainable labour market. Decisions regarding labour market planning, programming and resource allocation are all based on the labour market information that helps to describe the overall context in which we work and live. As such, a study of the existing labour force and a forecast of future skill requirements by employers was completed to help identify labour pool gaps critical to the sustainability and growth of existing and future employers. This study is an update for the labour market skills gap studies that were completed in Bruce, Grey, Huron and Perth counties in 2005. Where possible the community and labour market profiles developed for the current study were compared to the previous studies.1

Data for this report were derived from five major sources: • Statistics Canada databases, including the 2006 and 2011 censuses • Three original surveys designed and administered to employees, employers and grade 12 students in the Four County Region • Focus groups with employers and economic development stakeholders in the Four County Region

1 Individual reports were prepared for each county as part of the current study while blended reports were prepared for Bruce/Grey and Huron/Perth for the previous studies.

SECTION 1: INTRODUCTION THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 10 The report consists of six major sections. The first two sections, a Grey County community profile and labour market profile, were developed using Statistics Canada data. These data were compared to Ontario and to Bruce, Huron and Perth counties. The information from these profiles provide a foundation for understanding the issues in the larger context of the region as a whole.

The third section reports on the high school survey results. This survey was developed and administered to students in grade 12 in both the public and Catholic school boards in Grey County. The information gathered from the high school students can provide some insight into future contributions made by the next generation of the labour pool.

The fourth section highlights the findings of the employee survey that was developed to gather information on the current labour pool with respect to skills, education and training as well as job satisfaction and forecasts for future employment, mobility and training plans.

Survey findings from the employers and industry specific representatives is the fifth section of the report. The employer survey was completed in four phases. The first phase involved telephone interviews with strategically important local employers while the second phase was an online survey of additional local businesses. The third phase involved interviews with health, education and agriculture sector representatives and the fourth phase involved focus groups with employers.

The final sections of the report include a summary of all findings as well as recommendations on future directions suggested by these findings.

SECTION 1: INTRODUCTION THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 11 2.0 Grey Labour Market Profile

2.1 Introduction The purpose of the profile is to provide background information on the general socio-economic conditions in Grey County. The profile compliments research into present and future skills gaps in the Four County Region: Bruce, Grey, Huron and Perth counties. Understanding the socio-economic context is essential for developing effective economic and human resource development strategies.

The profile was compiled using data from the 2006 Statistics Canada Population Census and the 2011 Statistics Canada National Household Survey. To illustrate the various population and labour features of Grey County, tables and graphs have been prepared from the data. The profile features comparisons between the four counties and the Province of Ontario. In some cases comparisons have also been made to the previous study period.

2.1.1 Limitations The 2011 National Household Survey (NHS) was a voluntary survey, as opposed to the Census of Population long-form questionnaire used in previous databases for which response was mandatory. As a result there is an important difference in the response rates in 2011 compared to previous years.

For the 2011 NHS estimates, the global non-response rate (GNR) is used as an indicator of data quality. This indicator combines complete non-response (household) and partial non-response (question) into a single rate. A smaller GNR indicates a lower risk of non-response bias and as a result, lower risk of inaccuracy. The threshold used for estimates’ suppression is a GNR of 50% or more. The non-response rate for Canada and Ontario was 26% and 27% respectively.2

2 National Household Survey User Guide, 2011. Statistics Canada.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 12 The non-response rate for Grey County in 2011 was 36.8%. Non-response bias is a concern because the characteristics of people who responded to the survey may be different from those who refused to participate. This means that there are potential gaps in data from groups and communities that tend not to respond to voluntary surveys including new immigrants, low income families, residents in rural areas.

2.2 Grey County Population Profile 2.2.1 Population Grey County has a total land area of 4,513 square kilometres and a population density of 20.5 persons per square kilometre. Between 2006 and 2011 the population of Grey County was fairly stable with a small increase of 0.2%. Grey County is situated two hours north of Toronto and is bordered by Georgian Bay and Simcoe County to the east, the County of Bruce and the Bruce Peninsula to the west and Wellington and Dufferin Counties to the south. Highway 6 serves as a major corridor from the south of the county to the key seasonal tourist destinations of Bruce Peninsula and Georgian Bay.

Table 1: Population of Grey County 1996 2001 2006 2011 Percent Change 2006 to 2011 87,621 89,073 92,411 92,568 0.2%

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 13 2.2.2 Age and Gender Distribution The distribution of age across the population of Grey County is illustrated in Table 2. The population of the region varies among counties. In comparison to the Province of Ontario, the Four County Region has an older population. The median age in Ontario, in 2011, was 40.4 years. Each of the counties have a slightly higher proportion of females than males and a higher proportion of those 85 years of age and older than the province. Grey County has the oldest population in the region with a median age of 47.3 and the highest proportion of those 85 years and older.

Table 2: Age Distribution of Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011 Bruce Grey Huron Perth Ontario Total 66,100 92,565 59,100 75,110 12,851,820 Population Median 47 47.3 45.1 41.2 40.4 Age Pop. % Pop. % Pop. % Pop. % Pop. % 0-4 3,465 5.24 4,285 4.63 3,255 5.51 4,445 5.92 704,260 5.48 5-9 3,135 4.74 4,455 4.81 3,200 5.41 4,550 6.06 712,755 5.55 10-14 3,365 5.09 5,195 5.61 3,630 6.14 4,750 6.32 763,755 5.94 15-19 4,205 6.36 5,905 6.38 4,135 7.00 5,325 7.09 863,635 6.72 20-24 3,765 5.70 5,190 5.61 3,315 5.61 4,680 6.23 852,910 6.64 25-29 3,580 5.42 4,260 4.60 2,930 4.96 4,215 5.61 815,120 6.34 30-34 3,260 4.93 4,180 4.52 2,855 4.83 4,175 5.56 800,365 6.23 35-39 3,130 4.74 4,470 4.83 2,885 4.88 4,300 5.72 844,335 6.57 40-44 3,395 5.14 5,265 5.69 3,270 5.53 4,630 6.16 924,075 7.19 45-49 4,840 7.32 6,995 7.56 4,260 7.21 5,750 7.66 1,055,880 8.22 50-54 5,575 8.43 7,765 8.39 4,645 7.86 5,930 7.90 1,006,140 7.83 55-59 5,670 8.58 7,620 8.23 4,515 7.64 5,455 7.26 864,620 6.73 60-64 5,465 8.27 7,475 8.08 4,475 7.57 4,505 6.00 765,655 5.96 65-69 4,280 6.48 5,890 6.36 3,505 5.93 3,345 4.45 563,485 4.38 70-74 3,275 4.95 4,540 4.90 2,795 4.73 2,800 3.73 440,780 3.43 75-79 2,455 3.71 3,710 4.01 2,135 3.61 2,295 3.06 356,150 2.77 80-84 1,755 2.66 2,885 3.12 1,710 2.89 2,000 2.66 271,510 2.11 85+ 1,490 2.25 2,495 2.70 1,580 2.67 1,975 2.63 246,400 1.92

When comparing the population for Grey County to that of the province (Figure 1), it is clear that the age distribution is significantly different. The province has a greater proportion of children and youth than Grey County, with the exception of those aged 5-9 years. Grey County has a higher proportion of every age category over 55 years compared to Ontario.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 14 Figure 1: Population Chart, Ontario and Grey County 2011

2.2.3 Ethnic Origin Table 3 shows the number and percentage of the thirty most commonly reported ethnic groups by population in Ontario. The greatest number of Grey residents reported their ethnic origin as English followed by Canadian and Scottish. These rankings are fairly consistent with the provincial profile. Canadian, English, Scottish, Irish and German ethnic origins account for more than 80% the total population base in Grey County. In comparison, these five ethnic origins account for 52.3% of the total population base in Ontario.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 15 Table 3: Population by Ethnic Origin for Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011

Bruce Grey Huron Perth Ontario

# % # % # % # % # % Canadian 22,330 18.54 30,160 17.33 17,910 16.76 22,985 16.86 2,946,095 13.78 English 21,730 18.05 35,210 20.24 20,085 18.79 24,280 17.81 2,925,660 13.68 Scottish 18,730 15.55 29,195 16.78 16,945 15.86 19,000 13.94 2,080,545 9.73 Irish 16,025 13.31 25,090 14.42 15,370 14.38 16,895 12.4 2,069,110 9.67 French 5,420 4.5 7,195 4.14 5,095 4.77 5,970 4.38 1,362,320 6.37 German 16,545 13.74 20,135 11.57 13,535 12.67 22,070 16.19 1,154,550 5.4 Italian 1,205 1 1,650 0.95 845 0.79 1,560 1.14 883,990 4.13 Chinese 275 0.23 230 0.13 130 0.12 330 0.24 713,245 3.34 East 280 0.23 265 0.15 80 0.07 355 0.26 678,465 3.17 Indian Dutch 3,950 3.28 6,075 3.49 7,585 7.1 7,855 5.76 508,595 2.38 Polish 1,315 1.09 1,785 1.03 865 0.81 1,035 0.76 475,565 2.22 N. American 2,480 2.06 2,060 1.18 900 0.84 1,055 0.77 345,870 1.62 Indian Ukrainian 975 0.81 1,635 0.94 540 0.51 915 0.67 342,005 1.6 Filipino 165 0.14 95 0.05 60 0.06 150 0.11 295,700 1.38 Portuguese 335 0.28 360 0.21 150 0.14 345 0.25 295,030 1.38 Jamaican 55 0.05 120 0.07 35 0.03 80 0.06 218,065 1.02 Welsh 1,070 0.89 2,015 1.16 1,025 0.96 1,390 1.02 192,650 0.9 Russian 270 0.22 465 0.27 200 0.19 740 0.54 186,940 0.87 Jewish 230 0.19 190 0.11 90 0.08 75 0.06 173,780 0.81 Spanish 190 0.16 395 0.23 295 0.28 345 0.25 164,650 0.77 Hungarian 560 0.47 740 0.43 395 0.37 355 0.26 148,960 0.7 Greek 60 0.05 135 0.08 55 0.05 140 0.1 140,970 0.66 American 980 0.81 1,035 0.59 525 0.49 715 0.52 136,500 0.64 Sri Lankan 0 0 15 0.01 0 0 0 0 112,465 0.53 Pakistani 55 0.05 55 0.03 0 0 0 0 109,295 0.51 Vietnam- 0 0 30 0.02 0 0 75 0.06 100,520 0.47 ese Métis 680 0.56 1,135 0.65 125 0.12 300 0.22 97,045 0.45 Iranian 40 0.03 0 0 0 0 50 0.04 92,635 0.43 Romanian 120 0.1 300 0.17 115 0.11 290 0.21 85,115 0.4 Korean 100 0.08 115 0.07 0 0 145 0.11 82,640 0.39 Other 4,250 3.53 6,100 3.51 3,910 3.66 6,800 4.99 2,267,600 10.6

Total 120,420 100 173,985 100 106,865 100 136,300 100 21,386,575 100

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 16 2.2.4 Household and Personal Income 2.2.4.1 Household Income In Grey County the average household income was $70,736, an $8,190 increase from 2006, as shown in Table 4. The average household income for Ontario in 2011 was $85,772. Grey County has the lowest average household income for the Four County Region. Bruce County had the greatest increase, with a $19,052 increase from 2006 to 2011.

Table 4: Average Household Income for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011 2011 ($) 2006 ($) Change ($)

Bruce 83,516 64,464 19,052 Grey 70,736 62,546 8,190 Huron 71,916 63,011 8,905 Perth 75,863 67,241 8,622 Ontario 85,772 77,967 7,805

Part of the reason for the higher provincial median family income is the higher percentage of Ontario households in the larger income categories. As shown in Table 5, 30% of the Ontario households reported an income of $100,000 or higher, while in Grey County 21% reported a family income of $100,000 or higher. More than 10% of the Grey County population reported a household income less than $20,000.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 17 Table 5: Population by Family Income Categories in Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011

Bruce Grey Huron Perth Ontario

# % # % # % # % # % Total 27,410 100 38,040 100 23,640 100 29,400 100 4,886,655 100 Households Under 500 1.8 875 2.3 420 1.8 515 1.8 123,775 3 $5,000 $5,000 to 335 1.2 395 1 165 0.7 240 0.8 78,005 2 $9,999 $10,000 to 700 2.6 975 2.6 685 2.9 650 2.2 143,390 3 $14,999 $15,000 to 1,055 3.8 1,765 4.6 1,200 5.1 1,060 3.6 211,140 4 $19,999 $20,000 to 2,490 9.1 4,205 11.1 2,210 9.3 2,630 8.9 405,725 8 $29,999 $30,000 to 2,835 10.3 3,925 10.3 2,975 12.6 3,235 11 425,410 9 $39,999 $40,000 to 2,565 9.4 4,220 11.1 2,280 9.6 2,605 8.9 425,720 9 $49,999 $50,000 to 2,010 7.3 3,655 9.6 2,420 10.2 2,955 10.1 398,705 8 $59,999 $60,000 to 3,820 13.9 5,755 15.1 3,680 15.6 4,380 14.9 680,850 14 $79,999 $80,000 to 2,915 10.6 4,295 11.3 2,605 11 3,890 13.2 552,660 11 $99,999 $100,000 to 2,675 9.8 3,150 8.3 2,195 9.3 3,215 10.9 497,970 10 $124,999 $125,000 to 1,740 6.3 2,045 5.4 1,245 5.3 1,625 5.5 331,460 7 $149,999 $150,000 3,775 13.8 2,780 7.3 1,555 6.6 2,410 8.2 611,840 13 and over

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 18 2.2.4.2 Personal Income The analysis of personal income data in 2011 shows that Ontario as a whole reported a higher personal average income (male and female combined) compared to all counties in the Four County Region, with the exception of Bruce County. From Table 6, the average personal income was $34,314 in Grey County, $7,950 less than the Ontario average personal income. Grey County reported the second lowest personal average income for the Four County Region. In 2011, Grey County males reported almost $10,000 more in average personal income compared to females ($38,971 versus $29,159).

Table 6: Average Personal Income by Place of Residence, by Gender, NHS 2011 Total ($) Male ($) Female ($)

Bruce 42,279 50,960 31,824

Grey 34,314 38,971 29,159

Huron 33,932 38,064 29,229

Perth 35,731 41,437 29,542

Ontario 42,264 50,242 34,716

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 19 2.2.5 Education 2.2.5.1 Education Levels Approximately 22.4% of the Grey County population, 15 years and older, have not completed high school compared to 18.7% for Ontario. In Grey County 29.3% of the population reported a high school diploma as their highest level of education. Just over 10% of the Grey County population has received an apprentice or trade certificate while 22% has attended college. Just over 16% of the Grey County population has attended university of which 8.5% has completed a bachelor’s degree and 4.9% has completed a graduate degree or higher.

Table 7: Highest Education Level for Bruce, Grey, Huron and Perth County, NHS 2011 Bruce Grey Huron Perth Ontario # % # % # % # % # % Population 15 years & over by highest 54,855 100 76,335 100 47,815 100.0 59,820 100 10,473,670 100 education

Less than high school 11,620 21.2 17,105 22.4 12,585 26.3 15,535 26.0 1,954,520 18.7

High school graduate 14,455 26.4 22,325 29.3 13,570 28.4 17,875 29.9 2,801,805 26.8

Apprenticeship 6,175 11.3 7,910 10.4 5,130 10.7 5,835 9.8 771,140 7.4 or Trade

College, with or without degree 13,555 24.7 16,720 21.9 10,520 22.0 11,890 19.9 2,070,875 19.8 or diploma

University, 1,555 2.8 2,090 2.7 1,000 2.1 1,280 2.1 427,150 4.1 without degree

University, 4,895 8.9 6,475 8.5 3,310 6.9 4,970 8.3 1,515,075 14.5 Bachelor’s degree

University, above 2,600 4.7 3,715 4.9 1,700 3.6 2,445 4.1 933,100 8.9 Bachelor’s degree

In general, a smaller proportion of people in Grey County have completed high school and gone on to complete higher levels of formal education compared to Ontario as a whole. However, a higher proportion of the Grey County population has completed an apprenticeship or trade program compared to the province.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 20 2.2.5.2 Major Field of Study for Men and Women When compared with the Four County Region as a whole, the profile for women in Grey County reveal several general similarities. All four counties share the top three ranking fields of study. There was slight variation between the three least common fields of study for women in the Four County Region, though Mathematics; computer and information sciences was present in each county’s least common three.

Table 8: Post-Secondary Field of Study for Females for Bruce, Grey, Huron and Perth County, NHS 2011

Bruce Grey Huron Perth # % # % # % # % Total population aged 15 years and over by 27,475 100.0 38,990 100.0 24,315 100.0 30,660 100.0 major field of study No postsecondary certificate; diploma 13,205 48.1 19,795 50.8 12,905 53.1 17,045 55.6 or degree Education 1,800 6.6 2,660 7.0 1,430 5.9 1,640 5.4 Visual and performing arts; and communica- 380 1.4 770 2.0 260 1.1 475 1.6 tions technologies Humanities 850 3.1 1,060 2.8 590 2.4 900 2.9 Social and behavioural 1,630 5.9 2,200 5.7 1,405 5.8 1,675 5.5 sciences and law Business; management and 3,340 12.2 4,130 10.6 2,535 10.4 2,760 9.0 public administration Physical and life sciences 335 1.2 390 1.0 200 0.8 250 0.8 and technologies Mathematics; computer and 225 0.8 290 1.0 175 0.7 310 1.0 information sciences Architecture; engineering; and 490 1.8 300 1.0 195 0.8 300 1.0 related technologies Agriculture; natural resources and 380 1.4 355 1.0 330 1.4 315 1.0 conservation Health and 3,670 13.4 5,755 14.8 3,395 14.0 3,910 12.8 related fields Personal; protective and transportation 1,155 4.2 1,260 3.2 880 3.6 1,075 3.5 services Other fields of study 0 0.0 25 0.1 15 0.1 0 0.0

= Most Common Post-Secondary = Least Common Post-Secondary Fields of Study in Grey - Females Fields of Study in Grey - Females

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 21 When compared with the Four County Region as a whole, the profile for men in Grey County reveal several general similarities. All four counties have Business; management and public administration, and Architecture; engineering; and related technologies in their top three. Just like their female counterparts, all four counties have Mathematics; computer and information sciences in their least common three fields of study.

Table 9: Post-Secondary Field of Study for Males for Bruce, Grey, Huron and Perth County, NHS 2011

Bruce Grey Huron Perth # % # % # % # %

Total population aged 15 years and over by major 27,385 100 37,350 100.0 23,500 100.0 29,170 100.0 field of study

No postsecondary certifi- 12,870 47.0 19,630 52.6 13,250 56.4 16,365 56.1 cate; diploma or degree Education 590 2.2 870 2.3 420 1.8 535 1.8 Visual and performing arts; and communications 225 0.8 675 1.8 175 0.7 570 2.0 technologies Humanities 325 1.2 690 1.9 370 1.6 510 1.8 Social and behavioural 450 1.6 1,000 2.7 370 1.6 470 1.6 sciences and law Business; management and 1,300 4.8 2,305 6.2 1,045 4.5 1,480 5.1 public administration Physical and life sciences 615 2.3 320 0.9 215 0.9 220 0.8 and technologies Mathematics; computer 360 1.3 415 1.1 225 1.0 365 1.3 and information sciences Architecture; engineering; 8,170 29.8 7,910 21.2 4,960 21.1 5,795 19.9 and related technologies Agriculture; natural 910 3.3 1,075 2.9 1,190 5.1 1,115 3.8 resources and conservation Health and related fields 535 2.0 995 2.7 580 2.5 755 2.6 Personal; protective and 1,035 3.7 1,460 3.9 700 3.0 990 3.4 transportation services

Other fields of study 0 0.0 0 0.0 0 0.0 0 0.0

= Most Common Post-Secondary = Least Common Post-Secondary Fields of Study in Grey - Males Fields of Study in Grey - Males

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 22 2.2.6 Personal Income by Education The personal income by education for both males and females was reviewed to get a sense of the differences that exist between education levels. Place of work data was examined to better understand the differences associated with the jobs that are located in Grey County. As discussed above, males have an overall higher income than females.

For males in Grey County, the average income was $38,714 though this varied significantly depending on education. For males that completed university, their average income was $69,332 which is about $45,000 more than a male who did not complete high school. Male college graduates have a slightly higher average employment income than apprenticeship or trades graduates ($45,963 vs. $39,064).

Table 10: Personal Income by Place of Work for Grey County, by Education for Males, NHS 20113

Population Less than High Appren- University, University 15 years high school ticeship College without or above and older school graduate or trade degree Total number of 20,005 4,025 6,370 2,590 3,940 460 2,620 males Number with 18,840 3,710 6,020 2,505 3,660 445 2,505 employment income Median employment $31,268 $15,476 $28,408 $40,157 $42,364 $26,401 $50,042 income Average employ- $38,714 $24,430 $32,649 $39,064 $45,963 $35,732 $64,052 ment income Number with wages 16,025 2,995 5,450 2,040 3,250 330 1,960 and salaries Median wages and $35,309 $16,516 $30,044 $45,332 $44,862 $30,009 $57,026 salaries Average wages and $40,845 $23,614 $33,121 $45,091 $49,941 $39,452 $69,332 salaries

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 23 For females in Grey County, the average income was $29,179, almost $10,000 less than their male counterparts. Again the average employment income depended on education, those with a higher education made a higher income. For females that completed university, their average income was $46,668 which is about $32,000 more than a female who did not complete high school. Female college graduates have a slightly higher average employment income than apprenticeship or trades graduates ($33,814 vs. $27,065). The average personal income for males with a university degree is approximately $17,000 higher than female university graduates.

Table 11: Personal Income by Place of Work for Grey County, by Education for Females, NHS 2011

Population Less than High Appren- University, University 15 years high school ticeship College without or above and older school graduate or trade degree Total number of 22,525 3,145 6,880 1,140 7,065 650 3,640 females Number with 20,905 2,850 6,280 1,050 6,665 590 3,460 employment income Median employment $23,960 $9,298 $18,683 $25,035 $31,612 $27,436 $40,633 income Average employment $29,179 $14,287 $21,659 $27,065 $33,814 $29,983 $46,668 income Number with wages 19,160 2,565 5,760 930 6,335 470 3,095 and salaries Median wages $25,207 $9,622 $20,499 $26,811 $33,360 $33,989 $44,079 and salaries Average wages $29,910 $14,633 $22,707 $27,700 $34,193 $36,250 $46,928 and salaries

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 24 2.3 Grey County Labour Force Profile 2.3.1 Labour Force Participation The overall labour force participation rate3 in Grey County is lower than the participation rate for Ontario. As shown in the table below the participation rate for Ontario in 2011 was 65.5%, the Grey County labour force participation rate fell from 64.6% in 2006 to 63% in 2011. From Tables 13 and 14, the labour force participation rate was 67.5% for men and 58.6% for women in 2011 for Grey County.

Table 12: Employment Participation Rate for all ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Participation 62 64 63 64.6 65.9 67.5 71 72.1 65.5 67.1 Rate

Table 13: Employment Participation Rate for Males ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Participation 67.1 69.9 67.5 69.8 71.4 74.3 76.2 78.1 69.9 72.5 Rate

Table 14: Employment Participation Rate for Females ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Participation 56.9 58.3 58.6 59.6 60.6 60.9 66 66.4 61.4 62.1 Rate

3 The Labour Force Participation Rate is the percentage of total population who are employed or looking for work.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 25 2.3.2 Employment Rate Grey County has the second lowest employment rate4 for the Four County Region, and a lower employment rate than Ontario. From Table 15, Grey County’s employment rate dropped between 2006 and 2011 from 61.2% to 58.3%. The decrease in employment rate between the two periods is common across the Four County Region.

Table 15: Employment Rate for age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Employment 57.9 60.6 58.3 61.2 62.2 64.5 67.1 69.5 60.1 62.8 Rate

In 2011, in Grey County, the employment rate for men was 62.3% and 54.5% for women, compared to Ontario’s 64.2% and 56.3 for men and women, respectively.

Table 16: Employment Rate for Males age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Employment 62.9 66.4 62.3 66.0 66.9 71.5 72.2 75.6 64.2 68.1 Rate

Table 17: Employment Rate for Females age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011

Bruce Grey Huron Perth Ontario

Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Employment 53 55.0 54.5 56.6 57.6 57.7 62.2 63.7 56.3 57.8 Rate

4 The Employment Rate is the percentage of the total population who are actually employed.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 26 2.3.3 Unemployment As shown in the tables below, the unemployment rate5 in 2011 for Grey County is highest among the Four County Region, but consistently lower in comparison to Ontario. Between 2006 and 2011, the Grey County unemployment rate increased from 5.2% to 7.4%.

Table 18: Unemployment Rate for age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 Bruce Grey Huron Perth Ontario Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Unemployment 6.5 5.3 7.4 5.2 5.7 4.4 5.5 3.7 8.3 6.4 Rate

In 2011, the unemployment rate for men in Grey County was 7.7% and 7.0% for women.

Table 19: Unemployment Rate for Males age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 Bruce Grey Huron Perth Ontario Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Unemployment 6.3 5.0 7.7 5.5 6.2 3.7 5.3 3.2 8.3 6.0 Rate

Table 20: Unemployment Rate for Females age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 Bruce Grey Huron Perth Ontario Year 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 Unemployment 6.8 5.6 7.0 4.9 5.1 5.2 5.8 4.2 8.3 6.8 Rate

2.3.4 Employment by Industrial Sector The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, the United States and Mexico. The classification system was created against the background of the North American Free Trade Agreement and was designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate analysis of the three economies. The NAICS classification system replaces the Standard Industrial Classification system which was used by Statistics Canada prior to the 2001 Census.

The NAICS organizes Canadian industries into distinguishable categories or classifications. At the greatest level of aggregation these industries are divided into 20 separate categories and are presented in Table 21. Grey had a fairly similar distribution of employment by industrial sector compared to Ontario. The top three sectors in Ontario in 2011 in terms of jobs were Retail Trade (10.94%), Manufacturing (10.16%), and Health Care and Social Assistance (10.08%). The Agricultural sector only accounted for 1.48% of the jobs in Ontario. The top three for Grey is highlighted in Table 21. 5 The Unemployment Rate is the percentage of the population not employed and not looking for work.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 27 Table 21: Population by Industrial Sector for all age 15 and over, NHS 2011 NAICS Industrial Bruce Grey Huron Perth Ontario Sector Jobs % Jobs % Jobs % Jobs % Jobs % Total 33,550 100 47,270 100 30,975 100 41,875 100.0 6,680,255 100 Agriculture; forestry; fishing 2,620 7.7 3,270 7 4,230 13.4 3,765 8.9 101,280 1.5 and hunting Mining; quarrying; and oil and gas 265 0.8 245 1 445 1.4 105 0.3 29,985 0.4 extraction Utilities 5,185 15.3 655 1 550 1.7 190 0.5 57,035 0.8 Construction 2,855 8.4 4,455 9 2,930 9.3 3,115 7.3 417,900 6.1

Manufacturing 2,470 7.3 5,410 11 3,705 11.8 7,395 17.4 697,565 10.2

Wholesale trade 940 2.8 1,290 3 1,280 4.1 1,965 4.6 305,030 4.4

Retail trade 3,715 10.9 5,265 11 2,900 9.2 4,500 10.6 751,200 10.9 Transportation 1,150 3.4 1,605 3 1,415 4.5 1,945 4.6 307,405 4.5 and warehousing Information and 350 1.0 575 1 335 1.1 520 1.2 178,720 2.6 cultural industries Finance and 780 2.3 1,365 3 745 2.4 1,590 3.7 364,415 5.3 insurance Real estate and 310 0.9 930 2 435 1.4 445 1.1 133,980 2.0 rental and leasing Professional; scientific and 1,510 4.4 2,180 5 980 3.1 1,415 3.3 511,020 7.4 technical services Management of companies and 0 0.0 0 0 0 0.0 40 0.1 6,525 0.1 enterprises Administrative and support; waste manage- 760 2.2 1,915 4 1,060 3.4 1,290 3.0 309,630 4.5 ment and remediation services Educational services 1,770 5.2 2,880 6 1,675 5.3 2,050 4.8 499,690 7.3 Health care and 3,200 9.4 6,250 13 3,490 11.1 4,845 11.4 692,130 10.1 social assistance Arts; entertainment and 650 1.9 1,200 3 400 1.3 1,040 2.5 144,065 2.1 recreation Accommodation 2,345 6.9 3,100 6 1,855 5.9 2,510 5.9 417,675 6.1 and food services Other services (except public 1,315 3.9 2,075 4 1,360 4.3 1,710 4.0 296,340 4.3 administration) Public 1,360 4.0 2,605 5 1,185 3.8 1,440 3.4 458,665 6.7 administration

= Top Three Industries in Grey

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 28 Table 22 highlights the top three industries for men in Grey County.

Table 22: Population by Industrial Sector for Males age 15 and over, NHS 2011

NAICS Industrial Bruce Grey Huron Perth Ontario Sector # % # % # % # % # % Total 18,365 100.0 25,220 100.0 16,770 100 22,230 100.0 3,542,030 100.0 Agriculture; forestry; 1,910 10.4 2,170 8.6 2,965 17.7 2,485 11.2 66,485 1.9 fishing and hunting Mining; quarrying; and oil and gas 250 1.4 230 0.9 395 2.4 95 0.4 25,650 0.7 extraction Utilities 3,980 21.7 595 2.4 495 3.0 100 0.5 42,685 1.2 Construction 2,510 13.7 3,905 15.5 2,585 15.4 2,820 12.7 369,300 10.4 Manufacturing 1,840 10.0 3,715 14.7 2,750 16.4 5,190 23.4 493,305 13.9 Wholesale trade 710 3.9 1,005 4.0 935 5.6 1,435 6.5 197,770 5.6 Retail trade 1,390 7.6 2,250 8.9 1,160 6.9 2,010 9.0 344,480 9.7 Transportation and 835 4.6 1,165 4.6 975 5.8 1,465 6.6 225,245 6.4 warehousing Information and 155 0.8 300 1.2 160 1.0 240 1.1 98,835 2.8 cultural industries Finance and 185 1.0 535 2.1 210 1.3 440 2.0 153,125 4.3 insurance Real estate and 115 0.6 495 2.0 255 1.5 165 0.7 72,835 2.1 rental and leasing Professional; scientific and technical 760 4.1 1,040 4.1 430 2.6 655 3.0 281,420 8.0 services Management of companies and 0 0.0 0 0.0 0 0.0 35 0.2 3,540 0.1 enterprises Administrative and support; waste management and 385 2.1 1,065 4.2 630 3.8 580 2.6 172,475 4.9 remediation services Educational services 450 2.5 945 3.8 370 2.2 575 2.6 162,765 4.6 Health care and 255 1.4 900 3.6 320 1.9 680 3.1 120,165 3.4 social assistance Arts; entertainment 280 1.5 620 2.5 130 0.8 470 2.1 75,035 2.1 and recreation Accommodation 830 4.5 1,195 4.7 460 2.7 970 4.4 177,240 5.0 and food services Other services (except public 635 3.5 1,110 4.4 690 4.1 715 3.2 133,795 3.8 administration) Public 680 3.7 1,600 6.3 535 3.2 815 3.7 236,655 6.7 administration

= Top Three Industries in Grey - Males

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 29 For women in Grey County, the top three industries are highlighted in Table 23.

Table 23: Population by Industrial Sector for Females age 15 and over, NHS 2011

NAICS Industrial Bruce Grey Huron Perth Ontario Sector # % # % # % # % # % Total 15,625 100.0 22,860 100.0 14,755 100.0 20,225 100.0 3,322,960 100.0 Agriculture; forestry; 715 4.6 1,100 4.8 1,265 8.6 1,285 6.4 34,800 1.1 fishing and hunting Mining; quarrying; and oil and gas 0 0.0 0 0.0 50 0.3 0 0.0 4,340 0.1 extraction Utilities 1,205 7.7 60 0.3 60 0.4 85 0.4 14,350 0.4 Construction 345 2.2 550 2.4 340 2.3 295 1.5 48,595 1.5 Manufacturing 630 4.0 1,690 7.4 955 6.5 2,200 10.9 204,260 6.2 Wholesale trade 235 1.5 285 1.3 340 2.3 530 2.6 107,260 3.2 Retail trade 2,325 14.9 3,015 13.2 1,745 11.8 2,485 12.3 406,720 12.2 Transportation and 315 2.0 440 1.9 440 3.0 485 2.4 82,160 2.5 warehousing Information and 200 1.3 275 1.2 175 1.2 285 1.4 79,885 2.4 cultural industries Finance and 585 3.7 830 3.6 530 3.6 1,150 5.7 211,290 6.4 insurance Real estate and 195 1.3 440 1.9 180 1.2 280 1.4 61,145 1.8 rental and leasing Professional; scientific and 750 4.8 1,135 5.0 550 3.7 755 3.7 229,600 6.9 technical services Management of companies and en- 0 0.0 0 0.0 0 0.0 0 0.0 2,990 0.1 terprises Administrative and support; waste 375 2.4 845 3.7 435 3.0 705 3.5 137,155 4.1 management and remediation services Educational services 1,320 8.5 1,935 8.5 1,300 8.8 1,480 7.3 336,925 10.1 Health care and 2,945 18.9 5,355 23.4 3,170 21.5 4,165 20.6 571,965 17.2 social assistance Arts; entertainment 370 2.4 590 2.6 275 1.9 570 2.8 69,030 2.1 and recreation Accommodation and 1,515 9.7 1,910 8.4 1,395 9.5 1,545 7.6 240,430 7.2 food services Other services (except public adminis- 680 4.4 965 4.2 665 4.5 995 4.9 162,550 4.9 tration) Public 680 4.4 1,005 4.4 650 4.4 625 3.1 222,015 6.7 administration

= Top Three Industries in Grey - Females

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 30 The employment data provided above reflects employment in jobs that are located within Grey County as well as jobs that residents of Grey County commute to outside the county. The following table presents the employment by industry based only on those jobs located within Grey County (place of work in Grey County) and provides a more refined profile of the workforce employed in the county.

Table 24: Population by Place of Work by Industrial Sector for all age 15 and over, NHS 2011

Bruce Grey Huron Perth NAICS Industrial Sector # % # % # % # % Total 33,330 100 42,530 100 26,685 100 41,825 100 Agriculture; forestry; 2,635 7.9 3,200 7.5 4,055 15.2 3,825 9.1 fishing and hunting Mining; quarrying; and oil and gas 310 0.9 130 0.3 460 1.7 80 0.2 extraction Utilities 6,785 20.4 140 0.3 100 0.4 135 0.3 Construction 2,175 6.5 1,770 4.2 1,530 5.7 1,885 4.5 Manufacturing 1,705 5.1 5,125 12.1 2,980 11.2 8,885 21.2 Wholesale trade 870 2.6 1,045 2.5 1,010 3.8 1,905 4.6 Retail trade 3,545 10.6 5,700 13.4 3,030 11.4 4,580 11.0 Transportation and 625 1.9 1,120 2.6 1,080 4.0 1,500 3.6 warehousing Information and cultural industries 275 0.8 530 1.2 245 0.9 550 1.3 Finance and insurance 755 2.3 1,210 2.8 715 2.7 1,540 3.7 Real estate and rental and leasing 340 1.0 835 2.0 350 1.3 470 1.1 Professional; scientific and technical 1,575 4.7 1,850 4.3 780 2.9 1,325 3.2 services Management of companies and 0 0.0 0 0.0 0 0.0 55 0.1 enterprises Administrative and support; waste 625 1.9 1,275 3.0 670 2.5 1,170 2.8 management, remediation services Educational services 1,805 5.4 2,500 5.9 1,550 5.8 1,815 4.3 Health care and social assistance 3,015 9.0 5,900 13.9 3,385 12.7 4,985 11.9 Arts; entertainment and recreation 695 2.1 1,785 4.2 520 1.9 1,155 2.8 Accommodation and food services 2,795 8.4 4,250 10.0 2,000 7.5 3,065 7.3 Other services (except 1,320 4.0 1,895 4.5 1,270 4.8 1,500 3.6 public administration) Public administration 1,485 4.5 2,240 5.3 935 3.5 1,405 3.4

= Top Three Employment Sectors in Grey

Although Construction accounts for about 9.3% of the jobs that Grey County (Table 21), three residents are employed in construction only accounts for about 4.2% of the jobs that are located in the county.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 31 Location Quotient A further assessment of industrial specialization in Grey County can be obtained using the Location Quotient. Economic analysts have found the Location Quotient (LQ) to be a useful tool in determining which sectors of the economy are more specialized than others (Bendavid-Val, 1991, p.73). The term ‘specialized’ in this instance refers to the relative size or presence of an industrial activity. The LQ is essentially a ratio of ratios. In assessing industrial sector specialization, the regional share of a particular industrial sector is compared to the provincial share in the sector. Using the Agriculture sector in Grey County as an example, the LQ formula for 2011 appears as follows:

LQ = number of agriculture jobs in Grey ÷ number of agriculture jobs in Ontario total number of jobs in Grey ÷ total number of jobs in Ontario

LQ = ( 3,270 ÷ 47,270 ) ÷ ( 101,280 ÷ 6,680,255 ) = 4.6

For the purpose of interpreting the LQ, the LQ has a base value of one. An LQ of one suggests that the County and the province are specialized to an equal degree in the chosen industry sector. If the LQ for the County is greater than one, it indicates that the County has a higher degree of specialization in the industrial sector than the province. An LQ of less than one indicates that the industrial sector is less specialized in the County than it is for the province.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 32 Table 25 presents the LQs for Bruce, Grey, Huron and Perth counties using the data presented in Table 21. Based on 2011 LQ calculations, the economy of Grey County is specialized in several industrial sectors including Agriculture, Utilities and Construction.

Table 25: Location Quotient for Bruce, Grey, Huron and Perth Counties, NHS 2011 NAICS Industrial Sector Bruce Grey Huron Perth Agriculture; forestry; fishing and hunting 5.2 4.6 5.9 9.0 Mining; quarrying; and oil and gas extraction 1.8 1.2 0.6 3.2 Utilities 18.1 1.6 0.5 2.1 Construction 1.4 1.5 1.2 1.5 Manufacturing 0.7 1.1 1.7 1.1

Wholesale trade 0.6 0.6 1.0 0.9 Retail trade 1.0 1.0 1.0 0.8 Transportation and warehousing 0.7 0.7 1.0 1.0 Information and cultural industries 0.4 0.5 0.5 0.4 Finance and insurance 0.4 0.5 0.7 0.4 Real estate and rental and leasing 0.5 1.0 0.5 0.7 Professional; scientific and technical services 0.6 0.6 0.4 0.4 Management of companies and enterprises 0.0 0.0 1.0 0.0 Administrative and support; waste management 0.5 0.9 0.7 0.7 and remediation services Educational services 0.7 0.8 0.7 0.7 Health care and social assistance 0.9 1.3 1.1 1.1 Arts; entertainment and recreation 0.9 1.2 1.2 0.6 Accommodation and food services 1.1 1.0 1.0 1.0 Other services (except public administration) 0.9 1.0 0.9 1.0 Public administration 0.6 0.8 0.5 0.6

2.3.5 Labour Force by Occupation As defined by Statistics Canada, an “occupation” refers to the kind of work performed by persons during the week of Sunday, May 1 to Saturday, May 7, 2011, as determined by their kind of work and the description of the main activities in their job. The following analysis focuses on the 10 broad occupational categories that are formed on the basis of education, training or skill level required to enter the job, as well as the kind of work performed, as determined by the tasks, duties and responsibilities of the occupation.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 33 Table 26: Labour Force in Bruce, Grey, Huron and Perth County, and Ontario by Occupation, NHS 2011

Bruce Grey Huron Perth Ontario # % # % # % # % # % All Occupations 33,560 100 47,300 100 30,995 100 41,875 100 6,680,250 100 Management 4,670 13.9 5,895 12.5 4,420 14.3 5,130 12.3 770,580 11.5 occupations Business, finance and administration 4,195 12.5 6,150 13 3,760 12.1 5,600 13.4 1,138,330 17 occupations Natural and applied sciences and related 1,765 5.3 1,755 3.7 875 2.8 1,525 3.6 494,500 7.4 occupations Health occupations 1,915 5.7 3,570 7.5 2,050 6.6 2,805 6.7 392,695 5.9

Occupations in education, law and 3,000 8.9 4,705 9.9 2,945 9.5 3,560 8.5 801,465 12 social, community and government services

Occupations in art, culture, recreation 650 1.9 1,115 2.4 480 1.5 1,075 2.6 206,420 3.1 and sport Sales and service 7,220 21.5 10,565 22.3 5,880 19 8,840 21.1 1,550,260 23.2 occupations Trades, transport and equipment operators 5,740 17.1 8,700 18.4 6,145 19.8 7,620 18.2 868,515 13 and related occupations

Natural resources, agriculture and related 1,355 4 1,840 3.9 2,135 6.9 1,660 4 106,810 1.6 production occupations Occupations in manu- 3,060 9.1 3,005 6.4 2,310 7.5 4,065 9.7 350,685 5.2 facturing and utilities

= Top Three Occupational Categories in Grey

Like Grey, the top occupation in Ontario in 2011 was Sales and service at 23.2%. The remaining leading occupations at the provincial level were: • Business, finance and administration (17%) • Trades, transport and equipment operators and related occupations (13%)

The Grey County labour force by occupation profile is fairly comparable to the Four County Region as a whole. All four counties had both Sales and service and Trades, transport and equipment operators and related occupations in their top three ranked occupations.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 34 2.3.5.1 Male Labour Force by Occupation Table 27: Male Labour Force in Bruce, Grey, Huron and Perth County, and Ontario by Occupation, NHS 2011 Bruce Grey Huron Perth Ontario # % # % # % # % # % All Occupations 18,165 100 24,850 100 16,450 100 21,940 100 3,452,795 100 Management 2,910 16 3,895 15.7 2,900 17.6 3,245 14.8 474,655 13.7 occupations Business, finance and administration 935 5.1 1,510 6.1 945 5.7 1,635 7.5 352,505 10.2 occupations Natural and applied sciences and related 1,405 7.7 1,370 5.5 635 3.9 1,190 5.4 384,345 11.1 occupations Health occupations 340 1.9 455 1.8 195 1.2 450 2.1 78,330 2.3 Occupations in education, law and social, community 805 4.4 1,590 6.4 720 4.4 985 4.5 264,570 7.7 and government services Occupations in art, culture, recreation 210 1.2 515 2.1 175 1.1 510 2.3 96,055 2.8 and sport Sales and service 2,690 14.8 4,135 16.6 1,850 11.2 3,190 14.5 673,880 19.5 occupations Trades, transport and equipment 5,455 30 8,150 32.8 5,755 35 7,135 32.5 812,280 23.5 operators and related occupations Natural resources, agriculture and 1,060 5.8 1,225 4.9 1,590 9.7 1,075 4.9 82,610 2.4 related production occupations Occupations in manufacturing 2,355 13 2,010 8.1 1,680 10.2 2,515 11.5 233,565 6.8 and utilities

= Top Three Occupational Categories in Grey - Males

Like Grey, the top occupation for males in Ontario in 2011 was Trades, transport and equipment operators, though with a smaller proportion of the population at 23.5%. The remaining leading occupations at the provincial level were: • Sales and service (19.5%) • Management (13.7%)

The Grey County male labour force by occupation profile is very comparable to the Four County Region as a whole. All four counties had Trades, transport and equipment operators, Sales and service and Management in their top three ranked occupations.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 35 2.3.5.2 Female Labour Force by Occupation Table 28: Female Labour Force in Bruce, Grey, Huron and Perth County and Ontario by Occupation, NHS 2011

Bruce Grey Huron Perth Ontario # % # % # % # % # % All Occupations 15,400 100 22,445 100 14,545 100 19,940 100 3,227,450 100 Management 1,760 11.4 1,995 8.9 1,525 10.5 1,890 9.5 295,920 9.2 occupations Business, finance and administration 3,255 21.1 4,640 20.7 2,810 19.3 3,960 19.9 785,825 24.3 occupations Natural and applied sciences and related 365 2.4 390 1.7 235 1.6 335 1.7 110,150 3.4 occupations Health occupations 1,575 10.2 3,120 13.9 1,855 12.8 2,350 11.8 314,370 9.7 Occupations in education, law and

TIE social, community 2,200 14.3 3,115 13.9 2,225 15.3 2,580 12.9 536,895 16.6 and government services Occupations in art, culture, recreation 440 2.9 600 2.7 300 2.1 570 2.9 110,370 3.4 and sport Sales and service 4,525 29.4 6,425 28.6 4,030 27.7 5,645 28.3 876,380 27.2 occupations Trades, transport and equipment 285 1.9 555 2.5 395 2.7 485 2.4 56,230 1.7 operators and related occupations Natural resources, agriculture and 295 1.9 615 2.7 540 3.7 585 2.9 24,200 0.7 related production occupations Occupations in manufacturing 705 4.6 990 4.4 63 0.4 1,550 7.8 117,115 3.6 and utilities

= Top Three Occupational Categories in Grey- Females

Like Grey, the top occupation for females in Ontario in 2011 was sales and service with 27.2% of the occupations reported by women in 2011. The remaining leading occupations at the provincial level were: • Business, finance and administration (24.3%) • Education, law and social, community and government services (16.6%)

The Grey County female labour force by occupation profile is very comparable to the Four County Region as a whole. All four counties had Sales and service; Business, finance and administration; and, Education, law and social, community and government services in their top three ranked occupations. Grey County had the highest proportion of females employed in a health occupation.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 36 2.3.6 Personal Income by Industrial Sector An individual’s income can vary significantly depending upon which industry he or she is employed. In Grey County, the highest average employment income by place work (jobs located in Grey County) was for those in the Mining, quarrying, and oil and gas extraction sector with an average income of $68,189. The next closest industry was Utilities with $66,728 and Finance and insurance with $50,137 on average per year. The lowest paying industries on average for those working in Grey County are Arts, entertainment and recreation ($21,800), Agriculture ($20,307) and Accommodation and food services ($18,047).

Table 29: Personal Income by Place of Work, by Industry, NHS 2011

Median Average With Median Average Total With em- employ- employ- wages wages wages Employ- ployment ment ment and and and ment income income income salaries salaries salaries All industries 42,530 39,740 $26,990 $33,699 35,180 $29,184 $34,890 Agriculture, forestry, 3,200 2,825 $11,958 $20,307 1,595 $15,913 $21,100 fishing and hunting Mining, quarrying, and oil 130 125 $30,002 $68,189 130 $29,099 $57,883 and gas extraction Utilities 140 140 $59,451 $66,728 140 $59,451 $66,842 Construction 1,770 1,665 $32,878 $40,067 1,345 $35,324 $41,406 Manufacturing 5,125 4,875 $35,288 $39,560 4,570 $37,316 $41,051 Wholesale trade 1,045 975 $38,993 $48,015 855 $39,714 $51,582 Retail trade 5,700 5,290 $15,499 $22,165 4,995 $15,777 $22,532 Transportation and 1,120 1,030 $25,301 $34,095 905 $29,130 $37,728 warehousing Information and cultural 530 490 $30,735 $34,994 440 $31,575 $35,693 industries Finance and insurance 1,210 1,130 $39,988 $50,137 970 $42,708 $51,732 Real estate and rental and 835 720 $22,180 $25,056 560 $22,270 $26,025 leasing Professional, scientific and 1,850 1,730 $30,167 $39,457 1,195 $34,462 $41,419 technical services Management of companies 0 0 $0 $0 0 $0 $0 and enterprises Administrative and support, waste management 1,275 1,210 $29,356 $32,072 1,120 $30,210 $32,785 and remediation services Educational services 2,500 2,385 $40,440 $46,233 2,295 $42,045 $48,002 Health care and social 5,900 5,660 $37,021 $43,360 5,295 $38,210 $42,363 assistance Arts, entertainment and 1,785 1,655 $9,808 $21,800 1,565 $8,917 $22,305 recreation Accommodation and food 4,250 3,980 $11,545 $18,047 3,825 $11,688 $18,758 services Other services (except 1,895 1,735 $18,058 $23,177 1,310 $21,925 $25,157 public administration) Public administration 2,240 2,105 $50,158 $48,501 2,065 $50,884 $49,333

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 37 2.4 Summary The purpose of the profile is to provide background information on the general socio-economic status in Grey County. The profile compliments research into present and future skills gaps in the Four County Region. The profile was compiled using data from the 2006 Statistics Canada Population Census and the 2011 Statistics Canada National Household Survey.

Between 2006 and 2011, Grey County experienced a slight population increase of 0.2%. In comparison to Ontario as a whole, Grey County has an older population with a median age of 47.8. The top three ethnic backgrounds of Grey County residents in 2011 was English, Canadian and Scottish.

The average household income for Grey County in 2011 was $56,518 which represents the lowest average of the Four County Region and is about $10,000 lower than the provincial average. The average personal income for Grey County in 2011 was $34,314 which is comparable to Huron and Perth counties but about $8,000 lower than the average for Bruce County and Ontario as a whole.

The top three fields of study for women in Grey County included: Health professions and related fields; Business; management and public administration; and, Education. For men the top three fields of study were: Architecture; engineering; and related technologies; Business; management and public administration; and, Personal; protective and transportation services.

The employment participation rate in Grey County fell from 61.2% in 2006 to 58.3% in 2011. While the unemployment rate increased from 5.2% to 7.4% over the same period.

The top three industries by employment in 2011 by place of work in Grey County were: Health Care and Social Assistance, Retail, and Manufacturing, very similar observations compared to the previous labour market studies.

The leading occupations for males in Grey County in 2011 include Trades, transport and equipment operators and related occupations; Sales and service; and Management occupations. The leading occupations for females in Grey County in 2011 include Sales and service; Business, finance and administration; Health; and Education, law and social, community and government services.

SECTION 2: GREY LABOUR MARKET PROFILE THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 38 Fact Sheet - Grey County High School Student Profile

This fact sheet focuses on the key findings gathered from a survey of 378 Grade 12 students in Grey County. The survey was almost evenly split between males (47.4%) and females (52.6%) and the large majority of respondents were 17 years old.

Where possible comparisons to the study completed in 2005 were made. It should be noted that the 2005 high school student survey included Grade 10, 11 and 12 students and the 2013 high school student survey only surveyed Grade 12 students.

0 20 40 60 80 100

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 39 100

0 30 60 90 120 150

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 40 0 10 20 30 40 50 60 70 80

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 41 3.0 Grey High School Student Survey

3.1 Introduction The economic viability and growth of communities is dependent on a successful match between employers offering quality job opportunities and a skilled workforce that is able to respond to the corresponding labour requirements. Achieving this balance is consistently challenged in rural regions of Ontario where there is often a concern that a rural community will lose its population, particularly the youth population, to regions that are able to offer more choice in employment and higher salaries.

An inventory of the available skills within the local labour pool is an invaluable tool for strategic planning and economic development as identified shortcomings can be addressed through relevant training initiatives and recognized strengths can be used to attract new employers. With a view towards sustainability it is critical to incorporate the youth of the region into the study. The Grade 12 students were surveyed to identify the current skill level of the youth, their expectations regarding skill improvement through education as well as future employment.

3.2 Methodology 3.2.1 Survey Design The questionnaire used for the High School student survey was originally developed by Harry Cummings and colleagues for two similar projects in the counties of Bruce and Grey and the counties of Huron and Perth in Southern Ontario (Bruce Grey Huron Perth Georgian Triangle Training Board (BGHPGTTB), 2005). The original survey tool was found to be a useful tool for gathering pertinent data on high school students and it was adopted for the 2013 study to allow for the results from the two periods to be directly compared.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 42 The main research categories covered by the questionnaire focus on the current academic achievements of students, their involvement in extracurricular activities, their involvement in volunteer activities, their involvement in part-time and summer work activities, their involvement in school co-op programs, their level of skills, their plans for future education / training, and their plans for a future career.

The questionnaire provides information on the students’ current skills by firstly asking about their averages overall and in three major fields of study (English, math, science), and then by asking about the level of study of those fields (e.g. university preparation, college preparation, or workplace preparation). The amount of credits obtained in various others fields also provides information as to the types of skills they learned. Additionally, the students rated themselves on various skills including communication, analytical, teamwork, leadership, computer, etc. The combination of self-assessed skilled ratings with the number of credits completed, the level of classes taken and the average mark in class provide a representative picture of the skills the students have learned in high school.

Questions regarding the students’ work history, which includes volunteer, paid part-time, paid summer-time, and/or family business work provide additional details on the skills they currently have as well as where they tend to obtain those skills. The students’ recent employment record provides insight into the types of employments skills they have learned (i.e.: management skills, welding skills, customer service skills, etc.).

Information regarding the students’ future educational and employment plans were collected with direct questions regarding the post-secondary institutions they plan on attending, their future field of study, and the industry and occupation in which they expect to be. Students were also asked to identify their reasons for choosing such fields of work or study and to indicate whom or what influenced their decisions and aspirations.

Finally, students were asked to indicate whether they expect to continue to live and work in the county and the reasons motivating them to stay in or leave the county.

3.2.2 Population The future labour force for a region is composed of the current work force, minus those who die or leave, plus new entrants from the school system or via in-migration. The youth component would even include unborn children as they too may grow up to work in the area. Obviously, it would be quite impossible to representatively sample such a population. Therefore, the youth population studied here is that of all grade 12 students enrolled at 6 public high schools in Grey County.

Overall, there are 1,329 grade 12 students enrolled in 5 high schools from the Bluewater District School Board (BWDSB) and one high school from the Bruce Grey Catholic District School Board (BGCDSB). Due to time, monetary and logistical constraints, the other grades and the private schools were not part of the sample frame.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 43 Table 30: Surveyed Secondary Schools School Location School Board Georgian Bay Secondary School Meaford BWDSB Grey Highlands Secondary School Flesherton BWDSB John Diefenbaker Secondary School Hanover BWDSB Owen Sound Collegiate and Vocational Institute Owen Sound BWDSB St. Mary’s High School Owen Sound BWDSB West Hill Secondary School Owen Sound BWDSB

3.2.3 Sampling Strategy For the sample to be statistically representative of the population of 1,329 students and to have a 5% confidence interval and a 95% confidence level, it is technically necessary to obtain approximately 298 valid responses from randomly selected students in the sample frame.6 The sample would have to be drawn from an all-inclusive list of students. Given the administrative difficulties of delivering questionnaires to students randomly selected from all classes, the researchers used cluster sampling using the class as the unit to be sampled. For such a cluster sample then, a design factor of 1.5 is applied and a sample of 447 students is necessary.

Cluster sampling affords a few benefits. Mainly, it makes the administration of the survey much simpler since the researchers only have to address classes rather than trying to contact 298 individual students. Additionally, the questionnaire can be administered through regular class times by the instructor for that class rather than having to make alternate arrangements for a few students from various classes to complete the questionnaire.

The challenge is to select classes that will reach the greatest number of students while not sampling any students twice. Duplicating students would endanger the representativeness of the sample. To circumvent this, the researchers chose classes that did not overlap in roster. That is, the chosen classes were clearly separate so that it would be nearly impossible for a student to be in two sampled classes. Similar to the approach used in the previous Huron Perth Skills Gap Study, the solution was to select only English Grade 12 classes and to administer the survey to all students in these classes.

3.2.4 Survey Administration Starting in June 2013, formal letters of introduction were submitted to officials with the Bluewater District School Board and the Bruce Grey Catholic District School Board to obtain their permission to carry out the survey. In September, the individual school principals were alerted of the survey via email and invited to participate. At this time the principals were asked to confirm their participation in the survey and to provide details on the number of Grade 12 English classes being offered in the fall semester, the names of

6 A confidence level of 95% is typical for social science research. A 95% level of confidence ±5% error in the results means that if you asked a question from a survey 100 times, 95 of those times the percentage of people giving a particular answer would be within 5 points of the percentage who gave that same answer in the initial survey. For example, in a survey where 30% of the respondents chose Sunday as their favorite day of the week we can state that there is a 95% chance that between 25% and 35% of the population would select Sunday as their favorite day. Conversely, there is a 5% chance that fewer than 25% or more than 35% of the population would select Sunday as their favorite day.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 44 the teachers instructing these classes and the number of students in each of the classes. The goal was to administer the survey in mid to late October to avoid a conflict with busy teacher schedules at the start of the school semester.

In early October the surveys were printed by HCA and a schedule was developed with each of the schools to allow for an HCA representative to visit and drop off the surveys and provide instructions on the in-class administration of the survey. During the week of October 21, a member of the HCA research team visited all 6 high schools and met with school officials / teachers to review the goals of the survey and the process for administering it. At that time they also received all the necessary copies of the survey and were asked to have them completed over the next 2-3 weeks. They were asked to return the completed surveys to the HCA Guelph office via courier.

By the 1st week of November, all of the schools had completed and couriered the surveys to HCA. All of the survey results were entered into an electronic data base by members of the HCA research team using a Survey Monkey platform. The data was then transferred to an Excel data base for data cleaning and further coding and then finally transferred to an SPSS data base for statistical analysis.

3.3 Results 3.3.1 Response Rates A total of 476 survey questionnaires were distributed to the 6 high schools in Grey County and 378 valid responses were returned for an overall response rate of 79%. It important to recognize that the survey was voluntary and response rates varied across the schools.

As noted earlier, at least 447 responses were necessary to provide a 95% confidence level with a +/-5% confidence interval. Although the 378 valid responses is below the target of 447, it still provides a confidence level of 95% with a ±6% confidence interval.

Table 31: Response Rate by Secondary School

Total # of Total # of Response High School valid surveys students Rate completed

Georgian Bay Secondary School 70 42 60.0% Grey Highlands Secondary School 87 75 86.2% John Diefenbaker Secondary School 53 43 81.1% Owen Sound Collegiate and Vocational Institute 55 27 49.1% St. Mary’s High School 74 59 79.7% West Hill Secondary School 137 132 96.4% Total 476 378 79.4%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 45 3.3.2 Respondent Profiles The distribution of gender and age of the high school student respondents can be found in Table 31 and 32, below. In all counties, there were more female than male respondents, with the exception of Bruce County. In Grey County, 47.4% of the respondents were males and 52.6% were female. As expected, the majority of respondents are 17 years old. In Grey County, 88.9% of the respondents reported being 17 years old; another 8.2% are 18 years old.

Table 32: Sample Population by Gender Bruce Grey Huron Perth Total Gender # % # % # % # % # % Male 137 59.8% 174 47.4% 166 45.4% 191 47.3% 668 48.9% Female 92 40.2% 193 52.6% 200 54.6% 213 52.7% 698 51.1% Total 229 100.0% 367 100.0% 366 100.0% 404 100.0% 1,366 100.0%

Table 33: Sample Population by Age Bruce Grey Huron Perth Total Age # % # % # % # % # % 16 3 1.3% 6 1.6% 34 9.2% 7 1.7% 50 3.6% 17 201 86.6% 327 88.9% 307 83.0% 360 89.1% 1,195 87.0% 18 27 11.6% 30 8.2% 22 5.9% 37 9.2% 116 8.4% 19 0 0.0% 4 1.1% 4 1.1% 0 0.0% 8 0.6% 20 0 0.0% 0 0.0% 2 0.5% 0 0.0% 2 0.1% 21 1 0.4% 0 0.0% 1 0.3% 0 0.0% 2 0.1% 23 0 0.0% 1 0.3% 0 0.0% 0 0.0% 1 0.1% Total 232 100.0% 368 100.0% 370 100.0% 404 100.0% 1,374 100.0%

3.3.3 Courses The types of courses and the average grade for these courses was a focus of the survey. The type of course (i.e. university, college, and workplace) is an indicator of the pathway the student is likely to take as they pursue their career. The self-reported average for all classes, English, math and science courses was reviewed as an indicator of academic strengths. English develops the basics of reading and writing, math builds numeracy ability and science expands the capacity to analyze, make decisions and solve problems. Self-reported measurements of achievement within these courses are reflective of the students’ skills.

The self-reported average for all classes in the last school year was quite high, but higher for females than males across all four counties In Grey, the average for all classes in the last school year was 76.7% for males and 78.8% for females. Students reported English as the highest average, followed by Math and then Science with averages of 77.6%, 76.9% and 75.9% respectively.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 46 Table 34: Average Course Marks by Gender

Average for Average for Average for Overall current or current or current or average for most recently most recently County Gender most recently all classes last completed completed completed school year English Science Math course course course # 131 129 130 132 Male Average 77.3 75.0 76.2 73.9 # 88 87 89 87 Bruce Female Average 79.1 79.0 74.7 76.3 # 219 216 219 219 Total Average 78.0 76.6 75.6 74.8 # 158 153 158 156 Male Average 76.7 76.2 77.1 76.8 # 176 167 180 183 Grey Female Average 78.8 78.9 76.8 75.2 # 334 320 338 339 Total Average 77.8 77.6 76.9 75.9 # 159 145 153 149 Male Average 75.8 72.8 76.2 74.5 # 184 181 184 187 Huron Female Average 78.0 75.8 76.3 75.9 # 343 326 337 336 Total Average 77.0 74.5 76.3 75.3 # 185 179 186 181 Male Average 77.7 75.2 74.9 76.1 # 207 204 209 211 Perth Female Average 80.0 79.0 74.5 77.3 # 392 383 395 392 Total Average 78.9 77.2 74.7 76.7 # 633 606 627 618 Male Average 76.9 74.8 76.1 75.4 # 655 639 662 668 Total Female Average 79.0 78.1 75.7 76.2 # 1,288 1,245 1,289 1,286 Total Average 78.0 76.5 75.8 75.8

In addition to the core courses (English, math and science) the average number of credits for additional courses for arts, business studies, Canadian and world studies, technology and computer studies courses were also reviewed. Enrollment and achievement in these courses are an indicator of the interest and strengths of the students - especially as many are not required but are elective. In Grey County students

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 47 are most likely to be enrolled in Canadian and world studies than any other of the additional classes, 312 students reported as being enrolled in these courses such as geography and history. Males in Grey tend to favour technology education courses which would include wood working, metal, and automotive repair courses. Females are more likely to be engaged in arts courses including visual arts, drama and music. Perhaps surprisingly, the least common was computer studies.

Table 35: Average Number of Credits for Elective Courses by Gender Total Total Total Total credits Total credits credits credits County Gender Canadian credits arts business tech computer and world studies education studies studies # 132 89 127 116 54 Male Average 2.4 1.5 2.7 3.2 1.4 # 86 53 85 62 31 Bruce Female Average 3.4 1.6 2.7 1.8 1.0 # 218 142 212 178 85 Total Average 2.8 1.5 2.7 2.7 1.3 # 144 88 151 148 70 Male Average 2.0 1.5 2.6 3.6 1.7 # 172 104 170 142 52 Grey Female Average 3.1 1.3 2.7 2.4 0.9 # 316 192 321 290 122 Total Average 2.6 1.4 2.7 3.0 1.3 # 132 82 135 141 36 Male Average 1.9 1.9 2.4 4.2 1.5 # 172 101 174 145 29 Huron Female Average 2.9 1.3 2.7 2.4 1.0 # 304 183 309 286 65 Total Average 2.5 1.6 2.6 3.3 1.3 # 150 113 153 168 71 Male Average 2.0 1.8 2.7 3.7 1.5 # 180 111 178 148 42 Perth Female Average 2.8 1.4 2.6 2.3 0.8 # 330 224 331 316 113 Total Average 2.5 1.6 2.6 3.0 1.2 # 558 372 566 573 231 Male Average 2.1 1.7 2.6 3.7 1.5 # 610 369 607 497 154 Total Female Average 3.0 1.4 2.7 2.3 0.9 # 1,168 741 1,173 1,070 385 Total Average 2.6 1.5 2.6 3.0 1.3

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 48 The level of the English course for Grey County is below, to see the comparison to all four counties see Appendices. In Grey County, 38.8% of males have completed or were enrolled in a college level English course. Another 35.9% of males have completed or were enrolled in a university level English course, 4.7% reported workplace level. Females were more likely to be enrolled in a university level English course than males, with 48.9% of the female respondents. Another 31.1% of the female respondents reported having completed or been enrolled in a college level English course.

The 8.3% and 9.2% of respondents reported applied or academic level courses, respectively, likely represents misreporting by the students as Grade 12 students should be enrolled in either a university, college, workplace or open level English class.

Table 36: Highest Level of English Course Completed, by Gender Gender Total County Course Level Male Female # % # % # % Academic 14 8.2% 19 10.0% 33 9.2% Applied 18 10.6% 12 6.3% 30 8.3% University 61 35.9% 93 48.9% 154 42.8% Grey College 66 38.8% 59 31.1% 125 34.7% Workplace 8 4.7% 4 2.1% 12 3.3% Open 3 1.8% 3 1.6% 6 1.7% Total 170 100.0% 190 100.0% 360 100.0% *For full Four County results refer to Appendix Table A1

The level of the math course for Grey County is below (to see the comparison to all four counties see Appendices). In Grey County, more students have completed or enrolled in a university level math course than any other level; 33% of the female respondents and 29.6% of the male respondents reported university level math course. College level math was second most common level for both males and females.

Table 37: Highest Level of Math Course Completed, by Gender Gender Total County Course Level Male Female # % # % # % Academic 15 8.9% 15 7.9% 30 8.3% Applied 24 14.2% 23 12.0% 47 13.1% University 50 29.6% 63 33.0% 113 31.4% Grey College 46 27.2% 50 26.2% 96 26.7% Workplace 15 8.9% 16 8.4% 31 8.6% Open 19 11.2% 24 12.6% 43 11.9% Total 169 100.0% 191 100.0% 360 100.0% *For full Four County results refer to Appendix Table A2 The level of the science course for Grey County is below (to see the comparison to all four counties see

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 49 Appendices). In Grey County, more students have completed or enrolled in a university level science course than any other level; 37% of the female respondents and 33.7% of the male respondents reported university level science course. For males, applied was the second most common level of science course completed with 24.5% of the male respondents. This indicates that many have not continued in science past the Ontario Secondary School Diploma (OSSD) requirements to graduate. For females, college was the second most common level of science course completed with 21.4% of the female respondents.

Table 38: Highest Level of Science Course Completed, by Gender Gender Total County Course Level Male Female # % # % # % Academic 23 14.1% 34 17.7% 57 16.1% Applied 40 24.5% 37 19.3% 77 21.7% University 55 33.7% 71 37.0% 126 35.5% Grey College 32 19.6% 41 21.4% 73 20.6% Workplace 10 6.1% 7 3.6% 17 4.8% Open 3 1.8% 2 1.0% 5 1.4% Total 163 100.0% 192 100.0% 355 100.0% *For full Four County results refer to Appendix Table A3

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 50 3.3.4 Extra-Curricular Activities Participation in extra-curricular activities outside of regular classes can assist in developing a wide range of skills for students that often cannot be taught in a classroom, but are learned through experience. Interacting in a group setting builds social and interpersonal skills, teamwork and collaboration. Some extra-curricular activities develop and enhance leadership qualities in a participant in addition to the physical or artistic skills that may be more apparent. Extra-curricular activities can provide insight into the skills and interests of the students outside of their academic realm. In all four counties the majority of students are engaged in extra-curricular activities. In Grey County, 61.6% of males and 63.4% of females participate in extra-curricular activities. The time spent by the student per week on extra-curricular activities is significant. For all students across the Four County Region the average number of hours spent participating in extra-curricular activities is 8.2 hours. In Grey County, males spend 7.8 hours per week and females 8 hours per week engaged in extra-curricular activities.

Table 39: Extra-Curricular Participation by Gender Gender Total County Male Female # % # % # % Yes 103 75.2% 71 77.2% 174 76.0% Bruce No 34 24.8% 21 22.8% 55 24.0% Total 137 100.0% 92 100.0% 229 100.0% Yes 106 61.6% 121 63.4% 227 62.5% Grey No 66 38.4% 70 36.6% 136 37.5% Total 172 100.0% 191 100.0% 363 100.0% Yes 103 62.4% 140 70.4% 243 66.8% Huron No 62 37.6% 59 29.6% 121 33.2% Total 165 100.0% 199 100.0% 364 100.0% Yes 129 67.9% 147 69.0% 276 68.5% Perth No 61 32.1% 66 31.0% 127 31.5% Total 190 100.0% 213 100.0% 403 100.0% Yes 441 66.4% 479 68.9% 920 67.7% Total No 223 33.6% 216 31.1% 439 32.3% Total 664 100.0% 695 100.0% 1,359 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 51 Table 40: Average Number of Hours per Week Spent on Extra-Curricular Activities, by Gender

County Male Female Total

# 99 68 167 Bruce Average 9.8 8.3 9.2 # 104 117 221 Grey Average 7.8 8.0 7.9 # 99 136 235 Huron Average 8.0 7.6 7.7 # 124 140 264 Perth Average 8.9 7.6 8.2 # 426 461 887 Total Average 8.6 7.8 8.2

The level of the participation in extra-curricular activities for Grey County is below, to see the comparison to all four counties see Appendices.

In Grey, only 18.5% of the students do not participate in any sport or physical activity. Students are most likely to participate in sports or physical activity through another organization beyond school.

Table 41: Extra-Curricular Participation in Sports or Physical Activity at School or with Other Organizations Gender Total County Male Female # % # % # % School 50 47.2% 52 43.0% 102 44.9% Other Organization 63 59.4% 79 65.3% 142 62.6% Grey None 24 22.6% 18 14.9% 42 18.5% Total 106 100.0% 121 100.0% 227 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A4

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 52 Art, drama or music is less common among students in Grey County than sports or physical activity extra- curricular activities. In Grey, 26% of students participate in art, drama or music in schools and 17.6% of students participate in these activities through another organization outside of school.

Table 42: Extra-Curricular Participation in an Art, Drama or Music Group at School or With Other Organizations Gender Total County Male Female # % # % # % School 25 23.6% 34 28.1% 59 26.0% Other Organization 12 11.3% 28 23.1% 40 17.6% Grey None 74 69.8% 63 52.1% 137 60.4% Total 106 100.0% 121 100.0% 227 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A5

In Grey County, 22.1% of females and 18.1% of males have participated in student council or student government in school.

Table 43: Extra-Curricular Participation in Student Council Gender Total County Male Female # % # % # % Yes 19 18.1% 27 22.1% 46 20.3% Grey No 86 81.9% 95 77.9% 181 79.7% Total 105 100.0% 122 100.0% 227 100.0%

*For full Four County results refer to Appendix Table A6

In Grey County, 51.5% of the students participate in another type of group or club. Students in Grey County are active in 4-H, church, religious and/or youth groups, males are also active in cadets while many females reported being involved in prom committee.

Table 44: Extra-Curricular Participation in Another Type of Group or Club

Gender Total County Male Female # % # % # % Yes 46 43.0% 71 59.2% 117 51.5% Grey No 61 57.0% 49 40.8% 110 48.5% Total 107 100.0% 120 100.0% 227 100.0%

*For full Four County results refer to Appendix Table A7

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 53 3.3.5 Volunteer Activities Like extra-curricular activities, volunteer activities provide insight into student skills and interests of the students. Volunteering provides the chance to gain valuable experience within the structure of an existing organization. These volunteer activities allow the students to develop and enhance several skills that can be transferred into the work place.

As per the OSSD requirements, students are to perform at least 40 hours of volunteer work over the course of their high school career in order to graduate. Students were asked to report how many hours they have volunteered over the last year, as well as to describe the organizations for which they volunteer.

In all counties the majority of students have volunteered in the last year, and have volunteered significant hours. Across the Four County Region the average number of hours spent volunteering in the last year was 44.8 hours. In Grey, 82.8% of females and 71.8% of males have volunteered in the last year. Again in Grey County, the average number of hours spent volunteering over the last year was 50.2 hours.

Table 45: Volunteer Participation by Gender Gender Total County Male Female # % # % # % Yes 103 75.2% 83 90.2% 186 81.2% Bruce No 34 24.8% 9 9.8% 43 18.8% Total 137 100.0% 92 100.0% 229 100.0% Yes 125 71.8% 159 82.8% 284 77.6% Grey No 49 28.2% 33 17.2% 82 22.4% Total 174 100.0% 192 100.0% 366 100.0% Yes 127 77.0% 166 83.4% 293 80.5% Huron No 38 23.0% 33 16.6% 71 19.5% Total 165 100.0% 199 100.0% 364 100.0% Yes 146 76.4% 189 89.2% 335 83.1% Perth No 45 23.6% 23 10.8% 68 16.9% Total 191 100.0% 212 100.0% 403 100.0% Yes 501 75.1% 597 85.9% 1,098 80.6% Total No 166 24.9% 98 14.1% 264 19.4% Total 667 100.0% 695 100.0% 1,362 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 54 Table 46: Average Number of Hours Spent Volunteering in the Past Year by Gender County Male Female Total # 95 79 174 Bruce Average 51.1 47.1 49.3 # 116 152 268 Grey Average 45.1 54.1 50.2 # 116 157 273 Huron Average 45.8 42.6 44.0 # 137 182 319 Perth Average 38.5 38.4 38.5 # 464 570 1,034 Total Average 44.5 44.9 44.8

In Grey County, 42.6% of students reported having completed their volunteer activities because they had to in order to graduate high school. Beyond the school volunteer requirements, 25.7% students volunteered because they were asked by a friend or family member. Another 19.4% of students volunteered because they wanted to help a cause they believe in.

Table 47: Reason for Starting a Volunteer Activity by Gender Gender Total County Reasons Male Female # % # % # % I had to volunteer in order to graduate 62 49.6% 59 37.1% 121 42.6% from high school. I was asked to help by a friend or 40 32.0% 33 20.8% 73 25.7% family member. I had to complete public service hours due to an incident involving legal 1 0.8% 1 0.6% 2 0.7% authorities Grey I wanted to gain some skills and experience so I could get a better job 15 12.0% 39 24.5% 54 19.0% in the future; have more to show on my resume. My parent(s) wanted me to volunteer. 3 2.4% 7 4.4% 10 3.5% I wanted to help in a cause I personally 19 15.2% 36 22.6% 55 19.4% believe in. Total 125 100.0% 159 100.0% 284 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A11

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 55 The volunteer participation by industry and volunteer activity for Grey County is below, to see the comparison to all four counties see Appendices.

In Grey, the most common industries for which male students reported volunteer participation were Information, Culture, and Recreation (28.2%); Religious, Civic, Environmental or Social Advocacy (25.3%); and, Agriculture (12.1%). The top industries for female students reported volunteer participation were Information, Culture, and Recreation (30.7%); Religious, Civic, Environmental or Social Advocacy (28.6%); Educational (18.2%); and, Health Care or Social Assistance (17.7%).

Table 48: Volunteer Participation by Industry and Gender Gender Total County Industry Male Female # % # % # % Agricultural Organization 21 12.1% 29 15.1% 50 13.7% Finance, Insurance, Real Estate 0 0.0% 3 1.6% 3 0.8% Organization Professional, Scientific and Technical 6 3.4% 6 3.1% 12 3.3% Service Org. Educational Organization 15 8.6% 35 18.2% 50 13.7% Health Care or Social Assistance 16 9.2% 34 17.7% 50 13.7% Grey Organization Information, Culture, and Recreation 49 28.2% 59 30.7% 108 29.5% Organization Religious, Civic, Environmental or 44 25.3% 55 28.6% 99 27.0% Social Advocacy Organization Public Administration 7 4.0% 2 1.0% 9 2.5% Other volunteer activity 5 2.9% 7 3.6% 12 3.3% Total 174 100.0% 192 100.0% 366 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A8

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 56 The volunteering experiences reported by the students are opportunities to gain and develop many skills and qualities that are highly valued by employers. The students that reported helping an Information, Culture and Recreation organization are likely those engaged in social assistance or coaching. These individuals would therefore have strong leadership, organization and social and interpersonal skills. Religious, Civic and Social Advocacy volunteerism was the second highest reported industry category, which is common as these organizations are largely drive by volunteer support. Agriculture was ranked high among males which is linked to the rural foundations of the area, these agriculture opportunities can build physical, mechanical or hands on skills, as well as a chance to gain knowledge in agriculture and horticulture. Health Care and Social Assistance, a growing industry in the Four County Region was ranked high among females.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 57 The activities that the students perform provide useful information as to the types of specific skills learned through experience. In many cases these activities provide an opportunity to develop and improve leadership, teamwork and organization skills. In Grey County, the most common activities performed by male and female students were: • Social assistance, teaching or coaching (31.3%) • Organizing or supervising an event (21.5%) • Building, repairing, technical, or hands-on work (18%) • Selling a product or service in order to raise money fundraising (9.5%) • Health care, support or counseling (9.2%)

Table 49: Volunteer Participation by Activity where Most Time was Spent, by Gender Gender Total County Volunteer Activity Male Female # % # % # % Acting as a committee or board member 4 3.2% 2 1.3% 6 2.1% Organizing or supervising an event 22 17.6% 39 24.5% 61 21.5% Office work, administration, clerical 3 2.4% 3 1.9% 6 2.1% Helping to manage money or finances 2 1.6% 5 3.1% 7 2.5% Mentoring in a business or finance 0 0.0% 2 1.3% 2 0.7% organization Computer-based work (designing a 3 2.4% 2 1.3% 5 1.8% web site, working with spread sheets) Mentoring with a scientist, engineer, 0 0.0% 2 1.3% 2 0.7% or agricultural specialist Health care, support or counseling 6 4.8% 20 12.6% 26 9.2% Mentoring with a doctor, veterinarian, 0 0.0% 2 1.3% 2 0.7% or other health professional

Grey Social assistance, teaching, or coaching 34 27.2% 55 34.6% 89 31.3% Mentoring in a law office, with a social 1 0.8% 0 0.0% 1 0.4% worker or a teacher Using creative skills in graphic design, 3 2.4% 5 3.1% 8 2.8% painting, photography Writing newsletters, broadcasting, canvassing, campaigning or in some 2 1.6% 4 2.5% 6 2.1% other way providing information to the public Selling a product or service in order to 13 10.4% 14 8.8% 27 9.5% raise money; fundraising Building, repairing, technical, or 35 28.0% 16 10.1% 51 18.0% hands-on work Using agricultural or horticultural skills 9 7.2% 12 7.5% 21 7.4% Total 125 100.0% 159 100.0% 284 100.0% The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A9

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 58 3.3.6 Paid Work Paid employment provides the essential workforce experience that is required to successfully move forward in the labour market. The time committed to a job helps youth develop both industry and/or occupation specific skills as well as transferable skills that will make them more marketable and increase their employ- ability in the larger labour market.

The majority of students are employed either during the school year or the summer, or in many cases both. Across the Four County Region 76.8% of the student respondents worked during the school year, and 80.9% worked during the summer months while off school, as shown in Tables 50 and 51. Grey County has the lowest part-time work participation with 70.1% of males and 72.3% of females working during the school year.

Table 50: Part-time Work Participation by Gender Gender Total County Male Female # % # % # % Yes 105 77.2% 73 79.3% 178 78.1% Bruce No 31 22.8% 19 20.7% 50 21.9% Total 136 100.0% 92 100.0% 228 100.0% Yes 122 70.1% 138 72.3% 260 71.2% Grey No 52 29.9% 53 27.7% 105 28.8% Total 174 100.0% 191 100.0% 365 100.0% Yes 121 73.3% 149 74.5% 270 74.0% Huron No 44 26.7% 51 25.5% 95 26.0% Total 165 100.0% 200 100.0% 365 100.0% Yes 151 79.1% 186 87.7% 337 83.6% Perth No 40 20.9% 26 12.3% 66 16.4% Total 191 100.0% 212 100.0% 403 100.0% Yes 499 74.9% 546 78.6% 1,045 76.8% Total No 167 25.1% 149 21.4% 316 23.2% Total 666 100.0% 695 100.0% 1,361 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 59 Again, Grey County has the lowest participation rate in summer employment with 78% of males and 74.5% of females working in the summer.

Table 51: Summer Work Participation by Gender Gender Total County Male Female # % # % # % Yes 110 80.3% 72 79.1% 182 79.8% Bruce No 27 19.7% 19 20.9% 46 20.2% Total 137 100.0% 91 100.0% 228 100.0% Yes 135 78.0% 143 74.5% 278 76.2% Grey No 38 22.0% 49 25.5% 87 23.8% Total 173 100.0% 192 100.0% 365 100.0% Yes 135 81.3% 155 77.5% 290 79.2% Huron No 31 18.7% 45 22.5% 76 20.8% Total 166 100.0% 200 100.0% 366 100.0% Yes 163 85.3% 189 89.2% 352 87.3% Perth No 28 14.7% 23 10.8% 51 12.7% Total 191 100.0% 212 100.0% 403 100.0% Yes 543 81.4% 559 80.4% 1,102 80.9% Total No 124 18.6% 136 19.6% 260 19.1% Total 667 100.0% 695 100.0% 1,362 100.0%

Of those that did work during the school year, students worked approximately 17.3 hours across the Four County Region and slightly less at 15.7 hours in Grey County. In Grey County, males work slightly more than females; 16.1 and 15.4 hours comparatively.

Table 52: Average Number of Hours per Week Working in Part-time Job by Gender County Male Female Total # 101 71 172 Bruce Average 18.4 15.9 17.4 # 115 129 244 Grey Average 16.1 15.4 15.7 # 115 145 260 Huron Average 17.6 16.8 17.1 # 146 184 330 Perth Average 20.1 17.5 18.7 # 477 529 1,006 Total Average 18.2 16.6 17.3

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 60 The students worked on average 29.4 weeks of the year in the Four County Region and 27.3 weeks in Grey.

Table 53: Average Number of Weeks Working in Part-time Job by Gender County Male Female Total # 100 63 163 Bruce Average 28.3 30.0 29.0 # 108 116 224 Grey Average 26.3 28.2 27.3 # 110 133 243 Huron Average 29.9 29.4 29.6 # 137 172 309 Perth Average 32.0 30.4 31.1 # 455 484 939 Total Average 29.3 29.5 29.4

For those who reported working a summer job reported that they worked approximately 29.7 hours a week in the Four County Region and 30.6 hours a week in Grey County. Again, males work more hours per week than females.

Table 54: Average Number of Hours per Week Working in Summer time Job by Gender County Male Female Total # 105 72 177 Bruce Average 31.8 26.7 29.7 # 131 129 260 Grey Average 31.6 29.5 30.6 # 130 152 282 Huron Average 31.4 27.5 29.3 # 158 184 342 Perth Average 32.0 26.8 29.2 # 524 537 1,061 Total Average 31.7 27.6 29.7

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 61 For males and females across all four counties, the average number of weeks working in a summer job was around the eight week mark as expected.

Table 55: Average Number of Weeks Working in Summer time Job by Gender County Male Female Total # 106 69 175 Bruce Average 8.3 7.9 8.2 # 132 126 258 Grey Average 8.2 8.0 8.1 # 126 148 274 Huron Average 8.2 7.8 8.0 # 152 182 334 Perth Average 8.4 8.2 8.3 # 516 525 1,041 Total Average 8.3 8.0 8.1

The most dominant categories for both part-time and summer employment for males and females were Wholesale and Retail Trade and Accommodation and Food Services. While in many cases these jobs are used to gain money and not experience for a future career, such experience should be valued for the skills it impacts including customer service, interpersonal skills, team work, time management, organizational as well as financial.

Arts, Entertainment and Recreation was also among the top five industries for both males and females in Grey County. This industry includes work in libraries, parks, golf courses and tourist destinations where students are likely to learn a variety of skills. Perhaps not surprising Agriculture was also among the top five industries in Grey County which is linked to the focus of agriculture and farming in the area. These jobs provide youth with physical and hands on skills that are very valuable in an economy that depends on agriculture fairly significantly. The females from Grey also were active in the Health Care and Social Assistance field which includes babysitting and child care. This field is important as it provides highly valuable skills including mentoring, teaching, and interpersonal skills.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 62 Other Services was another common industry represented by both males and females from Grey. These occupations are likely to include automotive service and repair, personal care, and pet care.

Additional details on the part-time and summer work for Grey County can be found in Tables 56 and 57. Details on the other three counties can be found in the Appendices.

Table 56: Part-time Work Activity by Industry and Gender Gender Total County Industry Male Female # % # % # % Agriculture, Forestry, Fishing 11 9.0% 10 7.2% 21 8.1% Utilities 1 0.8% 0 0.0% 1 0.4% Construction and/or Specialty 14 11.5% 2 1.4% 16 6.2% Trade Contractor Manufacturing 5 4.1% 3 2.2% 8 3.1% Wholesale and Retail Trade 34 27.9% 44 31.9% 78 30.0% Transportation and Warehousing 2 1.6% 1 0.7% 3 1.2% Finance, Insurance 1 0.8% 0 0.0% 1 0.4% Professional, Scientific and Technical 1 0.8% 1 0.7% 2 0.8% Services Business, Building and Other Support 3 2.5% 7 5.1% 10 3.8% Services Grey Educational Services 0 0.0% 4 2.9% 4 1.5% Health Care and Social Assistance 2 1.6% 17 12.3% 19 7.3% Arts, Entertainment, Recreation 16 13.1% 10 7.2% 26 10.0% Accommodation and Food Services 30 24.6% 46 33.3% 76 29.2% Other Services (repair & maintenance; automotive repair, personal care, 13 10.7% 10 7.2% 23 8.8% beauty, hair styling; dry cleaning and laundry; pet care; photo finishing) Religious, Civic and Social Advocacy 0 0.0% 3 2.2% 3 1.2% Organization Public Administration 2 1.6% 1 0.7% 3 1.2% Total 122 100.0% 138 100.0% 260 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A12

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 63 Table 57: Summer Work Activity by Industry and Gender Gender Total County Industry Male Female # % # % # % Agriculture, Forestry, Fishing 10 7.4% 9 6.3% 19 6.8% Mining, Quarrying, and Oil and 2 1.5% 0 0.0% 2 0.7% Gas extraction Utilities 2 1.5% 0 0.0% 2 0.7% Construction and/or Specialty 24 17.8% 6 4.2% 30 10.8% Trade Contractor Manufacturing 6 4.4% 3 2.1% 9 3.2% Wholesale and Retail Trade 25 18.5% 30 21.0% 55 19.8% Transportation and Warehousing 2 1.5% 0 0.0% 2 0.7% Real Estate and Leasing 0 0.0% 2 1.4% 2 0.7% Professional, Scientific and Technical 0 0.0% 2 1.4% 2 0.7% Services Business, Building and Other Support Grey 2 1.5% 9 6.3% 11 4.0% Services Educational Services 1 0.7% 2 1.4% 3 1.1% Health Care and Social Assistance 2 1.5% 17 11.9% 19 6.8% Arts, Entertainment, Recreation 14 10.4% 14 9.8% 28 10.1% Accommodation and Food Services 32 23.7% 37 25.9% 69 24.8% Other Services (repair & maintenance; automotive repair, personal care, 19 14.1% 10 7.0% 29 10.4% beauty, hair styling; dry cleaning and laundry; pet care; photo finishing) Religious, Civic and Social Advocacy 0 0.0% 2 1.4% 2 0.7% Organization Public Administration 0 0.0% 3 2.1% 3 1.1% Total 135 100.0% 143 100.0% 278 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A13

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 64 In Grey County, most found both their part-time and summer job through a family member, friend or neighbour, this is especially true for males. Another common method was submitting an application to an employer for a job that was not advertised, as shown in the tables below. Only a small number of students found their job through an employment agency or job counsellor.

Table 58: Method Used to Find Part-time Job by Gender

Gender Total County Method Male Female # % # % # % Through a family member, friend or 70 57.4% 73 52.9% 143 55.0% neighbor. I responded to a newspaper or 9 7.4% 9 6.5% 18 6.9% print ad. I submitted an application to an employer 37 30.3% 43 31.2% 80 30.8% for a job that wasn’t advertised. Grey By posting an ad stating that I was 0 0.0% 2 1.4% 2 0.8% looking for work.

By consulting an employment agency 1 0.8% 1 0.7% 2 0.8% or job counselor. Total 122 100.0% 138 100.0% 260 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A14

Table 59: Method Used to Find Summer Work by Gender Gender Total County Method Male Female # % # % # % Through a family member, friend 93 68.9% 80 55.9% 173 62.2% or neighbor. I responded to a newspaper or 6 4.4% 5 3.5% 11 4.0% print ad. I submitted an application to an employer for a job that wasn’t 24 17.8% 31 21.7% 55 19.8% Grey advertised. By posting an ad stating that I was 1 0.7% 1 0.7% 2 0.7% looking for work. By consulting an employment 0 0.0% 0 0.0% 0 0.0% agency or job counselor. Total 135 100.0% 143 100.0% 278 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A15

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 65 In Grey County, males are most likely to get a part-time and summer job to have money to spend in their free time, while the females are most likely to want a part-time and summer job for their future education.

Table 60: Reason for Getting a Part-time Job by Gender Gender Total County Reason Male Female # % # % # % I wanted money to spend in my free 49 40.2% 42 30.4% 91 35.0% time or to buy things. I wanted money for my future 48 39.3% 70 50.7% 118 45.4% education. I needed money to help my family. 3 2.5% 8 5.8% 11 4.2% I was asked to work by a friend or 8 6.6% 9 6.5% 17 6.5% Grey family member. I wanted to gain some skills and work 28 23.0% 25 18.1% 53 20.4% experience. I wanted to find out if I was interested 8 6.6% 8 5.8% 16 6.2% in a certain type of job/career. My parent(s) wanted me to work. 5 4.1% 10 7.2% 15 5.8% Total 122 100.0% 138 100.0% 260 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A16

Table 61: Reason for Getting a Summer Time Job by Gender Gender Total County Reason Male Female # % # % # % I wanted money to spend in my free 65 48.1% 37 25.9% 102 36.7% time or to buy things. I wanted money for my future 52 38.5% 68 47.6% 120 43.2% education. I needed money to help my family. 4 3.0% 7 4.9% 11 4.0% I was asked to work by a friend or 9 6.7% 7 4.9% 16 5.8% Grey family member. I wanted to gain some skills and 23 17.0% 19 13.3% 42 15.1% work experience. I wanted to find out if I was interested 9 6.7% 3 2.1% 12 4.3% in a certain type of job/career. My parent(s) wanted me to work. 8 5.9% 11 7.7% 19 6.8% Total 135 100.0% 143 100.0% 278 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A17

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 66 3.3.7 School Co-op Activities Planned learning experiences, like cooperative education or co-op, provide students who are enrolled in courses of all types and in all disciplines with the opportunity to enhance their school programs. Co-op is typically offered in the form of credit courses that are scheduled for a full semester. It is the intention of the Ontario government that co-op can assist all students in making career decisions as well as in developing the knowledge, skills, and attitudes that are essential in today’s society. All forms of experiential learning are a valuable complement to students’ academic experience and preparation for the future. When organized in a sequential fashion that meets career development needs, experiential learning can maximize student growth and development, and should be encouraged.

For the Four County Region as a whole, only 16.6% of students have been enrolled in co-op, with more females participating in co-op than males; 19.2% versus 13.8%. In Grey County, 11.5% of males and 18.7% of females have participated in co-op. Last study there were slightly more males participating in co-op than females.

Table 62: School Co-op Participation by Gender Gender Total County Male Female # % # % # % Yes 22 16.1% 20 21.7% 42 18.3% Bruce No 115 83.9% 72 78.3% 187 81.7% Total 137 100.0% 92 100.0% 229 100.0% Yes 20 11.5% 36 18.7% 56 15.3% Grey No 154 88.5% 157 81.3% 311 84.7% Total 174 100.0% 193 100.0% 367 100.0% Yes 25 15.2% 33 16.5% 58 15.9% Huron No 140 84.8% 167 83.5% 307 84.1% Total 165 100.0% 200 100.0% 365 100.0% Yes 25 13.2% 44 21.1% 69 17.3% Perth No 164 86.8% 165 78.9% 329 82.7% Total 189 100.0% 209 100.0% 398 100.0% Yes 92 13.8% 133 19.2% 225 16.6% Total No 573 86.2% 561 80.8% 1,134 83.4% Total 665 100.0% 694 100.0% 1,359 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 67 In Grey County, males participating in co-op were most likely to be involved in Other services (35%) including repair and maintenance and automotive repair. In Grey County, females participating in co-op were most likely to be involved in Health Care and Social Assistance (44%), while Educational Services (22.2%) was also fairly common.

Table 63: Co-op Program Activity by Industry and Gender Gender Total County Industry Male Female # % # % # % Agriculture, Forestry, Fishing 1 5.0% 1 2.8% 2 3.6% Utilities 1 5.0% 0 0.0% 1 1.8% Construction and/or Specialty 1 5.0% 0 0.0% 1 1.8% Trade Contractor Manufacturing 2 10.0% 0 0.0% 2 3.6% Wholesale and Retail Trade 1 5.0% 2 5.6% 3 5.4% Transportation and Warehousing 3 15.0% 0 0.0% 3 5.4% Professional, Scientific and Technical 1 5.0% 1 2.8% 2 3.6% Services Grey Business, Building and Other Support 0 0.0% 1 2.8% 1 1.8% Services Educational Services 2 10.0% 8 22.2% 10 17.9% Health Care and Social Assistance 1 5.0% 16 44.4% 17 30.4% Arts, Entertainment, Recreation 1 5.0% 2 5.6% 3 5.4% Other Services (repair & maintenance; automotive repair, personal care, 7 35.0% 4 11.1% 11 19.6% beauty, hair styling; dry cleaning and laundry; pet care; photo finishing) Total 20 100.0% 36 100.0% 56 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A18

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 68 The majority of male co-op students (65%) in Grey choose to participate in the co-op program to gain some skills and work experience. The majority of Grey County female co-op students (55.6%) choose to participate in the co-op program to find out if they were interested in a certain type of job or career.

Table 64: Reason for Participating in Co-op Program by Gender

Gender Total County Reason Male Female # % # % # % A teacher or counselor suggested I 3 15.0% 1 2.8% 4 7.1% should take the course.

I wanted to start accumulating hours 1 5.0% 3 8.3% 4 7.1% for an apprenticeship. My friend(s) were taking the course. 0 0.0% 1 2.8% 1 1.8% I thought the course would be easy. 1 5.0% 1 2.8% 2 3.6% Grey I wanted to gain some skills and 13 65.0% 10 27.8% 23 41.1% work experience. I wanted to find out if I was interested 6 30.0% 20 55.6% 26 46.4% in a certain type of job/career. My parent(s) wanted me to take 0 0.0% 1 2.8% 1 1.8% the course. Total 20 100.0% 36 100.0% 56 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A19

3.3.8 Work at Home Activities The final area analyzed by the survey as a source of skill development and experience is labour that occurs within the home or through a family-owned business. Across the Four County Region, 52.8% of students reported working at home. In general, females are more likely to participate in work at home than their male counterparts.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 69 In Grey County, 43.7% of males and 51.6% of females reported working at home.

Table 65: Work at Home Participation by Gender Gender Total County Male Female # % # % # % Yes 75 54.7% 45 48.9% 120 52.4% Bruce No 62 45.3% 47 51.1% 109 47.6% Total 137 100.0% 92 100.0% 229 100.0% Yes 76 43.7% 99 51.6% 175 47.8% Grey No 98 56.3% 93 48.4% 191 52.2% Total 174 100.0% 192 100.0% 366 100.0% Yes 88 53.7% 127 63.5% 215 59.1% Huron No 76 46.3% 73 36.5% 149 40.9% Total 164 100.0% 200 100.0% 364 100.0% Yes 98 51.9% 109 51.9% 207 51.9% Perth No 91 48.1% 101 48.1% 192 48.1% Total 189 100.0% 210 100.0% 399 100.0% Yes 337 50.8% 380 54.8% 717 52.8% Total No 327 49.2% 314 45.2% 641 47.2% Total 664 100.0% 694 100.0% 1,358 100.0%

Females from Grey work approximately 10 hours per week, while males work 8.9 hours per week.

Table 66: Average Number of Hours per Week Working at Home in Past School Year by Gender County Male Female Total # 68 42 110 Bruce Average 10.4 9.8 10.1 # 70 82 152 Grey Average 8.9 10.4 9.7 # 88 119 207 Huron Average 10.1 10.6 10.4 # 91 102 193 Perth Average 10.7 8.9 9.8 # 317 345 662 Total Average 10.1 10.0 10.0

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 70 The majority (56%) of the students from Grey County do household chores around their house, another 25.7% work on their family farm, 10.9% work for their family’s trade business.

Table 67: Main Work Activity When Working at Home by Gender

Gender Total County Work Activity Male Female # % # % # % I often work on my family farm 18 23.7% 27 27.3% 45 25.7% I often work for my family’s 9 11.8% 10 10.1% 19 10.9% trade business Grey I often work at my family’s store 2 2.6% 2 2.0% 4 2.3% I often work at my family’s restaurant. 3 3.9% 5 5.1% 8 4.6% I often do chores around my house 39 51.3% 59 59.6% 98 56.0% Total 76 100.0% 99 100.0% 175 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A21

3.3.9 Overall Skills As a supplement to the more objective measurements of participation and time commitment in various skill developing activities the survey also incorporated a self-assessment of a number of skills. The students self-assessed on a 5-point scale from poor to excellent on various skills, as listed in Table 68. For comparison the Four County Region as a whole has also been provided. The following tables outline the mean scores for each variable according to gender. In all cases, the mean score for each variable was 2.9 or higher.

In reviewing the Four County Region as a whole, the students rated their social, interpersonal skills and teamwork skills the highest with a mean score of 3.8. Reading and creative thinking skills followed closely with a mean score of 3.7.

In Grey County, males have scored themselves the highest in analytical, decision making and problem solving and teamwork with an average score of 3.8 each. Females have scored themselves the highest in social, interpersonal skills and reading with 3.9 each. Gendered differences in self-assessed skill levels could be an indication of the area of concern in extending skill development and training.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 71 Table 68: Average Skill Rating for Grey County Students by Gender

Male Female Total Skill # Average # Average # Average Reading 165 3.6 188 3.9 353 3.8 Writing 165 3.3 188 3.6 353 3.5 Oral communication 163 3.5 187 3.7 350 3.6 Mathematical 164 3.5 186 3.0 350 3.2 Social, interpersonal 165 3.5 187 3.9 352 3.7 Analytical, decision making and 164 3.8 188 3.7 352 3.7 problem solving Teamwork 165 3.8 188 3.8 353 3.8 Computer 165 3.4 187 3.2 352 3.3 Self-management and organizational 164 3.1 188 3.5 352 3.4 Administrative/planning 164 3.1 187 3.5 351 3.3 Leadership 165 3.5 187 3.6 352 3.5 Creative thinking 165 3.5 188 3.8 353 3.6 Technological 163 3.5 185 2.9 348 3.2 Physical, mechanical or hands on 164 3.6 188 2.9 352 3.2 Performance, creativity, artistic 165 2.8 186 3.5 351 3.2 Adaptability 165 3.6 188 3.7 353 3.7 *For full Four County results refer to Appendix Tables A22-A26 Table 69: Average Skill Rating for Four County Students by Gender Male Female Total Skill # Average # Average # Average Reading 646 3.6 684 3.9 1,330 3.7 Writing 645 3.3 681 3.6 1,326 3.4 Oral communication 645 3.5 678 3.5 1,323 3.5 Mathematical 646 3.4 682 2.9 1,328 3.2 Social, interpersonal 646 3.6 683 3.9 1,329 3.8 Analytical, decision making and 645 3.7 684 3.6 1,329 3.6 problem solving Teamwork 646 3.8 684 3.9 1,330 3.8 Computer 646 3.4 683 3.2 1,329 3.3 Self-management and organizational 645 3.1 684 3.5 1,329 3.3 Administrative/planning 643 3.1 680 3.4 1,323 3.3 Leadership 646 3.5 683 3.7 1,329 3.6 Creative thinking 644 3.6 682 3.7 1,326 3.7 Technological 641 3.6 677 2.9 1,318 3.2 Physical, mechanical or hands on 644 3.7 683 2.9 1,327 3.3 Performance, creativity, artistic 643 2.9 679 3.6 1,322 3.2 Adaptability 642 3.5 682 3.6 1,324 3.6

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 72 3.3.10 Plans for Future Education As part of studying the future labour force, it is helpful to gain an understanding of the expected future skills, the skills the students now in Grade 12, will have once they enter the labour force. As such, the survey asked the students their future education plans upon graduating high school. A large majority (93.2%) of students across the Four County Region plan to enter post-secondary school or an apprenticeship. Males are more likely to enter the job market following high school than females. In Grey County specifically, 85.5% of males expect to finish high school and continue onto post-secondary school or apprenticeship program compared to 97.9% of females. 7

Table 70: Plans for the Near Future by Gender

Gender Total County Plans for the Near Future Male Female # % # % # % Finish high school and continue onto post-secondary school or 148 85.5% 187 97.9% 335 92.0% apprenticeship Grey Finish high school or leave high 25 14.5% 4 2.1% 29 8.0% school and find a job Total 173 100.0% 191 100.0% 364 100.0% Finish high school and continue onto post-secondary school or 599 90.1% 668 96.3% 1,267 93.2% apprenticeship Total Finish high school or leave high 66 9.9% 26 3.7% 92 6.8% school and find a job Total 665 100.0% 694 100.0% 1,359 100.0%

7 It is important to recognize that these figures represent stated intentions and not actual post-secondary outcomes. A 2009 study by Colleges Ontario assessed the PSE outcomes for high school students across Ontario. The study determined that 60% of students with 4 or 5 years of high school went directly into PSE programs (34% university, 20% college; 6% apprenticeship) while 40% went into the workforce (15% with OSSD, 25% without OSSD) (Ontario Colleges. Who doesn’t go to PSE? Nov. 2009).

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 73 The students are less sure when it comes to deciding which career path they will follow in the near future. Looking at the Four County Region, only 61.3% know about their career options and what they want to do regarding education to reach that goal, 32.9% have not choose a career but are aware of their areas of interest. The remainder of students have not made any decisions regarding area of interest but feel they need further education to find a job. Again, females are surer of their future education and career pathway than males. In Grey, fewer students know about their career options and what they want to do regarding their education.

Table 71: Future Plans for Post-secondary School / Training by Gender Gender Future Plans for Post-secondary Total County Male Female School / Training # % # % # % I know about my career options and what I want to do and I’m 80 55.2% 121 64.7% 201 60.5% planning for a program

I don’t know what I want as a career 50 34.5% 55 29.4% 105 31.6% but I know my areas of interest Grey

I don’t know what I want as a career but I know I need more 15 10.3% 11 5.9% 26 7.8% education to get a job

Total 145 100.0% 187 100.0% 332 100.0%

I know about my career options and what I want to do and I’m 346 58.3% 427 64.0% 773 61.3% planning for a program

I don’t know what I want as a career 210 35.4% 204 30.6% 414 32.9% Total but I know my areas of interest I don’t know what I want as a career but I know I need more 37 6.2% 36 5.4% 73 5.8% education to get a job

Total 593 100.0% 667 100.0% 1,260 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 74 Making decisions regarding post-secondary education is important and can be daunting for some students. Often, there are several factors that can influence their plans in furthering their education. In Grey County, the students’ own thoughts and interests is the greatest influence on their plans for post- secondary education; 35.3% for males and 47/1% for females. For males, the second greatest influence was their classes at school. For females, the second greatest influence was their desire for a good job and a high income, followed by their classes at school. The students’ experience in a co-op placement was also quite high for female students, who were more likely to participate in co-op.

Table 72: Factors that Influenced Student Plans for Post-secondary Education

Gender Total County Factors Male Female # % # % # % My classes at school 35 20.2% 32 16.8% 67 18.4% My volunteer experiences 1 0.6% 11 5.8% 12 3.3% My job experiences 18 10.4% 10 5.2% 28 7.7% My Co-op placement 7 4.0% 21 11.0% 28 7.7% A career education or guidance class 0 0.0% 1 0.5% 1 0.3% The advice of a school counselor, 3 1.7% 9 4.7% 12 3.3% Grey teacher, or mentor My friends’ opinions 5 2.9% 5 2.6% 10 2.7% My parents’ opinions 14 8.1% 19 9.9% 33 9.1% My own thoughts and interests 61 35.3% 90 47.1% 151 41.5% My desire for a good job and a 34 19.7% 34 17.8% 68 18.7% high income Total 173 100.0% 191 100.0% 364 100.0% The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A27

Males from Grey County are more confident in being accepted to and completing post-secondary education than females.

Table 73: Level of Confidence in Being Accepted to and Completing Post-secondary Education by Gender

Gender Total County Level of Confidence Male Female # % # % # % Not confident at all 4 2.7% 3 1.6% 7 2.1% Fairly confident 27 18.4% 42 22.5% 69 20.7% Grey Confident 63 42.9% 78 41.7% 141 42.2% Very confident 53 36.1% 64 34.2% 117 35.0% Total 147 100.0% 187 100.0% 334 100.0% *For full Four County results refer to Appendix Table A29

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 75 In reviewing the educational institutions the Four County Region students are most likely to attend a few important observations can be made. University is the most common response with 45.2% of the students planning to pursue a university program. Another 44.6% of students are looking to enter a college program upon graduating high school. Males are much more likely to enroll in a trade, vocational or apprenticeship with 18.8% of the male respondents planning to attend a trade program compared to 2.5% of females. Similar patterns exist in Grey County, though college is more common than university with 53.7% of the females and 39.2% of the males planning to enroll in a college program. Males from Grey County are the most likely to attend a trades program.

Table 74: Educational Institutions Students are Most Likely to Attend by Gender Gender Total County Educational Institution Male Female # % # % # % University 64 48.5% 50 55.6% 114 51.4% College 46 34.8% 38 42.2% 84 37.8% Bruce Trade, vocational or apprenticeship 22 16.7% 2 2.2% 24 10.8% Total 132 100.0% 90 100.0% 222 100.0% University 56 37.8% 82 43.6% 138 41.1% College 58 39.2% 101 53.7% 159 47.3% Grey Trade, vocational or apprenticeship 34 23.0% 5 2.7% 39 11.6% Total 148 100.0% 188 100.0% 336 100.0% University 49 34.8% 89 47.3% 138 41.9% College 65 46.1% 95 50.5% 160 48.6% Huron Trade, vocational or apprenticeship 27 19.1% 4 2.1% 31 9.4% Total 141 100.0% 188 100.0% 329 100.0% University 77 43.0% 107 52.2% 184 47.9% College 72 40.2% 92 44.9% 164 42.7% Perth Trade, vocational or apprenticeship 30 16.8% 6 2.9% 36 9.4% Total 179 100.0% 205 100.0% 384 100.0% University 246 41.0% 328 48.9% 574 45.2% College 241 40.2% 326 48.6% 567 44.6% Total Trade, vocational or apprenticeship 113 18.8% 17 2.5% 130 10.2%

Total 600 100.0% 671 100.0% 1,271 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 76 In university programs, females are most likely to pursue an arts degree, with 46.2% of the female respondents indicating they plan to enroll in an arts program. The majority of males are most likely to pursue a science degree. The bachelor of commerce program is more common among males than females. In Grey, 50% of females are planning to pursue an arts degree and 42.7% are interested in the science program. Males from Grey are most likely to pursue a science degree.

Table 75: University Degree Programs Students are Most Likely to Pursue by Gender

Gender Total County University Degree Program Male Female # % # % # % Bachelor of Arts 19 29.7% 24 48.0% 43 37.7% Bachelor of Commerce 10 15.6% 5 10.0% 15 13.2% Bruce Bachelor of Science 35 54.7% 21 42.0% 56 49.1% Total 64 100.0% 50 100.0% 114 100.0% Bachelor of Arts 11 20.0% 41 50.0% 52 38.0% Bachelor of Commerce 7 12.7% 6 7.3% 13 9.5% Grey Bachelor of Science 37 67.3% 35 42.7% 72 52.6% Total 55 100.0% 82 100.0% 137 100.0% Bachelor of Arts 14 29.2% 28 31.5% 42 30.7% Bachelor of Commerce 10 20.8% 10 11.2% 20 14.6% Huron Bachelor of Science 24 50.0% 51 57.3% 75 54.7% Total 48 100.0% 89 100.0% 137 100.0% Bachelor of Arts 26 33.8% 58 54.7% 84 45.9% Bachelor of Commerce 13 16.9% 14 13.2% 27 14.8% Perth Bachelor of Science 38 49.4% 34 32.1% 72 39.3% Total 77 100.0% 106 100.0% 183 100.0% Bachelor of Arts 70 28.7% 151 46.2% 221 38.7% Bachelor of Commerce 40 16.4% 35 10.7% 75 13.1% Total Bachelor of Science 134 54.9% 141 43.1% 275 48.2% Total 244 100.0% 327 100.0% 571 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 77 In college programs, females are most likely to enroll in a health science program, with 41.3% of the female respondents, followed by 18.6% of females planning to attend a community services program. The most common program among males is engineering technology. For males, business and protective services were also common. In Grey, the same patterns exist, 43.3% of females are planning to pursue an education in health science. Males from Grey are most likely to enroll in engineering technology with 32.8% of the respondents. Business and general arts and science programs were both ranked second most common with 13.8% of the male respondents looking to attend these programs.

Table 76: College Programs that Students are Most Likely to Pursue by Gender Gender Total County College Program Male Female # % # % # % Business 8 13.8% 5 5.1% 13 8.3% Community Services 0 0.0% 19 19.2% 19 12.1% Engineering Technology 19 32.8% 1 1.0% 20 12.7% General Arts and Sciences 8 13.8% 10 10.1% 18 11.5% Health Sciences 5 8.6% 43 43.4% 48 30.6% Grey Hospitality and Tourism 1 1.7% 7 7.1% 8 5.1% Info Technology / Computing 5 8.6% 0 0.0% 5 3.2% Media Studies 5 8.6% 9 9.1% 14 8.9% Protective Services 7 12.1% 5 5.1% 12 7.6% Total 58 100.0% 99 100.0% 157 100.0% Business 36 15.2% 31 9.6% 67 12.0% Community Services 9 3.8% 60 18.6% 69 12.3% Engineering Technology 61 25.7% 8 2.5% 69 12.3% General Arts and Sciences 33 13.9% 35 10.9% 68 12.2% Health Sciences 20 8.4% 133 41.3% 153 27.4% Total Hospitality and Tourism 5 2.1% 20 6.2% 25 4.5% Info Technology / Computing 11 4.6% 0 0.0% 11 2.0% Media Studies 26 11.0% 18 5.6% 44 7.9% Protective Services 36 15.2% 17 5.3% 53 9.5% Total 237 100.0% 322 100.0% 559 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 78 As discussed, apprenticeship programs are not common among females in Grey County. Only 5 students indicated they were interested in pursuing an apprenticeship. Females were most interested in hairstylist and horticulture, followed by automotive service or repair and electrician programs. Thirty-four males indicated they were interested in pursuing an apprenticeship, 6 of which were interested in carpentry. Another 14.7% of males are interested in automotive service, followed by electrician, machinist and welding programs.

Table 77: Apprenticeship Programs that Students are most Likely to Pursue by Gender

Gender Total County Apprenticeship Program Male Female # % # % # % Automotive service technician 5 14.7% 1 20.0% 6 15.4% Auto body repair 1 2.9% 1 20.0% 2 5.1% Cabinet maker 1 2.9% 0 0.0% 1 2.6% Carpenter 6 17.6% 0 0.0% 6 15.4% Chef/Cook 2 5.9% 0 0.0% 2 5.1% Electrician (general) 4 11.8% 1 20.0% 5 12.8% Hairstylist 0 0.0% 2 40.0% 2 5.1% Horticulture 0 0.0% 2 40.0% 2 5.1% Grey Machinist (general) 4 11.8% 0 0.0% 4 10.3% Millwright (industrial mechanic) 3 8.8% 0 0.0% 3 7.7% Plumber 3 8.8% 0 0.0% 3 7.7% Roofer 1 2.9% 0 0.0% 1 2.6% Sheet metal worker 1 2.9% 0 0.0% 1 2.6% Tool and die maker 1 2.9% 0 0.0% 1 2.6% Truck and coach technician 2 5.9% 0 0.0% 2 5.1% Welding, fitting 4 11.8% 0 0.0% 4 10.3% Total 34 100.0% 5 100.0% 39 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A30

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 79 3.3.11 Plans for Future Career Assessing the aspirations regarding the students’ future employment provides a mean of gauging expected labour supply in both industry and occupation categories. Survey figures in this regard provide a broad conception of where the emerging workforce is heading.

The following tables describe the industry and occupations that the students of Grey County are most likely to be employed, for comparisons to the Four County Region refer to Appendices.

Table 78: Industry that Students are most Likely to be Employed In by Gender

Gender Total County Industry Male Female # % # % # % Agriculture, Forestry, Fishing 9 5.2% 8 4.1% 17 4.6% Mining, Quarrying, and Oil and Gas 2 1.1% 1 0.5% 3 0.8% extraction Utilities 2 1.1% 2 1.0% 4 1.1% Construction and/or Specialty Trade 22 12.6% 3 1.6% 25 6.8% Contractor Manufacturing 13 7.5% 0 0.0% 13 3.5% Wholesale and Retail Trade 4 2.3% 2 1.0% 6 1.6% Transportation and Warehousing 2 1.1% 0 0.0% 2 0.5% Information, Culture 5 2.9% 6 3.1% 11 3.0% Finance, Insurance 2 1.1% 0 0.0% 2 0.5% Real Estate and Leasing 1 0.6% 0 0.0% 1 0.3% Grey Professional, Scientific and Technical 31 17.8% 14 7.3% 45 12.3% Services Business, Building and Other Support 10 5.7% 6 3.1% 16 4.4% Services Educational Services 3 1.7% 16 8.3% 19 5.2% TIE Health Care and Social Assistance 16 9.2% 81 42.0% 97 26.4% Arts, Entertainment, Recreation 14 8.0% 17 8.8% 31 8.4% Accommodation and Food Services 3 1.7% 5 2.6% 8 2.2% Other Services 15 8.6% 14 7.3% 29 7.9% Religious, Civic and Social Advocacy 2 1.1% 3 1.6% 5 1.4% Organization Public Administration 9 5.2% 8 4.1% 17 4.6% Total 174 100.0% 193 100.0% 367 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A31

= Top Three Industry Categories = Top Three Industry Categories in Grey - Males in Grey - Females

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 80 Occupational categories are even more directly connected to an individual’s particular set of skills that they use on a daily basis to conduct their job. The data mirrors the data related to the industry categories. For males, Tradesperson, transport or equipment operator followed by Natural and applied sciences were the most common reported occupations. Occupations in Health followed by Social science, education government service and religion and Art, culture, recreation and sport were the most common.

Table 79: Occupations that Students are most Likely to Have by Gender

Gender Total County Occupation Male Female # % # % # % Management Occupation 4 2.3% 4 2.1% 8 2.2% Business, Finance and Administrative 18 10.3% 7 3.6% 25 6.8% Occupation Natural and Applied Sciences and 30 17.2% 8 4.1% 38 10.4% Related Occupation

Health Occupation 12 6.9% 65 33.7% 77 21.0%

Social Science, Education, Govt. 12 6.9% 47 24.4% 59 16.1% Service and Religion Grey Art, Culture, Recreation and Sport 21 12.1% 30 15.5% 51 13.9% Occupation Sales and Service Occupation 9 5.2% 9 4.7% 18 4.9% Tradesperson, Transport or Equipment 40 23.0% 4 2.1% 44 12.0% Operator Primary Industry Occupation 5 2.9% 5 2.6% 10 2.7%

Processing, Manufacturing and 9 5.2% 0 0.0% 9 2.5% Utilities Occupation

Total 174 100.0% 193 100.0% 367 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A32

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 81 Factorings influencing career selection are very similar to those influencing proposed education with an individual’s own thoughts and interests having the greatest bearing followed by classes at school and 18% for co-op placement.

Table 80: Factors that Directed Students toward Pursuing this Career by Gender Gender Total County Factors Male Female # % # % # % My classes at school 87 50.0% 110 57.0% 197 53.7% My volunteer work 17 9.8% 44 22.8% 61 16.6% My part-time or summer job 34 19.5% 37 19.2% 71 19.3% My co-op placement 21 12.1% 45 23.3% 66 18.0% My own interests, thoughts, and ideas 129 74.1% 154 79.8% 283 77.1% Grey My results from an aptitude or 14 8.0% 33 17.1% 47 12.8% career-match test A career education class 10 5.7% 15 7.8% 25 6.8% Job shadowing 14 8.0% 32 16.6% 46 12.5% Total 174 100.0% 193 100.0% 367 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A34

Most students from Grey (77.4%) spoke to parents, family members and/or friends about their career interests. Less than half of the students spoke to a guidance counselor or teacher at school. Approximately 6% of the Grey County students did not speak to anyone regarding their career interests.

Table 81: Resources Students Spoke to about their Career Interests by Gender Gender Total County Resource Male Female # % # % # % My parent(s), family, relatives and 131 75.3% 153 79.3% 284 77.4% friends A guidance counselor, career edu- 72 41.4% 100 51.8% 172 46.9% Grey cation advisor, or teacher at school Someone working in the profession 60 34.5% 89 46.1% 149 40.6% No one 18 10.3% 5 2.6% 23 6.3% Total 174 100.0% 193 100.0% 367 100.0% The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A33

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 82 3.3.12 Future Place of Work and Residence The out-migration of youth is a common trend faced by rural regions of Ontario, including the Four County Region. This has an impact on the future labour market supply as it determines the availability of the workforce, as well as the quality. A considerable number of youth across the region report intentions of out-migration. In all four counties, students are more likely to believe they will not find a job or live in Bruce, Grey, Huron or Perth County. In Grey County specifically, 58.1% of males and 66.3% of females do not expect to find a job or live in the Four County Region.

Table 82: Students Expectations to Find a Job and Live in Bruce, Grey, Huron, Perth County by Gender

Gender Do you Expect to Find Total County a Job and Live in Bruce, Male Female Grey, Huron, Perth County? # % # % # % Yes 55 42.3% 42 46.7% 97 44.1% Bruce No 75 57.7% 48 53.3% 123 55.9% Total 130 100.0% 90 100.0% 220 100.0% Yes 67 41.9% 63 33.7% 130 37.5% Grey No 93 58.1% 124 66.3% 217 62.5% Total 160 100.0% 187 100.0% 347 100.0% Yes 73 44.5% 94 48.5% 167 46.6% Huron No 91 55.5% 100 51.5% 191 53.4% Total 164 100.0% 194 100.0% 358 100.0% Yes 92 49.7% 104 49.5% 196 49.6% Perth No 93 50.3% 106 50.5% 199 50.4% Total 185 100.0% 210 100.0% 395 100.0% Yes 287 44.9% 303 44.5% 590 44.7% Total No 352 55.1% 378 55.5% 730 55.3% Total 639 100.0% 681 100.0% 1,320 100.0%

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 83 Those planning on leaving Grey County blame the lack of job opportunities in the area. The majority of students also believe life will be more exciting elsewhere.

Table 83: Reasons for Planning to Leave Grey County to Live and Work by Gender

Gender Total County Reason Male Female # % # % # % There are no jobs here that I am interested in; not enough variety in 46 49.5% 50 40.3% 96 44.2% job opportunities There are no jobs here that 24 25.8% 18 14.5% 42 19.4% pay enough Grey There are not enough jobs 22 23.7% 23 18.5% 45 20.7% here at all I think life will be more exciting in 50 53.8% 89 71.8% 139 64.1% another place Total 93 100.0% 124 100.0% 217 100.0%

The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A35

Students were asked to identify influential factors for staying in the Four County Region as they pursue a career. Being in close proximity to family and friends was the most common reason for staying in the region (72.3%), followed by their belief that their community is a great place to live (56.2%). However, only 23.1% cited the opportunity for a job in which they are interested as a reason to stay in the area.

Table 84: Student Reasons for Planning to Stay in Grey County by Gender Gender Total County Reason Male Female # % # % # % There are plenty of jobs in the area 18 26.9% 12 19.0% 30 23.1% that I am interested in The jobs here provide a 11 16.4% 5 7.9% 16 12.3% good salary I want to be near my friends Grey 50 74.6% 44 69.8% 94 72.3% and family

I like my community and think it is 40 59.7% 33 52.4% 73 56.2% a great place to live Total 67 100.0% 63 100.0% 130 100.0% The percentages in the table may add up to more than 100% since some students identified more than one category. *For full Four County results refer to Appendix Table A36

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 84 3.4 Summary Grey County had 174 male respondents (47.4%) and 193 female respondents (52.6%) for the survey of grade 12 students. The majority of respondents were 17 years old.

The average for all school classes in the last school year was 76.7% for males and 78.8% for females. Generally students reported English as the highest average for core courses (English, math and science). Males in Grey tend to favour technology education elective courses, females are more likely to be engaged in arts elective courses. There was an increase in average class scores between the two study periods, this may be in part to surveying only grade 12 students in 2011 versus students in grades 10 through 12 in 2005.

The majority of students participate in extra-curricular activities where they spend 7.9 hours per week on average. The most common extra-curricular activities are related to sports and physical activity. This observation was also made in the previous studies.

Students are continuing to be engaged in volunteer activity, 82.8% of females and 71.8% of males in Grey County in the last year. The average number of hours spent volunteering over the last year was 50.2 hours, well over the 40 hours required for their high school career. The most common industries students reported volunteer participation were similar to 2005 which included Information, Culture, and Recreation; Religious, Civic, Environmental or Social Advocacy; Health Care or Social Assistance, and the addition of Agriculture and Education.

Fewer Grey County students held a part-time or summer job compared to the previous study. In 2013, 70.1% of males and 72.3% of females worked part-time during the school year and 78% of males and 74.5% of females worked in the summer. The most common part-time and summer employment activities include Wholesale and Retail Trade; Accommodation and Food Services; Arts, Entertainment, Recreation, and Construction and/or Specialty Trade Contractor.

Co-op education in Grey County has fairly low participation, only 11.5% of males and 18.7% of females have participated in co-op in the last year. Males participating in co-op were most likely to be involved in Other services including repair and maintenance and automotive repair, females participating in co-op were most likely to be involved in Health Care and Social Assistance and Educational Services.

For transferable skills, males have scored themselves the highest in analytical, decision making and problem solving and teamwork. In 2005, they considered themselves strongest in physical and mechanical work. Females have scored themselves the highest in social, interpersonal skills and reading.

In Grey, 92% of students expect to finish high school and continue onto post-secondary school or an apprenticeship program. Females are more likely to be planning on attending post-secondary education than males. College is the most common post-secondary education choice for students, followed by university. Males are much more likely to enroll in a trade, vocational or apprenticeship with 23% of the male respondents planning to attend a trade program compared to 2.7% of females.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 85 The top industry categories that male students are hoping to be employed are: Professional, Scientific and Technical Services; Construction and/or Specialty Trade Contractor; and Health Care and Social Assistance. Females are expecting to be employed in Health Care and Social Assistance; Arts, Entertain- ment, Recreation; and, Professional, Scientific and Technical Services.

Youth out-migration has been an issue in rural communities as 58.1% of males and 66.3% of females expect to leave the Four County Region to find a job. This was a considerable increase since the last study period.

The unemployment rate for Grey County youth aged 15 to 24 was 21% in 2011 which was considerably higher than the provincial youth unemployment rate of 16%.

SECTION 3: GREY HIGH SCHOOL STUDENT SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 86 Fact Sheet - Grey County Employee Experiences

The study carried out for the Four County Labour Market Planning Board in 2013 included a labour market profile and surveys with high school students, employees and employers in Bruce, Grey, Huron and Perth counties. Where possible comparisons to the 2005 study were made.

This fact sheet focuses on the key findings gathered from the Grey County employees surveyed by telephone in the summer of 2013. Grey County had 149 male respondents (49.5%) and 152 female respondents (50.5%) and the average age of respondents was 48.7 years.

35 30 25 20 15 10 5 0

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 87

70 80

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 88 0 10 20 30 40 50 60

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 89 4.0 Grey Employee Survey

4.1 Introduction A fundamental input into a labour market study is information pertaining to the education, experience, skills and training of the current labour pool. This provides a basis for understanding the human resources available to employers in the area. As such, a telephone survey of the people composing the local labour force was deemed to be the best method to gain such information. The survey was designed to capture the relevant components necessary for the continued development of the labour market. The aim of the survey was to determine the particular levels of work experience, education and skills possessed by the residents of the area, as well as information on mobility, household activities and job satisfaction.

4.2 Methodology 4.2.1 Survey Design The design of the survey instrument was based on three criteria. The first was to ensure the survey met the needs of the study including requirement to collect information on the skills, training and education of the current labour pool in addition to the demographic information required to describe the socio-economic status of the County.

The second was the need to design the instrument in a manner that would allow for comparison with the employer and the high school survey for the study. This was critical in the design as a primary output of the project was to perform a gap analysis among the three surveys. Comparisons to the Statistics Canada database was also a key consideration to gauge the representativeness of the sample within the context of the population at large.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 90 The third consideration was the need to design the instrument in a manner that would allow for the comparison to the studies completed in 2005.

A draft version of the survey was generated and provided to the steering committee for review. Revisions suggested by the steering committee were incorporated into the draft. A pre-test of the redraft was conducted to ensure clarity of the questions, test the data input program, verify the survey output and validate the randomized calling process.

4.2.2 Survey Process A team of eight graduate students was hired to conduct the surveys. There was a two hour training session providing an overview of the project as well as specific training on the survey instrument.

The survey commenced on May 7, 2013 and concluded on July 17, 2013. Calls were made in the evenings from Monday to Friday. No surveys were carried out on the weekends, or on Mondays of a holiday weekend (Victoria Day, Canada Day).

4.2.3 Sampling Strategy The labour force population survey was administered using a telephone interview. Potential participants for the survey were selected according to a randomized calling strategy. The unit of analysis for the sample was the household. Any participant within the household that met the following eligibility requirements was invited to participate: • Permanent resident of Grey County • Legally permitted to work in Canada • Over 16 years of age • Not retired

Interviewers made calls from the region’s phonebook. The randomized calling strategy was achieved by consulting a random number table. The number generated by this table was then applied to the phonebook to select an entry. If a household was unreachable after three attempts that number was removed from the calling list. In instances where a household was unreachable replacement numbers were generated using a calling rule that directed them to a phone book row above or below the original entry selected.

The total population, ages 15 and over, employed across all industrial sectors in Grey County in 2011 was 76,335. For the survey sample to be statistically representative of the population of employees and to have a ±5% confidence interval and a 95% confidence level, it is technically necessary to obtain approximately 380 valid responses from randomly selected employees in the sample frame. For the purpose of this study it was decided to limit the survey to 300 valid responses. A total of 301 surveys were actually completed which provides a confidence level of 95% with a ±6% confidence interval.

The sample was stratified to ensure an even split of male and female respondents.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 91 4.3 Survey Analysis 4.3.1 Response Rate As noted above, the sampling strategy resulted in the completion of 301 surveys. Approximately 11 households were contacted for every survey completed (the non-response households included refusals, no one home, retirees).

4.3.2 Respondent Profile 4.3.2.1 Age and Gender Distribution For each of the four counties the survey aimed to have a 50:50 male to female ratio. Grey County had 149 male respondents (49.5%) and 152 female respondents (50.5%).

Table 85: Gender of Respondents Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Gender # % # % # % # % # % Male 150 49.8 149 49.5 145 48.2 150 49.3 594 49.2 Female 151 50.2 152 50.5 156 51.8 154 50.7 613 50.8

Total 301 100.0 301 100.0 301 100.0 304 100.0 1207 100.0

The average age of respondents from Grey County was 48.7 years, the highest of the Four County Region. Only 7% of the Grey County respondents were younger than 30 years old, 20% were over 60 years, 35.5% of the respondents were between 50 and 59 years old.

Table 86: Age of Respondents for Bruce, Grey, Huron and Perth County Bruce Grey Huron Perth Total Age # % # % # % # % # % 16 to 19 4 1.4 3 1.0 4 1.4 6 2.0 17 1.4

20 to 29 27 9.2 19 6.4 24 8.1 19 6.4 89 7.5

30 to 39 43 14.6 51 17.2 45 15.3 51 17.3 190 16.1

40 to 49 62 21.0 58 19.6 76 25.8 70 23.7 266 22.5

50 to 59 113 38.3 105 35.5 86 29.2 96 32.5 400 33.9

60 to 69 38 12.9 51 17.2 47 15.9 46 15.6 182 15.4

70 and over 8 2.7 9 3.0 13 4.4 7 2.4 37 3.1

Total 295 100.0 296 100.0 295 100.0 295 100.0 1181 100.0

Average 48.3 48.7 48.2 48.3 48.4 age

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 92 4.3.2.2 Household Income Household income is a relative measure of well-being for area residents. The figures in Table 87 are the self-reported figures representing a private household unit. The most common household income category reported was $120,000 and over with 21.2% of the responses. Comparing the reported household income of the survey respondents to data from the NHS shows that this is not completely representative of the area. The average household income in Grey in 2011 was 56,518, and the most common income category was $60,000 to $79,999.

It should be noted that the response rate for household income is lower than less sensitive questions. It may be the case that those respondents that did not respond to this specific question were those in the lower income categories.

Table 87: Respondents Household Income Categories in Bruce, Grey, Huron and Perth County

Household Bruce Grey Huron Perth Total Income # % # % # % # % # %

Under $20,000 9 4.2 11 4.9 6 2.7 8 3.7 34 3.9

$20,000 - $39,999 16 7.4 33 14.6 24 10.8 29 13.2 102 11.6

$40,000 - $59,999 31 14.4 46 20.4 39 17.6 36 16.4 152 17.2

$60,000 - $79,999 27 12.5 35 15.5 48 21.6 34 15.5 144 16.3

$80,000 - $99,999 30 13.9 28 12.4 36 16.2 32 14.6 126 14.3

$100,000 - 27 12.5 25 11.1 24 10.8 36 16.4 112 12.7 $119,999

$120,000 and over 76 35.2 48 21.2 45 20.3 44 20.1 213 24.1

Total 216 100.0 226 100.0 222 100.0 219 100.0 883 100.0

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 93 4.3.2.3 Marital Status Marital status gives an indication of the composition of family units in the Four County Region. The marital status of respondents is found in Table 88. The majority (64.1%) of Grey County respondents were legally married, another 12.8% reported as single and 10.1% were in a common-law partnership.

Table 88: Marital Status of Respondents for Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Marital Status # % # % # % # % # % Single 37 12.5 38 12.8 40 13.3 47 15.6 162 13.5 Legally married 202 68.2 191 64.1 211 70.1 216 71.8 820 68.6 Common-law 18 6.1 30 10.1 14 4.7 9 3.0 71 5.9

Separated but still 9 3.0 12 4.0 8 2.7 8 2.7 37 3.1 legally married

Divorced 19 6.4 19 6.4 19 6.3 11 3.7 68 5.7 Widowed 11 3.7 8 2.7 9 3.0 10 3.3 38 3.2 Total 296 100.0 298 100.0 301 100.0 301 100.0 1,196 100.0

4.3.3 Labour Market Features There are a number of basic features that are key in providing a framework for understanding local economies. For the purpose of this study employment status and experience, education, skills and training were examined.

4.3.3.1 Employment There are a number of aspects of employment that are covered both by the NHS and the employee survey completed for the study. To describe the dynamics of employment in the Four County Region the following survey variables have been selected: employment status, employment basis and number of jobs held. Unemployment in the Region and the mechanisms for support of the employment was also reviewed.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 94 Employment Status For the Four County Region, 89.5% of the respondents had been employed in the last 52 weeks. In Grey County, the employment rate among respondents was 90.7%.

Table 89: Employment Status of Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # %

Yes 274 91 273 90.7 267 88.7 266 87.5 1,080 89.5

No 27 9 28 9.3 34 11.3 38 12.5 127 10.5

Total 301 100 301 100 301 100 304 100 1,207 100

In Grey County, 84.4% of respondents were employed at the time of the survey. For the entire Four County Region, 85.1% of the respondents were employed. In Grey, 6.3% of the respondents reported being a homemaker, 3.3% were unemployed and 2.7% were on disability leave.

Table 90: Respondents’ Work Status for Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Work Status # % # % # % # % # %

Employed 264 87.7 254 84.4 257 85.4 252 82.9 1027 85.1

Unemployed 13 4.3 10 3.3 13 4.3 11 3.6 47 3.9

Student 6 2 9 3 9 3 6 2 30 2.5

Homemaker 14 4.7 19 6.3 17 5.6 25 8.2 75 6.2

Disabled 3 1 8 2.7 4 1.3 7 2.3 22 1.8

Maternity 1 0.3 1 0.3 1 0.3 3 1 6 0.5 leave

Total 301 100 301 100 301 100 304 100 1207 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 95 Respondents who reported to be unemployed in the last 52 weeks were asked to provide information about their incomes sources so as to help understand the structure of unemployment in the area. Table 91 provides the information for the Four County Region. Approximately 5% of the respondents were supported by others, 2% depended on ODSP.

Table 91: Income Sources for Unemployed Respondents for Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Household Income # % # % # % # % # %

Supported by others 14 4.7 15 5 15 5 23 7.6 67 5.6

Investment income 3 1 1 0.3 1 0.3 0 0 5 0.4

Loans 0 0 1 0.3 2 0.7 1 0.3 4 0.3

Employment 3 1 1 0.3 2 0.7 5 1.6 11 0.9 insurance

Social assistance 2 0.7 1 0.3 6 2 2 0.7 11 0.9

Informal income 0 0 3 1 1 0.3 0 0 4 0.3

ODSP 3 1 6 2 5 1.7 3 1 17 1.4

CPP 3 1 2 0.7 4 1.3 3 1 12 1

WSIB pension 0 0 1 0.3 1 0.3 1 0.3 3 0.2

Child tax benefit 0 0 2 0.7 3 1 1 0.3 6 0.5

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 96 Primary Employment In Grey County, 20.3% of the respondents held multiple jobs, the highest proportion among the Four County Region. On average, 16.4% of the respondents held multiple jobs in the Four County Region.

Table 92: Multiple Jobs for Respondents from Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total

# % # % # % # % # %

Yes 35 12.7 56 20.3 33 12.3 54 20.2 178 16.4

No 240 87.3 220 79.7 235 87.7 213 79.8 908 83.6

Total 275 100 276 100 268 100 267 100 1,086 100

In reference to primary employment, 66.8% of the Grey County respondents have a permanent job compared to 70.1% across the Four County Region. In Grey County 22% of the respondents are self- employed, the highest among the four counties.

Table 93: Employment Basis for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Job Type # % # % # % # % # %

Permanent basis 172 72.6 145 66.8 157 67.4 156 73.6 630 70.1

Contract / seasonal 24 10.1 13 6 22 9.4 13 6.1 72 8 basis

Self-employed 36 15.2 49 22.6 46 19.7 36 17 167 18.6

Casual basis 5 2.1 10 4.6 8 3.4 7 3.3 30 3.3 Total 237 100 217 100 233 100 212 100 899 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 97 As shown in Table 94, 76% of Grey County respondents’ primary employment is on a full-time basis, the lowest of all four counties. It is likely that the high response rate of multiple job holdings relate to the higher rate of respondents employed on a part-time basis.

Table 94: Employment Status for Bruce, Grey, Huron and Perth County Respondents

Employment Bruce Grey Huron Perth Total Type # % # % # % # % # %

Part time 38 16 52 24 42 17.9 46 21.7 178 19.8

Full time 199 84 165 76 192 82.1 166 78.3 722 80.2

Total 237 100 217 100 234 100 212 100 900 100

Respondents were asked to indicate how many hours per week, on average they work at their primary place of employment. On average, Grey County respondents work 39.4 hours per week. The average Four County Region respondent works 39.8 hours per week.

Table 95: Hours per Work at Primary Employment for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Hours per Week # % # % # % # % # % Less than 10 4 1.5 13 4.8 2 0.7 7 2.6 26 2.4 hours

10 to 19 hours 15 5.5 15 5.5 12 4.5 20 7.5 62 5.7

20 to 29 hours 27 9.9 35 12.8 35 13.1 32 12 129 12

30 to 39 hours 68 24.9 57 20.9 51 19.1 62 23.3 238 22.1

40 to 49 hours 105 38.5 102 37.4 103 38.6 94 35.3 404 37.4

50 to 59 hours 32 11.7 22 8.1 38 14.2 35 13.2 127 11.8

60 or more hours 22 8.1 29 10.6 26 9.7 16 6 93 8.6

Total 273 100 273 100 267 100 266 100 1,079 100

Average hours 40.1 39.4 40.4 39 39.8

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 98 On average, Grey County respondents have been employed with their current employer for 12.6 years, approximately one year less than the Four County Region average. Just over 30% of Grey County respondents reported to be in the same primary employment between 6 and 15 years.

Table 96: Number of Years with Primary Employer for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Years # % # % # % # % # %

Less than 12 months 24 8.8 27 10 19 7.1 14 5.3 84 7.8

1 to 5 years 70 25.7 76 28 62 23.2 59 22.4 267 24.9

6 to 10 years 63 23.2 47 17.3 42 15.7 51 19.4 203 18.9

11 to 15 years 38 14 35 12.9 34 12.7 45 17.1 152 14.2

16 to 20 years 8 2.9 21 7.7 31 11.6 23 8.7 83 7.7

More than 20 years 69 25.4 65 24 79 29.6 71 27 284 26.5

Total 272 100 271 100 267 100 263 100 1,073 100

Average years 12.6 12.6 15.2 14.2 13.7

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 99 Secondary Employment On average 16.1% of the respondents from the Four County Region reported they hold multiple jobs. In Grey County, 54 of 276 respondents hold a second job. From Table 97, of those that hold a second job in Grey County, 40.7% reported being self-employed and 24.1% of second jobs are on a causal basis.

Table 97: Secondary Employment Basis for Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Job Type # % # % # % # % # %

Permanent basis 7 20.6 8 14.8 4 12.5 17 31.5 36 20.7

Contract / seasonal 2 5.9 11 20.4 7 21.9 9 16.7 29 16.7 basis

Self-employed 16 47.1 22 40.7 13 40.6 18 33.3 69 39.7

Casual basis 9 26.5 13 24.1 8 25 10 18.5 40 23

Total 34 100 54 100 32 100 54 100 174 100

Of those that hold a second job in Grey County, 92.6% reported working part-time in their second job.

Table 98: Employment Status for Secondary Employment for Bruce, Grey, Huron and Perth County

Employment Bruce Grey Huron Perth Total Type # % # % # % # % # %

Part time 31 91.2 50 92.6 30 93.8 48 88.9 159 91.4

Full time 3 8.8 4 7.4 2 6.3 6 11.1 15 8.6

Total 34 100 54 100 32 100 54 100 174 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 100 Tertiary Employment On average 2.6% of the respondents from the Four County Region reported they hold multiple jobs. In Grey County, 12 of 276 respondents hold a third job. The majority (75%) of those in Grey County with a third job work on a contract or seasonal basis.

Table 99: Employment Basis for Tertiary Employment in Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Job Type # % # % # % # % # %

Permanent basis 0 0 1 8.3 0 0 0 0 1 3.6

Contract / seasonal 1 20 9 75 1 33.3 4 50 15 53.6 basis

Self-employed 2 40 2 16.7 1 33.3 1 12.5 6 21.4

Casual basis 2 40 0 0 1 33.3 3 37.5 6 21.4

Total 5 100 12 100 3 100 8 100 28 100

From the table below, in Grey County, 91.7% work part-time in their third job. This is consistent with the Four County Region average of 92.9%

Table 100: Employment Status of Tertiary Employment in Bruce, Grey, Huron and Perth County

Employment Bruce Grey Huron Perth Total Type # % # % # % # % # % Part time 4 80 11 91.7 3 100 8 100 26 92.9

Full time 1 20 1 8.3 0 0 0 0 2 7.1

Total 5 100 12 100 3 100 8 100 28 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 101 4.3.3.2 Employment Experience There are a variety of occupation and industry specific skills that can be acquired from employment. Skills learned in both specific occupations and specific industries endow the employee with experience learned from both their employment and the business climate in which they work.

Occupation The most basic description of what people do at work can be circumscribed by their occupation classification. An occupation title is linked to a standard set of skills that are required to perform the day to day operations of that occupation in the workplace. The standard format for classifying and presenting occupation specific data is the National Occupation Classification System (NOC-S).

For the purpose of this analysis, only the occupation of primary employment was examined, as shown in Table 101.

Table 101: Occupation Classification by Respondents for Bruce, Grey, Huron and Perth County

Bruce Grey Huron Perth Total Occupation # % # % # % # % # % Management Occupations 35 12.9 33 12.1 41 15.5 29 10.9 138 12.8

Business, Finance and 29 10.7 37 13.6 32 12.1 45 16.9 143 13.3 Administrative Occupations

Natural and Applied Sciences 9 3.3 4 1.5 6 2.3 5 1.9 24 2.2 and Related Occupations

Health Occupations 28 10.3 28 10.3 28 10.6 18 6.8 102 9.5 Occupations in Social Science, Education, Government Service 42 15.4 33 12.1 36 13.6 29 10.9 140 13 and Religion

Occupations in Art, Culture, 1 0.4 4 1.5 5 1.9 10 3.8 20 1.9 Recreation and Sport

Sales and Service Occupations 46 16.9 51 18.7 28 10.6 40 15 165 15.3

Trades, Transport and Equipment Operators and 48 17.6 47 17.2 44 16.6 37 13.9 176 16.4 Related Occupations

Occupations Unique to Primary 13 4.8 11 4 33 12.5 26 9.8 83 7.7 Industry

Occupations Unique to Processing, 21 7.7 25 9.2 12 4.5 27 10.2 85 7.9 Manufacturing and Utilities Total 272 100 273 100 265 100 266 100 1076 100

= Top Three Reported Occupations in Grey

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 102 In a direct comparison between the occupation reported by respondents and the occupations reported by Statistics Canada, the survey is largely representative.

Table 102: Grey County Respondents Occupation Classification Compared to NHS 2011 Respondents NHS Occupation # % # % Management Occupations 33 12.1 5,895 12.5

Business, Finance and 37 13.6 6,150 13 Administrative Occupations

Natural and Applied Sciences and 4 1.5 1,755 3.7 Related Occupations

Health Occupations 28 10.3 3,570 7.5

Occupations in Social Science, Education, Government Service 33 12.1 4,705 9.9 and Religion

Occupations in Art, Culture, 4 1.5 1,115 2.4 Recreation and Sport

Sales and Service Occupations 51 18.7 10,565 22.3

Trades, Transport and Equipment 47 17.2 8,700 18.4 Operators and Related Occupations

Occupations Unique to Primary 11 4 1,840 3.9 Industry

Occupations Unique to Processing, 25 9.2 3,005 6.4 Manufacturing and Utilities

Industry In addition to the data collected on occupation, industry concentrations is essential to the composition of the labour market. Experience in a given industry provides certain industry-specific skills available for transfer within the labour market for employment.

The standard format for classifying and presenting industry specific data is the North American Industry Classification System (NAICS). For the purpose of this analysis, only the industry of primary employment was examined. In Grey County, the top reported industry was Health Care and Social Assistance 16.8%. The remaining leading industries as reported by Grey County respondents were Retail Trade (11.7%) and Manufacturing (11.4%).

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 103 In comparison to the Four County Region, Grey County had the lowest proportion engaged in Agriculture, forestry, fishing and hunting and the highest proposition engaged in Construction, as reported by respondents.

Table 103: Respondents by Industrial Sector for Bruce, Grey, Huron and Perth County Bruce Grey Huron Perth Total Industry # % # % # % # % # % Agriculture, forestry, fishing 16 5.9 14 5.1 40 15 36 13.5 106 9.8 and hunting Mining, quarrying, and oil and 1 0.4 2 0.7 7 2.6 0 0 10 0.9 gas extraction Utilities 57 20.9 8 2.9 9 3.4 4 1.5 78 7.2 Construction 20 7.3 28 10.3 21 7.9 13 4.9 82 7.6 Manufacturing 11 4 31 11.4 27 10.2 39 14.7 108 10 Wholesale trade 9 3.3 5 1.8 3 1.1 8 3 25 2.3 Retail trade 25 9.2 32 11.7 18 6.8 18 6.8 93 8.6 Transportation and warehousing 3 1.1 11 4 9 3.4 8 3 31 2.9 Information and cultural industries 2 0.7 5 1.8 1 0.4 0 0 8 0.7 Finance and insurance 7 2.6 8 2.9 10 3.8 27 10.2 52 4.8 Real estate and rental and leasing 3 1.1 3 1.1 4 1.5 1 0.4 11 1 Professional, scientific and 18 6.6 13 4.8 9 3.4 17 6.4 57 5.3 technical services Management of companies and 0 0 0 0 2 0.8 0 0 2 0.2 enterprises

Administrative and support, waste management and remediation 1 0.4 1 0.4 0 0 0 0 2 0.2 services. Educational services 29 10.6 21 7.7 27 10.2 23 8.6 100 9.3 Health care and social assistance 35 12.8 46 16.8 45 16.9 28 10.5 154 14.3 Arts, entertainment and recreation 6 2.2 5 1.8 9 3.4 10 3.8 30 2.8 Accommodation and food services 7 2.6 10 3.7 11 4.1 10 3.8 38 3.5 Other services (except public 13 4.8 16 5.9 7 2.6 11 4.1 47 4.4 administration) Public administration 10 3.7 14 5.1 7 2.6 13 4.9 44 4.1 Total 273 100 273 100 266 100 266 100 1,078 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 104 In comparison to the Industries reported by Statistics Canada from the 2011 NHS, the greatest differentia- tion was in Health Care and Social Assistance, which was over represented in the survey. Administrative and support, waste management and remediation services was under represented, as presented in the table below.

Table 104: Grey County Respondents Reported Industry Compared to NHS 2011

Respondents NHS Industry # % # % Agriculture, forestry, fishing and 14 5.1 3,270 6.8 hunting Mining, quarrying, and oil and gas 2 0.7 245 0.51 extraction Utilities 8 2.9 655 1.36 Construction 28 10.3 4,455 9.26 Manufacturing 31 11.4 5,410 11.25 Wholesale trade 5 1.8 1,290 2.68 Retail trade 32 11.7 5,265 10.95 Transportation and warehousing 11 4 1,605 3.34 Information and cultural industries 5 1.8 575 1.2 Finance and insurance 8 2.9 1,365 2.84 Real estate and rental and leasing 3 1.1 930 1.93 Professional, scientific and 13 4.8 2,180 4.53 technical services Management of companies and 0 0 0 0 enterprises Administrative and support, waste management and remediation 1 0.4 1,915 3.98 services. Educational services 21 7.7 2,880 5.99 Health care and social assistance 46 16.8 6,250 13 Arts, entertainment and recreation 5 1.8 1,200 2.5 Accommodation and food services 10 3.7 3,100 6.45 Other services 16 5.9 2,075 4.32 (except public administration) Public administration 14 5.1 2,605 5.42

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 105 4.3.3.3 Education The current labour market demands a base level of education for most forms of employment. The education levels as well as the major field of study shapes the labour market opportunities for those seeking employment.

A large portion (35.7%) of Grey County respondents’ highest level of education was high school. Another 34.4% reported college or a speciality school as their highest completed education. As shown in the table below, 9% of Grey County respondents have not completed high school.

Table 105: Highest Education Level for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Highest Education # % # % # % # % # %

Not completed high 21 7 27 9 31 10.3 36 11.9 115 9.5 school

High School 77 25.6 107 35.7 81 26.9 89 29.4 354 29.4 Trade School 12 4 16 5.3 7 2.3 10 3.3 45 3.7 College/Specialty School 108 35.9 103 34.3 108 35.9 105 34.7 424 35.2 University - 67 22.3 34 11.3 63 20.9 49 16.2 213 17.7 Undergraduate Degree

University - 15 5 13 4.3 10 3.3 12 4 50 4.1 Master’s Degree

University- Ph.D. 1 0.3 0 0 1 0.3 2 0.7 4 0.3

Total 301 100 300 100 301 100 303 100 1205 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 106 The concentrations for the major fields of study are provided below.

Table 106: Major Field of Study of Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Major Field of Study # % # % # % # % # % Education 23 11.4 14 8.2 16 8.4 13 7.3 66 8.9 Visual and performing arts, and 4 2 7 4.1 11 5.8 4 2.2 26 3.5 communications technologies Humanities 5 2.5 12 7 7 3.7 7 3.9 31 4.2 Social and behavioural sciences 14 6.9 13 7.6 16 8.4 23 12.9 66 8.9 and law Business, management, and 26 12.9 29 17 29 15.2 36 20.2 120 16.2 public administration Physical and life sciences and 19 9.4 5 2.9 12 6.3 7 3.9 43 5.8 technologies Mathematics, computer and 5 2.5 1 0.6 6 3.1 4 2.2 16 2.2 information sciences Architecture, engineering, and 24 11.9 10 5.8 10 5.2 7 3.9 51 6.9 related technologies Agriculture, natural resources, 11 5.4 10 5.8 15 7.9 17 9.6 53 7.1 and conservation Health, parks, recreation, and 28 13.9 28 16.4 35 18.3 25 14 116 15.6 fitness Personal, protective, and 8 4 3 1.8 3 1.6 1 0.6 15 2 transportation services General study 19 9.4 16 9.4 13 6.8 11 6.2 59 8 Trades 16 7.9 23 13.5 18 9.4 23 12.9 80 10.8 Total 202 100 171 100 191 100 178 100 742 100

= Top Three Fields of Study in Grey

The reported concentrations for the major fields of study from the survey are comparable to the Census, Business was a top ranked field of study for both men and women, and Health was the second most common field of study for women in Grey County.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 107 4.3.3.4 Skills An individual’s skill set is equally as important as their education background in the labour market. Their skills are a collection of abilities that are at their disposal and are able to use to perform in their job. The arrays of skills covered in the survey are those that are either generally in demand in the workplace or are broad based job-transferable skills.

The ability to speak more than one language is considered a valuable skill set, especially in an increasingly globalized labour market. Approximately 20% of all Four County Region respondents are able to speak a second language, other than English, well enough to hold a conversation. Grey County respondents scored slightly higher at 22%, the highest among the Four County Region.

Table 107: Ability to Speak a Second Language by Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Yes 53 17.6 66 22 55 18.3 58 19.1 232 19.2 No 248 82.4 234 78 246 81.7 246 80.9 974 80.8 Total 301 100 300 100 301 100 304 100 1,206 100

Of the 66 individuals who reported being able to speak a second language, 31 are able to speak French well enough to hold a conversation. German and Dutch, as a second language, were also fairly common among the Grey County respondents.

Table 108: Languages Spoken by Bruce, Grey, Huron and Perth County Respondents

Other Bruce Grey Huron Perth Total Languages # % # % # % # % # % French 36 12 31 10.3 27 9 30 9.9 124 10.3

Spanish 4 1.3 9 3 10 3.3 6 2 29 2.4

Dutch 1 0.3 12 4 13 4.3 14 4.6 40 3.3

German 10 3.3 15 5 6 2 7 2.3 38 3.2

ASL 2 0.7 1 0.3 3 1 1 0.3 7 0.6

Other language 9 3 10 3.3 6 2 6 2 31 2.6

Total 301 300 301 304 1,206

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 108 Survey respondents rated their perception of their own skills in a number of categories. There was a 5-point scale to self-rate their skills; a score of 1 was very poor and 5 was very good.

Foundational to all jobs is a certain baseline skills set. In Grey County, respondents self-rated the following skills the highest: • Reading • Verbal communication • Teamwork • Written communication • Social or interpersonal • Critical thinking or problem solving

As expected, occupation or industry specific skills such as Skilled Trades and AutoCAD were rated much lower, as fewer individuals require these skills.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 109 Table 109 provides a summary of the skill set of the Four County Region survey respondents.

Table 109: Self-Assessment of Skills by Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total

Aver- Aver- Aver- Aver- Aver- # age # age # age # age # age Reading skills 300 4.5 300 4.4 300 4.3 303 4.3 1,203 4.4 Verbal communi- 300 4.3 300 4.3 299 4.3 303 4.3 1,202 4.3 cation skills Teamwork skills 300 4.4 299 4.3 300 4.3 303 4.3 1,202 4.3 Written communi- 300 4.2 300 4.2 300 4.1 303 4.1 1,203 4.1 cation skills Social/ 300 4.2 300 4.2 300 4.1 303 4.2 1,203 4.2 Interpersonal skills Critical thinking/ 300 4.2 300 4.2 300 4.2 303 4.2 1,203 4.2 problem solving Leadership 300 4.1 298 4.1 300 4.1 303 4 1,201 4.1 Organizational 300 4.2 300 4 300 4 303 4.1 1,203 4.1 skills Math skills 300 4 300 3.8 300 3.8 303 3.9 1,203 3.9 Physical, mechanical, 300 3.7 299 3.8 300 3.8 303 3.6 1,202 3.7 hands-on skills Internet and information 299 3.7 299 3.6 299 3.6 302 3.6 1,199 3.6 technology Artistic, 300 3.2 300 3.4 300 3.2 302 3.1 1,202 3.2 creative skills Word Processing 299 3.3 299 3.2 300 3.2 302 3.2 1,200 3.2 Agricultural skills 299 2.9 299 2.9 299 3 302 2.9 1,199 2.9 Education sector 300 3.2 294 2.9 299 2.9 302 2.8 1,195 2.9 skills Manufacturing 299 2.6 294 2.7 299 2.6 302 2.6 1,194 2.6 specific skills Spreadsheets 299 3 299 2.7 300 2.7 302 2.8 1,200 2.8 Information 299 2.9 298 2.7 300 2.7 302 2.7 1,199 2.7 Technology Health and social 300 2.6 293 2.7 300 2.7 300 2.5 1,193 2.6 service sector skills Construction / 298 2.8 294 2.7 299 2.5 300 2.3 1,191 2.6 skilled trades Database 299 2.7 298 2.5 300 2.5 302 2.5 1,199 2.5 AutoCAD / 298 1.9 290 1.7 298 1.7 300 1.7 1,186 1.7 Engineering skills

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 110 4.3.3.5 Training In order to keep up with the ever changing labour market many employers and employees feel it is necessary to upgrade their education and training. The survey asked respondents about their upgrading activities in the last year. In Grey County, 57.7% of respondents did not participate in any upgrading activities. The most common type of training or education in the last year was an industry or occupation specific course, workshop or conference with 26.6% of Grey County respondents. Another 6% have completed workplace safety or first aid training and 5.6% completed a college or university course.

Table 110: Training and Education Upgrading of Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Other Training # % # % # % # % # % No training / education in last 160 53.2 179 59.5 176 58.5 181 59.5 696 57.7 year

College or university course 11 3.7 17 5.6 18 6 21 6.9 67 5.6

Small business management skills 6 2 10 3.3 3 1 2 0.7 21 1.7 course

Accounting or bookkeeping skills 1 0.3 3 1 5 1.7 1 0.3 10 0.8

Teamwork or conflict resolution 2 0.7 2 0.7 1 0.3 1 0.3 6 0.5 skills Workplace safety or first aid 20 6.6 18 6 25 8.3 14 4.6 77 6.4 course

Customer service skills 1 0.3 1 0.3 1 0.3 2 0.7 5 0.4

Adult education course 1 0.3 2 0.7 2 0.7 0 0 5 0.4

Internships/Apprenticeships 1 0.3 0 0 3 1 1 0.3 5 0.4

Language training 0 0 0 0 1 0.3 1 0.3 2 0.2

Industry or occupation specific 111 36.9 80 26.6 89 29.6 96 31.6 376 31.2 course/workshop/conference

WHIMIS / food handling 3 1 3 1 5 1.7 1 0.3 12 1

Computer skills 4 1.3 3 1 3 1 4 1.3 14 1.2

Total 301 301 301 304 1207

Respondents were also asked about what training or education programs they would like to participate in that they believe is not offered in their area. As shown in Table 111, the majority of respondents believe that no training is needed. In Grey County, 15.7% of respondents would like to participate in a college or

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 111 university course and 9.1% would like to participate in industry specific training. Grey County respondents are the least likely to want an adult education course in the Four County Region.

Table 111: Desired Training or Education by Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total Training # % # % # % # % # % No training needed 81 57 79 65.3 81 64.8 87 70.7 328 64.2

Adult education course 14 9.9 8 6.6 17 13.6 18 14.6 57 11.2

College or university 27 19 19 15.7 20 16 12 9.8 78 15.3 course

Workplace safety or first 2 1.4 0 0 2 1.6 6 4.9 10 2 aid course

Internships/ 5 3.5 1 0.8 0 0 4 3.3 10 2 Apprenticeships

Language training 8 5.6 4 3.3 2 1.6 7 5.7 21 4.1

Industry specific training 12 8.5 11 9.1 6 4.8 5 4.1 34 6.7

Certification programs 3 2.1 1 0.8 0 0 0 0 4 0.8

Total 142 121 125 123 511

4.3.3.6 Job Satisfaction The level of satisfaction of the respondents in their current employment is an important aspect of their quality of life and is an indicator of their commitment to their employer. Respondents were asked to rate how satisfied they were with their primary employment, given their experience, training and education. The majority of Grey County respondents are very satisfied with their current employment. Almost 90% are satisfied or very satisfied with their current employment.

Table 112: Job Satisfaction of Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Very satisfied 130 54.6 109 50.2 80 34.2 93 43.9 412 45.7 Satisfied 86 36.1 85 39.2 128 54.7 96 45.3 395 43.8 Undecided 11 4.6 7 3.2 13 5.6 6 2.8 37 4.1 Dissatisfied 10 4.2 14 6.5 9 3.8 15 7.1 48 5.3 Very dissatisfied 1 0.4 2 0.9 4 1.7 2 0.9 9 1 Total 238 100 217 100 234 100 212 100 901 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 112 A sizeable proportion of Grey County respondents believe they are underemployed (19.4%), the highest among the Four County Region. Underemployed was referred to as working less than 30 hours per week, not by choice; when skills are underutilized; when wages, productivity or other job qualities are substandard relative to skill and education level.

Table 113: Perceived Underemployment of Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Yes 42 17.6 42 19.4 34 14.5 35 16.6 153 17 No 196 82.4 174 80.6 200 85.5 176 83.4 746 83 Total 238 100 216 100 234 100 211 100 899 100

A major component of job satisfaction relates to the compensation for the work done. Respondents were asked to describe how they feel about their current wage for their primary place of work. The majority of respondents (53%) believe the wages they receive are adequate for the work they do. However, a large proportion of Grey County respondents (22.3%) feel the wages they receive are somewhat less than adequate for the line of work they do.

Table 114: Satisfaction with Wages for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total

# % # % # % # % # % My wages are much less than adequate for the line of work 17 7.2 16 7.4 15 6.4 16 7.6 64 7.1 I do.

My wages are somewhat less than adequate for the line of 31 13.1 48 22.3 50 21.4 36 17.1 165 18.4 work I do.

My wages are adequate for the 134 56.5 114 53 128 54.7 134 63.5 510 56.9 line of work I do.

My wages are somewhat more than adequate for the line of 42 17.7 28 13 32 13.7 20 9.5 122 13.6 work I do.

My wages are much more than adequate for the line of work 13 5.5 9 4.2 9 3.8 5 2.4 36 4 I do. Total 237 100 215 100 234 100 211 100 897 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 113 Survey respondents were asked to think towards the future and describe where they see themselves next year and in five years, in terms of employment. In the next year, 85% of the respondents from Grey County believe they will be in the same job. Almost 5% believe they will be retired, which is comparable for the Four County Region as a whole (5.4%).

Table 115: Where the Bruce, Grey, Huron and Perth County Respondents see themselves in the next year

Bruce Grey Huron Perth Total # % # % # % # % # % In the same job 192 80.7 182 85 189 81.8 183 87.6 746 83.6 In the same job in a different 2 0.8 1 0.5 3 1.3 3 1.4 9 1 industry In a higher position in the same 13 5.5 7 3.3 12 5.2 8 3.8 40 4.5 industry Retired 20 8.4 10 4.7 11 4.8 7 3.3 48 5.4 Unemployed 4 1.7 4 1.9 1 0.4 2 1 11 1.2 Unsure 3 1.3 4 1.9 4 1.7 2 1 13 1.5 Different job 4 1.7 6 2.8 11 4.8 4 1.9 25 2.8 Total 238 100 214 100 231 100 209 100 892 100

In the next five years, only 47.4% of Grey County respondents believe they will be in the same job. Retirements are expected to be quite high, as 28.8% of Grey respondents reported they believe they will be retired in five years.

Table 116: Where the Bruce, Grey, Huron and Perth County Respondents see themselves in the next five years

Bruce Grey Huron Perth Total # % # % # % # % # % In the same job 115 48.3 102 47.4 115 49.4 112 52.8 444 49.4 In the same job in a different 5 2.1 3 1.4 3 1.3 4 1.9 15 1.7 industry

In a higher position in the 26 10.9 23 10.7 31 13.3 23 10.8 103 11.5 same industry

Retired 72 30.3 62 28.8 56 24 46 21.7 236 26.3 Unemployed 1 0.4 2 0.9 1 0.4 2 0.9 6 0.7 Unsure 8 3.4 9 4.2 11 4.7 12 5.7 40 4.5 Different job 9 3.8 11 5.1 11 4.7 9 4.2 40 4.5 Further education 0 0 2 0.9 2 0.9 3 1.4 7 0.8 Move to self-employment 2 0.8 1 0.5 3 1.3 1 0.5 7 0.8 Total 238 100 215 100 233 100 212 100 898 100

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 114 4.3.3.7 Mobility Most of the respondents from Grey County are not willing to relocate outside of the Four County Region. Key factors that would motivate Grey respondents to move away include family or personal reasons (13.6%) and better wages (12%).

Table 117: Factors that would influence Bruce, Grey, Huron and Perth County Respondents to move out of the Region

Bruce Grey Huron Perth Total

# % # % # % # % # % Nothing 113 37.5 99 32.9 115 38.2 105 34.5 432 35.8

Better wage 34 11.3 36 12 44 14.6 41 13.5 155 12.8 More opportunity for 32 10.6 30 10 42 14 25 8.2 129 10.7 jobs / promotion Family and/or personal 55 18.3 41 13.6 27 9 34 11.2 157 13 reasons Job loss 14 4.7 12 4 6 2 12 3.9 44 3.6

Better education / 7 2.3 6 2 2 0.7 1 0.3 16 1.3 training facilities Better benefits 3 1 3 1 2 0.7 0 0 8 0.7

Better working 0 0 1 0.3 0 0 1 0.3 2 0.2 conditions

Better hours 0 0 0 0 1 0.3 2 0.7 3 0.2 Already working outside 0 0 4 1.3 4 1.3 2 0.7 10 0.8 the county

Total 301 301 301 304 1207

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 115 Some of the respondents are willing to move to the United States or abroad, though most are willing to stay within Ontario. Just shy of 10% of Grey County respondents are only willing to move within Grey County, another 11% would only move within the Four County Region.

Table 118: Distance Willing to Relocate for a New Job for Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Not willing to relocate 138 50.4 120 44.1 129 48.5 143 53.8 530 49.2 Within the County I live 23 8.4 26 9.6 18 6.8 23 8.6 90 8.3

Within the 23 8.4 30 11 42 15.8 36 13.5 131 12.2 Four County Region Within the Province of 42 15.3 40 14.7 40 15 33 12.4 155 14.4 Ontario Within Canada 20 7.3 29 10.7 18 6.8 16 6 83 7.7 To the United States or 28 10.2 27 9.9 19 7.1 15 5.6 89 8.3 abroad Total 274 100 272 100 266 100 266 100 1,078 100

4.3.4 Community Characteristics Survey respondents were asked to identify the characteristics and qualities they enjoy about the Four County Region. The rural, small town feel and the sense of community was the highest rated quality by Grey County respondents, followed closely by the overall good quality of life. Other positive qualities included: closeness to family and friends, availability of parks and recreation facilities and friendly neighbours. The remaining qualities can be found in Table 119.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 116 Table 119: Positive Community Characteristics by Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Rural, small town, small 89 29.6 89 29.6 79 26.2 112 36.8 369 30.6 community, sense of community Overall good quality of life 89 29.6 85 28.2 105 34.9 83 27.3 362 30 Close to family and friends 89 29.6 72 23.9 114 37.9 74 24.3 349 28.9 Availability of parks and 114 37.9 72 23.9 56 18.6 26 8.6 268 22.2 recreation facilities Friendly, good neighbours 61 20.3 66 21.9 69 22.9 63 20.7 259 21.5 Quiet, peaceful 42 14 53 17.6 54 17.9 41 13.5 190 15.7 Convenient to get around the 44 14.6 36 12 35 11.6 41 13.5 156 12.9 community / area Relative location to work, other 18 6 25 8.3 18 6 33 10.9 94 7.8 towns, amenities Availability of shopping / 23 7.6 27 9 25 8.3 15 4.9 90 7.5 retail services Scenic location 25 8.3 39 13 8 2.7 11 3.6 83 6.9 Safe, secure, no crime 20 6.6 20 6.6 22 7.3 20 6.6 82 6.8 Availability of health services 25 8.3 24 8 16 5.3 11 3.6 76 6.3 Availability of cultural / 16 5.3 18 6 15 5 25 8.2 74 6.1 entertainment activities Availability of education services 15 5 16 5.3 11 3.7 11 3.6 53 4.4 Availability of affordable 15 5 23 7.6 11 3.7 3 1 52 4.3 housing Availability of job opportunities 20 6.6 7 2.3 7 2.3 2 0.7 36 3 Privacy 8 2.7 15 5 7 2.3 6 2 36 3 Outdoors activities 10 3.3 9 3 4 1.3 1 0.3 24 2 Clean, cleanliness 6 2 7 2.3 4 1.3 7 2.3 24 2 No traffic 10 3.3 7 2.3 2 0.7 2 0.7 21 1.7 Good community to raise 3 1 4 1.3 5 1.7 8 2.6 20 1.7 kids/family Availability of other 6 2 5 1.7 2 0.7 2 0.7 15 1.2 government services Availability of quality housing 4 1.3 6 2 2 0.7 2 0.7 14 1.2 Church, clubs, community 5 1.7 4 1.3 3 1 2 0.7 14 1.2 groups Availability of daycare centres 2 0.7 2 0.7 0 0 1 0.3 5 0.4 Availability of public 0 0 1 0.3 3 1 0 0 4 0.3 transportation Historical features 2 0.7 0 0 1 0.3 0 0 3 0.2 Total 301 301 301 304 1207

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 117 Survey respondents were also asked to identify the characteristics and features they do not like about the Four County Region.

Table 120: Negative Community Characteristics Reported by Bruce, Grey, Huron and Perth County Respondents

Bruce Grey Huron Perth Total # % # % # % # % # % Lack of shopping / retail services 97 32.2 67 22.3 72 23.9 46 15.1 282 23.4 Lack of job opportunities 58 19.3 99 32.9 81 26.9 39 12.8 277 22.9 Lack of cultural / entertainment 48 15.9 42 14 45 15 30 9.9 165 13.7 activities Cost of living (including gas/taxes) 21 7 28 9.3 14 4.7 27 8.9 90 7.5 Weather - winter, winter roads 36 12 17 5.6 17 5.6 13 4.3 83 6.9 Lack of health services 34 11.3 17 5.6 22 7.3 7 2.3 80 6.6 Lack of public transportation 24 8 23 7.6 20 6.6 13 4.3 80 6.6 Distance, isolation 21 7 14 4.7 18 6 14 4.6 67 5.6 Lack of education services 22 7.3 17 5.6 17 5.6 9 3 65 5.4 Not convenient to get around 8 2.7 14 4.7 12 4 20 6.6 54 4.5 the community / area Lack of parks and recreation 10 3.3 6 2 18 6 13 4.3 47 3.9 facilities Municipal government, town 7 2.3 12 4 11 3.7 11 3.6 41 3.4 council, local politics Lack of affordable housing 11 3.7 13 4.3 8 2.7 6 2 38 3.1 Lack of other government services 9 3 7 2.3 14 4.7 5 1.6 35 2.9 Lack of privacy, town gossip 8 2.7 8 2.7 6 2 7 2.3 29 2.4 Unfriendly neighbours, exclusive 7 2.3 7 2.3 7 2.3 8 2.6 29 2.4 community Too distant from family and friends 10 3.3 7 2.3 6 2 5 1.6 28 2.3 Crime 8 2.7 9 3 5 1.7 6 2 28 2.3 Wind mills/ wind turbines 6 2 4 1.3 7 2.3 6 2 23 1.9 Lack of activities 4 1.3 8 2.7 4 1.3 3 1 19 1.6 Tourists 13 4.3 0 0 0 0 5 1.6 18 1.5 Communication infrastructure, 2 0.7 6 2 1 0.3 2 0.7 11 0.9 internet access Lack of daycare centres 3 1 0 0 4 1.3 0 0 7 0.6 Lack of quality housing 3 1 0 0 4 1.3 0 0 7 0.6 Overall poor quality of life 1 0.3 2 0.7 0 0 0 0 3 0.2 Agriculture activities 0 0 1 0.3 1 0.3 1 0.3 3 0.2 Total 301 301 301 304 1207

The community characteristics that were reported as the most negative among Grey County respondents was the lack of job opportunities in the area, with 32.9% of the respondents. Other disliked qualities included: the lack of shopping or retail in the area (22.3%) and lack of cultural or entertainment activities (14%).

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 118 4.4 Employee Summary Grey County had 149 male respondents (49.5%) and 152 female respondents (50.5%) in the employee telephone survey. The average age of respondents from Grey County was 48.7 years.

Approximately 90% of the 301 respondents had worked in the last year. Just over 75% of employees surveyed worked on a full time basis in their primary employment. More than one fifth of respondents held multiple jobs, this is up from 13.9% of Grey County respondents from the 2005 survey. Almost 5% of Grey County respondents believe they will be retired in one year and 28.8% of respondents reported they believe they will be retired in five years

The proportion of the Grey County respondents who have not completed high school remained consistent between 2005 and 2013 (9%). In 2013, 34.4% reported college or a speciality school as their highest completed education. In Grey, the top three fields of post-secondary study were: business, management and public administration; health, parks, recreation and fitness; and, trades.

The most common occupations held by Grey County respondents included Sales and service; Trades, transport and equipment operators and related occupations; Business, finance and administrative occupations; and, Occupations in education, law and social, community. These remain fairly consistent from the last study.

Employees residing in Grey County perceive the following as their top skills: • Reading • Verbal communication • Teamwork • Written communication • Social or interpersonal • Critical thinking or problem solving

In the previous study, verbal, reading as well as social and interpersonal skills were the top three skills among Bruce and Grey County residents.

Employees from Grey County perceive the following as their weakest skills: • Sector specific skills (engineering, health care, skilled trades, agriculture) • Database • Information technology • Spreadsheets • Word processing • Artistic, creative

In comparison to the previous study, employees from Grey County identified computer, mathematics and artistic skills as their weakest skills.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 119 In Grey County, close to 60% of respondents did not participate in any training or professional development in the last year, this is up from 48% in 2005. Of those who did complete training in the last year, the common training was an industry or occupation specific course, workshop or conference. Another 6% have completed workplace safety or first aid training, and over 5% have completed a college or university course.

The majority of Grey County residents who participated in the survey are very satisfied with their current employment, of which almost 90% are satisfied or very satisfied with their current employment. However, almost 20% of the Grey respondents believe they are underemployed. More than half believe the wages they receive are adequate for the work they do, while 22.3% of respondents believe the wages are somewhat less than adequate.

SECTION 4: GREY EMPLOYEE SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 120 Fact Sheet - Grey County Employer Experiences

This fact sheet focuses on the key findings gathered from the Grey County employers surveyed by telephone and via an online survey. There were 62 employers surveyed for Grey County, 49 of which had their head office located in Grey County.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 121 SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 122 SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 123 5.0 Grey Employer Survey

5.1 Introduction An important component of the skills gap study project is the employer survey. The main focus of the survey was to gather labour market information for each county regarding the current employee skills and the expectations for the future.

5.2 Methodology 5.2.1 Survey Design The design of the survey instrument was based on three criteria. The first was to ensure the survey met the needs of the study including the requirement to collect information on the skills, training and education of the current labour pool. These principal areas were supplemented with the information on the employers’ current workforce, future skill requirements and the ability of the employer to recruit and retain employees.

The second was the need to design the instrument in a manner that would allow for comparison with the employee and the high school survey for the study. This was critical in the element in design as a primary output of the project was to perform a gap analysis among the three surveys.

The third consideration was the need to design the instrument in a manner that would allow for some comparisons with the studies completed in 2005.

A draft version of the survey was prepared based on the 2005 survey and shared with the steering committee for review. Revisions suggested by the steering committee were incorporated into the final survey.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 124 5.2.2 Survey Process The objective for this study was to survey as many as 50 businesses using a mixed method, where at least 10 major employers were to be interviewed by phone with the balance participating in an online electronic version of the survey. The list of candidate businesses was developed in consultation with the steering committee. Businesses were selected that represented a variety of industry sectors including businesses that were major employers in the county.

The 10 phone interview surveys were completed August to September 2013. Calls were typically made between 8:30am and 4:30pm, Monday through Friday. In some cases, interviews were scheduled in the evening to better suit the employer. No interviews were completed on the weekends.

Personalized email invitations were sent to the remaining 40 businesses to complete the online survey. However, fewer than 10 of these businesses accepted the invitation to participate and the steering committee decided to open the survey to the wider business community using pre-existing membership mailing lists (e.g. Grey County Economic Development Office). A total of 50 online surveys were completed during August and September 2013.

Key informant interviews were also conducted with representatives of the Bluewater District School Board and the Bruce Grey Catholic District School Board, Grey Bruce Health Services, and the Grey County Federation of Agriculture to ensure that these important employment sectors were captured in the final analysis.

5.3 Survey Analysis 5.3.1 Respondent Profile Of the employers that responded to the Grey County Employer Survey, 60 had a business located in Grey County.

Table 121: Reported Location of Businesses Surveyed

Location of Business # Employers Grey 60 Huron 2 Perth 2 Bruce 5 Other 3 Total Number of Respondents* 62 *Some respondents listed multiple locations for their business

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 125 49 of these businesses had their head office located in Grey County.

Table 122: Head Office Location of Businesses Surveyed Location of Head Office # Employers Grey 49 Outside the Four County Region, in Ontario 6 Outside Ontario, in Canada 2 Outside of Canada 3 Total Number of Respondents 60

The majority of the employers (58.3%) reported their business as a corporation. Almost a quarter of the businesses are sole proprietor while 6.7% operate as a partnership and 6.7% operate as a non-profit.

Table 123: Operating Arrangement of Businesses Surveyed Operating Arrangement # Employers % Corporation 35 58.3 Sole Proprietor 14 23.3 Partnership 4 6.7 Non-profit Corporation 4 6.7 Other: Limited Liability Company, 3 5.0 Charity, Municipality Total Number of Respondents 60 100

A total of 13 different industry sectors were represented in the employer survey. Close to 26% of the businesses/organizations are in the Manufacturing industry while 17.7% are in the Professional, Scientific and Technical Services industry.

Table 124: Businesses / Organizations by Industry Sector Industry # % Manufacturing 16 25.8 Professional, Scientific and Technical Services 11 17.7 Agriculture 7 11.3 Wholesale and Retail Trade 7 11.3 Construction 4 6.5 Health Care and Social Assistance 4 6.5 Business, Building and Other Support Services 3 4.8 Accommodation and Food Services 2 3.2 Arts, Entertainment, Recreation 2 3.2 Public Administration 2 3.2 Real Estate and Leasing 2 3.2 Religious, Civic and Social Advocacy Organization 1 1.6 Transportation and Warehousing 1 1.6 Total 62 100

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 126 Approximately 48% of the survey respondents were the actual owners of the business.

Table 125: Was the Survey Respondent the Owner of the Business? Are you the owner of # Employers % the business? Yes 29 48.3 No 31 51.7 Total 60 100

The great majority of the businesses (86.7%) were started in Grey County.

Table 126: Did the Business Start in the Four County Region? Was the business started in the # Employers % Four County Region Yes 52 86.7 No 8 13.3 Total 62 100

Many of the businesses have been in the Four County Region for more than 50 years. The median number of years in the area was 30.

Table 127: Number of Years in Business in the Four County Region

Number of years in the Four County Region # Employers % 0-5 years 4 7.0 6- 10 years 11 19.3 11-15 years 5 8.8 16-20 years 4 7.0 21-25 years 4 7.0 26- 30 years 2 3.5 31-35 years 2 3.5 36- 40 years 5 8.8 41- 45 years 1 1.8 46- 50 years 4 7.0 More than 50 years 15 26.3 Total 57 100 Median 30 Mode 40

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 127 Using a 5-point scale, where 1 was not important and 5 was very important, the respondents were asked to score a variety of factors that potentially influenced the decision to locate their business in the Four County Region. The highest ranking factor was the personal preference of the business owner (4.5) to locate in the Four County Region. The next highest ranking factors included the high quality of life (4.4) and the business friendly environment (4.3). Other influential factors included the competitive costs of hydro and other utilities, as well as access to a skilled labour force.

Table 128: Factors Influence to Locate in the Four County Region

How important each feature is with respect to your decision to Average # Employers locate your business in the Four County Region? Score

Personal preference 4.5 60 High quality of life 4.4 60 Business friendly environment / Pro business philosophy 4.3 61 Competitive costs (e.g. hydro and gas utilities) 4 60 Access to skilled labour force 4 60 Access to state of the art telecommunication services 4 61 Lower taxes 3.9 60 Excellent community amenities 3.9 60 Access to raw resources 3.9 60 Infrastructure for business 3.8 60 Available land 3.8 60 Access to extensive transportation network 3.8 59 Access to business assistance programs 3.7 60 Access to support industries / businesses 3.6 59 Access to national and global markets 3.6 60 Available buildings 3.5 60 * 5 point scale: 1 = not important and 5 = very important

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 128 5.3.2 Employees’ Status Of the Grey County businesses surveyed the median number of employees was 9, as the majority of businesses reported having between 1 and 10 employees. Approximately 70% of Grey County businesses surveyed have 30 employees or less, while 6.9% employ more than 200.

Table 129: Number of Employees

Number of Employees # Employers % 1 to 10 31 53.4 11 to 20 5 8.6 21 to 30 4 6.9 31 to 40 0 0.0 41 to 50 3 5.2 51 to 60 0 0.0 61 to 70 2 3.4 71 to 80 1 1.7 81 to 90 1 1.7 91 to 100 0 0.0 101-150 6 10.3 151-200 1 1.7 201 or more 4 6.9 Total 58 100.0 Mode 6 Median 9

Within an aging community it is important to get a sense of the upcoming retirements. Most employers, 78.1%, expect 10 retirements or less in the next five years. One large business expects more than 100 retirements in the next five years.

Table 130: Number of Expected Retirements in the Next 5 Years

Number of Expected Retirements # Employers % 0 12 29.3 1 to 10 20 48.8 11 to 20 7 17.1 21 to 50 1 2.4 51 to 100 0 0.0 More than 100 1 2.4 Total 41 100

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 129 Just over half of the businesses surveyed reported that 100% of their employees live within a 30 minute commute from work.

Table 131: Percent of Employees Living within a 30 Minute Drive to Work

Percentage of employees # Employers % 1 to 10 3 6.8 11 to 20 0 0.0 21 to 30 0 0.0 31 to 40 0 0.0 41 to 50 1 2.3 51 to 60 0 0.0 61 to 70 0 0.0 71 to 80 6 13.6 81 to 90 8 18.2 91 to 100 26 59.1 100% 23 52.3 Total 44 100.0 No response 16

Employers were asked to provide information regarding the average income for each of the three employee categories: management, skilled trades or professional, and general labourer. General labourers were most likely to earn between $20,000 and $39,999, skilled trades or professionals between $40,000 and $59,999. Management employees earn the most, as 66.7% of management employees earn more than $60,000 annually.8

Table 132: Income by Employee Category

Management Skilled Trades/Professional General Labourer # Employers % # Employers % # Employers % Less than $19,999 0 0 0 0.0 0 0.0 $20,000-$39,999 2 13.3 2 16.7 6 85.7 $40,000-$59,999 3 20 7 58.3 1 14.3 $60,000 and over 10 66.7 3 25.0 0 0.0

5.3.3 Employees’ Skills Assessment Employers were asked to provide an assessment of the existing labour force for management, skilled trades or skilled professionals, and general labourers. Inquiries were made as to the quantity, quality, availability and stability of each category of employee. Employers were asked to rank each type of employee on a 5-point scale where 1 was very poor and 5 was excellent. 8 Wages can vary considerably across occupations and within occupations under the same occupation title. For example, the wages for a Human Resource Manager in the Stratford – Bruce Peninsula Region range from a low hourly wage of $20.67 to a median hourly wage of $38.67 to a high hourly wage of $61.19 (Labour Force Survey, Statistics Canada, 2011-2012). A profile of wages by select occupations is presented in Appendix A36.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 130 For the purpose of the survey, the quality of the labour force was described as the employees presently in the position possessing the appropriate skills to perform their functions adequately. Quantity referred to the employer being able to find the desired number of employees possessing the required skills for the position. Availability referred to the type of employee the employer was searching for in relation to their availability in the area while not currently employed or seeking to advance or change positions. Finally, stability meant the duration an employee stayed in the position, in other words the employer was not constantly replacing and training new employees for a specific position.

As shown in the table below, employers are generally satisfied with the labour force in the Four County Region. General labourers scored highest among the three employee groups for quality and availability, but quantity appears to be the most significant issue for this employee group. Management scored highest among the three groups for quantity and stability, but availability appears to be the most significant issue for this employee group. The skilled trades / professionals group scored lowest among the three employee groups for quality and availability with scores that are considerably lower than the other two groups.

Table 133: Quality, Quantity, Availability, Stability of Each Employee Category Skilled Trades/Skilled Management General Labourer Professionals Average Score Average Score Average Score Quality 3.9 3.3 4.2 Quantity 4.1 3.7 3.6 Availability 3.6 3.1 3.8 Stability 4.2 3.7 3.7 * 5 point scale: 1 = very poor and 5 = excellent

The majority of Grey County businesses (60%) require employees with at least a high school education, while 11.1% do not require a high school diploma and 28.9% reported that the requirement of a high school education varies with the position.

Table 134: High School Education Required

High School Education Required # Employers % Yes 27 60.0 No 5 11.1 Varies 13 28.9 Total 45 100.0 No response 15

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 131 Employers from Grey County were asked to indicate which occupational skills their business will be looking for in the next two to five years. Teamwork skills is the most sought after skill followed by verbal communication and social or interpersonal skills. Other valued skills included organizational and critical thinking or problem solving. The industry specific skills such as agriculture, health or education scored lower, but are very valuable to the employers of the specific sector.

Table 135: Occupational Skills Needed in the Next 2-5 Years

Occupational Skills # Employers

Teamwork skills 41 Verbal communication skills 39 Social/Interpersonal skills 37 Organizational skills 36 Critical thinking/problem solving 35 Written communication skills 33 Reading skills 32 Leadership skills 32 Math skills 28 Physical, mechanical, hands on skills 23 Internet 23 Spreadsheets 21 AutoCAD / Engineering skills 19 Database 17 Information technology 17 Word Processing 15 Artistic, creative skills 14 Manufacturing specific skills 14 Construction / skilled trades 9 Agricultural skills 5 Health and social service sector skills 5 Education sector skills 4

In the sector specific interviews it was found that all positions in the health care field require their employees to have teamwork, leadership, organizational skills, as well as strong problem solving skills. As the health care field begins to add even more computerized systems into their hospitals and practices the organizations are expecting employees to have strong computer skills. Agricultural related employers are looking for well-rounded individuals with the sector specific skills as well as leadership, communication skills, social and interpersonal skills, teamwork skills, math skills and organizational skills. Skills or qualities required for teachers beyond their education requirements include: interpersonal, communication, computer, teamwork, leadership, organizational and problem solving or critical thinking skills. Similar skills are sought for school support staff.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 132 5.3.4 Current and Future Workforce The turnover rate experienced by businesses across the region is an important consideration in their individual business plans and a factor in the overall labour market in the region. In the last year, employers reported very few employees leaving the company; 86.7% of businesses have had 10 or fewer. Two employers had between 30 and 50 employees leave their company.

Table 136: Number of employees that leave the company/business each year and their positions have to be filled

Number of employees # Employers %

0 10 33.3 1 to 5 14 46.7 6 to 10 2 6.7 11 to 20 1 3.3 21 to 30 0 0.0 31 to 40 1 3.3 41 to 50 1 3.3 51 to 100 0 0.0 More than 100 1 3.3 Total 30 No response 29

Employers were asked to predict the state of their workforce (growth/shrinkage) in the next two years. Sixteen respondents from Grey County believe the workforce will increase. The increase is predicted to be quite low, 10 of the 16 businesses believe their workforce will increase by no more than 5 positions. The growth of the workforce is expected as employers have seen an increase in demand for their services/ products and more sales. Some employers discussed plans to expand their operations, requiring more staff. At least five employers predict a decrease in their workforce. The decrease is expected to be anywhere between 3 and 30 employees. The drop in workforce numbers has been related to the outsourcing of work to other regions and automation replacing some jobs.

Grey County agricultural representatives believe the workforce will increase. It is believed that any increase may be caused by the increase in farm sizes, or an increase in farm operators and operators needing more staff to run their operations.

The Public School Board representative believes that jobs will decrease across the board due to declining enrollment in all schools. The Catholic Board has had moderate increase in enrollment in the elementary schools over the last few years but often loses students in the move from elementary to high school, as parents wish to keep their kids in their own communities. The Catholic Board is developing initiatives to keep students in the Catholic Board (e.g. putting internet on buses, having later buses for youth in extracurricular activities).

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 133 Health sector representatives do not anticipate any major changes in the health sector workforce in terms of new positions. While there are likely to be retirements, these positions will be filled as necessary. It was noted that there could be a move towards more part-time positions and fewer full-time positions.

Table 137: Predicted Increase or Decrease of the Workforce in the Next 2 Years Increase by how many… 16 Employers 1-5 10 20 2 30 1 40 1 75 2 Decrease by how many… 5 Employers 3 1 5 2 25 1 30 1

Employers were asked to provide information about how they typically recruit employees to their available positions. The majority of employers typically hire from outside the company. Employers use a variety of methods to recruit employees including word of mouth, local media and online job sites. A handful of employers use their connections with educational institutions to hire new graduates. Social networking, including Facebook and LinkedIn, is also common among those looking to hire.

Table 138: Recruitment Sources

Recruitment Sources # Employers From outside the company 42 From within the company 19 Word of mouth 31 Local media (newspaper) 26 Online job sites 25 Company website 20 Head hunter 12 Educational Institutes 5 Social Media (LinkedIn, Facebook) 2 Other 6

A follow up question was asked of employers about the difficulty they have had in recruiting a specific type of employee. In Grey County, employers who responded to the survey find it most difficult to fill skilled professions or skilled trade positions. There is less difficulty filling management positions and general labourer positions.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 134 Farm operators in Grey County have difficulty filling most positions especially equipment operators and mechanics, livestock specialists, horticulture specialists, and general labourers. The fruit farms in Grey have foreign workers because they cannot attract/find reliable local help.

In the education sector, there has been difficulty filling management and administrative positions such as Finance, IT, Principals and Vice Principals. The public school board has found it difficult to encourage teachers to leave the union and move into management positions. The finance positions have been difficult to fill as Bruce Power often takes the most qualified individuals and is able to pay a higher wage. Challenges associated with hiring teaching staff is most commonly the lack of availability of full time positions. It can also be challenging to maintain teachers on the supply list and few teachers are willing to move to the region if they are unsure about the amount of work they will receive. French has been the most difficult qualification to find within the teachers for both Boards, especially for immersion schools.

The decentralization of health services have caused a shift in available positions in the more rural communities. Hospitals and other health care employers in Grey County have difficulty hiring specialized positions such as Psychiatrists and Cardiologists. It was found to be difficult to find Nurse Practitioners and somewhat difficult to fill Registered Nurses positions. It can be especially difficult to find Nurses with specialized qualifications such as Pediatrics or Critical Care. For these positions it can be difficult to convince someone to relocate to the area, as there are few full-time positions available. It has been fairly easy to fill the Registered Practical Nurse positions, though many of these positions are part-time or casual. There are several professional positions that have been difficult to fill including: Dieticians, Physiothera- pists, Respiration Therapists, Speech and Language, Occupational Therapists and Pharmacists. Medical Lab Technicians and Medical Radiation Technicians have been the most difficult to fill. Again, it has been difficult to fill these positions due to the lack of available spousal employment opportunities and a lack of full-time positions open.

With respect to filling management positions in the healthcare sector, it is difficult to find Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs), as well as Managers. There was no difficulty across the region finding administrative assistants. Challenges associated with the management positions relate to wage freezes. Further to this, many in nursing or other professional positions are unwilling to be promoted if it means they must leave their union. The support staff positions in the healthcare sector have been less difficult to fill, with the exception of professional trades in the hospitals. It is challenging to fill these positions as the private sector often pays a higher wage.

Table 139: Difficult to Fill Positions

What positions does your company # Employers have the most difficulty filling? Skilled Professionals 16 Skilled Trades 15 Management 13 General Labour 11

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 135 Employers were asked to rate the following skills on the basis of difficulty of finding an employee using a 5-point scale, where 1 was very difficult and 5 was never difficult. It was found that word processing and reading skills were fairly easy to find, as well as verbal communication and internet skills. Sector specific skills were most difficult to find, including AutoCAD, agricultural skills and construction for a handful of employers. Leadership and critical thinking skills were desired by a large proportion of the employers but were among the most difficult to find.

Table 140: Difficult to Find Skills

Skills Average Score # Employers Word Processing 3.6 30 Reading skills 3.6 42 Verbal communication skills 3.4 42 Internet 3.4 30 Spreadsheets 3.4 28 Social/Interpersonal skills 3.3 42 Teamwork skills 3.3 40 Math skills 3.2 37 Health and social service sector skills 3.2 9 Organizational skills 3.2 42 Written communication skills 3.1 41 Education sector skills 3 6 Database 3 27 Physical, mechanical, hands on skills 2.9 32 Information technology 2.9 28 Artistic, creative skills 2.9 17 Leadership skills 2.8 41 Critical thinking/problem solving 2.8 41 Manufacturing specific skills 2.7 20 AutoCAD / Engineering skills 2.6 17 Agricultural skills 2.6 10 Construction / skilled trades 2.4 12 * 5-point scale: 1 = very difficult and 5 = never difficult.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 136 Apprenticeship programs are a great opportunity for an individual looking to gain experience and skills on the job, under the direction of more experienced workers. For employees, apprenticeship programs can be an important step to learning new skills and building a rewarding career. As such, employers were asked if their business or company was providing apprenticeship opportunities in the Four County Region. Of those surveyed, 44.4% were offering apprenticeship opportunities in Grey County, and another 6 businesses were interested in learning more.

Table 141: Does the Business Provide Apprenticeship Opportunities?

Apprenticeship Opportunities # Employers % Yes 20 44.4 No 18 40.0 Not currently, would be interested in learning more 6 13.3 Don’t know 1 2.2 Total 100.0

Employers were asked to rate the importance of a variety of factors as they relate to the future success of their business on a 5-point scale where 1 was not at all important and 5 was very important. The three most important factors to ensure future success were improving worker productivity, improved business management and workforce development.

Table 142: Factors to Ensure Future Success

Factor Average Score # Employers Improving worker productivity 4.2 42 Improved business management 4.2 41 Workforce development 4.1 40 Availability of telecommunication services 4.0 40 New markets 3.9 40 Expansion of workforce 3.8 39 Energy costs 3.6 39 Research and development 3.6 40 Accessing Capital 3.4 37 Automation 3.4 37 * 5 point scale: 1 = not at all important and 5 = very important

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 137 5.3.5 Training Employers in the Four County Region provide a variety of occupational training to their employers on a regular basis. Health and Safety was the most common training provided, followed by employee retraining. Other training included the apprenticeship programs, as well as classroom or vocational training. Only 6 of the Grey County businesses indicated that they do not provide any training opportunities for their employees.

In the sector specific interviews training was also discussed to get a sense of their specific needs and opportunities. In Grey County, the health related fields offer training to their employees, where and when possible given budget restrictions. Many of the physician, nursing, and professional health care workers also have training available through their associated colleges or associations. Some organizations have partnered with larger health facilities to improve accessibility to training opportunities for their employees. In the education sector, training and professional development is provided by the school boards for teachers, support staff and management or administration. Training is position specific, teachers have a wide range of professional development opportunities, and support staff have been offered training related to mental health and crisis intervention in the Public Board recently. The Catholic Board works in partnership with Niagara University to offer a Masters of Education, offered at the Board office to reduce travel. There has also been training for teachers interested in becoming principals, with Kings College. Overall, both boards are satisfied with the training opportunities for the staff.

While there has been some training opportunities for farm operators and staff, there has not been a lot of up take on these training sessions. Several agri sector employers noted that training opportunities and the benefits of training needs to be better marketed to farmers and farm staff. Agri sector representatives believe that school boards and the school curriculum are doing very little to contribute to the development of a qualified labour force in agriculture.

Table 143: Training Opportunities Provided by Employers

Training # Employers

Health and Safety 33 Employee retraining 24 Apprenticeship (Registered/Pre) 13 Other 11 Classroom training 10 Vocational Training 8 School to Work Programs 6 None 6 Academic – Remedial (Reading, Math) 3 Academic – Advanced (Reading, Math) 1

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 138 The most common type of training that employers would like to see completed by their employees is computer skills including word processing, database management and computer system maintenance. Customer service skills and managerial skills training is also desirable among employers for their employees. Nine employers do not believe their current employees need training.

Table 144: Training Needs

Training Needs # Employers

Computer Skills 18 Customer Service Skills 17 Managerial Skills 15 Equipment Operation Skills 15 Professional Skills 12 Current employees do not need training 9 Specialized Skills (Medical skills, legal 7 knowledge, etc.) General Skills (Basic math, reading, 5 writing, problem solving, etc.)

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 139 5.4 Focus Group Results As part of the employer research, focus groups were held with employers in each of the four counties. These focus groups were used to share the results of the employer survey and to highlight any additional Grey County specific challenges and/or initiatives related to the workforce.

In Grey County, the focus group was well attended by employers and economic development officials from the County and various lower tier municipalities on November 21, 2013.

In Grey County the following workforce challenges were identified through the focus group: • Changing expectations and attitude of employees (including youth) • Poor work ethic (improper use of cell phone, tardiness, improper dress) • Expectation to move up quickly in the company, without training or experience • Entry level high school or university/college graduates are easy to find but not willing to start at an entry position (‘at bottom of the ladder’)

• Retirements/aging workforce • No succession planning • Many retiring but still planning on working as a contract employee • Potential for a huge loss of institutional memory if/when staff retire

• Spousal employment, especially for highly qualified employees • Engagement and retention challenge

• Cost and availability of training • Limited budget for some employers • For those close to retirement, not willing to participate • Scheduling of training, often conflicts with working hours or personal time • Training opportunities are not well marketed

• Rural location • Difficult to attract employees from other areas • Cannot offer same compensation: balance between staying competitive and staying in business • Transportation • Housing costs and availability

• Soft skills and hard skills (many not taught at school any longer) • Leadership • Basic numeracy (short and long division) • Note taking, hand writing • Some individuals (18-28 years old) do not have their driver’s licence

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 140 • Offering benefits to employees: mixed reaction by employers • Not a challenge for large businesses • More of a challenge with an aging workforce • Challenge in the next 10-20 years: challenge shifts to the quantity of available employees more so than the quality of employees • Applicant numbers are already showing signs of decrease • How can businesses do the same, with fewer employees

The focus group participants discussed the challenges and merits associated with co-op education: Transportation challenge, especially for high school students • Manufacturing/construction: safety concerns, limited by the government • Maturity level of students in some situations • Scheduling - program only allows students to work during school hours (not weekends or evenings) • Commitment related to training and space • Some success where the school provides a matching process between student and employer

In regards to the challenges discussed above, the focus group participants offered the following solutions: • Spousal employment program • Employers may need to start being more flexible with employees where possible (i.e. scheduling) • Strong employee engagement supports employee retention • Training: networking with other businesses looking for similar training, chambers or associations • Better marketing and networking with services that already exist (Four County Labour Market Planning Board, CFDC) • Benefits for smaller businesses through the Chambers • Partner with the School Board • Schools need to be aware of existing and projected skills gaps • Need to offer Co-op and other training related programs to all students, not just for students in workplace pathways • Mock interviews with businesses for students • Colleges and Apprenticeships - flexibility of programming to allow employees to work and learn without losing time and money

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 141 5.5 Employer Summary A total of 62 employers were surveyed for Grey County, 49 of which had their head office located in Grey County. Approximately 87% of the businesses surveyed started in Grey County. The median number of years in operation in the Four County Region was 30 years, while 15 businesses had been in operation in the Four County Region for more than 50 years.

From the perspective of the business owners, the top factors to locate their business in Grey County were personal preference, high quality of life, business friendly environment, competitive costs related to utilities and access to a skilled labour force.

Approximately 80% of the businesses surveyed had 100 employees or less, and only four businesses employ more than 200 people working on a regular basis. Approximately 78% of employers expect 10 employee retirements or less in their business in the next five years.

All employers reported that all of their employees earn at least $20,000 annually. Management positions are the highest paid position with 66% of management employees earning more than $60,000 per year.

Employers provided a mixed response regarding the increase or decrease of the future workforce. Grey County agricultural representatives believe the workforce will increase as farms continue to grow in size. Healthcare sector representatives do not anticipate major changes in the health sector workforce due to the way health care is being funded in the Province. The public school board believes that jobs will decrease across the board due to declining enrollment in all schools. The Catholic board has experienced a moderate increase in enrollment in the elementary schools over the last few years but often loses students in the move from elementary to high school, as parents wish to keep their kids in their own communities.

Employers find skilled trades or skilled professionals positions are most difficult to fill. There are also sector specific challenges in hiring. Agriculture for instance has had challenges finding local employees willing to be hired as a general labourers, as such there has been an increase in foreign workers in the area. The education system does not have many challenges filling teaching positions with the exception of French language teachers. There can be issues related to filling the Early Childhood Educator positions with the move to full day kindergarten. Hospitals in the area have challenges finding many positions including physicians, RPNs and RN. These challenges are often related to the lack of full-time positions available and the lack of spousal support for new hires.

Employers in Grey County are looking for the following occupations skills: • Teamwork • Verbal communication • Social/interpersonal skills • Critical thinking and problem solving

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 142 Employers are having the most difficulty finding employees who have the following occupational skills: • Sector specific skills (AutoCAD, agriculture, health) • Critical thinking and problem solving • Leadership skills • Artistic or creative skills

In the sector specific interviews it was found that all positions in the health care field require their employees to have teamwork, leadership, organizational skills, as well as strong problem solving skills. As the health care field begins to add even more computerized systems into their hospitals and practices, the organizations are expecting employees to have strong computer skills. Agricultural related employers are looking for well-rounded individuals with the sector specific skills as well as communication skills, social and interpersonal skills and teamwork. Skills or qualities required for teachers beyond their education requirements include: interpersonal, communication, computer, team work, leadership, organizational and problem solving or critical thinking skills.

Approximately 60% of Grey County businesses require employees to have a high school diploma. • 44.4% offer apprenticeship opportunities in Grey County • Most companies offer a variety of occupational training to their employers on a regular basis including • Health and safety • Employee retraining • Apprenticeship programs • Classroom or vocational training

Generally, business owners and employers hire from outside their company or business. Education may be one of the few exceptions which often hire from within the system as occasional teachers are promoted to full-time permanent teachers, principals are often previous teachers.

SECTION 5: GREY EMPLOYER SURVEY THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 143 6.0 Summary of Findings

The depth and quality of the data from this study allows for a comprehensive understanding to better inform those interested in the labour market in Bruce, Grey, Huron and Perth counties. Thriving and sustainable regional economies are reliant on a solid information base so as to be equipped with knowledge that allows them to be responsive in an ever changing environment. By engaging local employees, employers and high school students in the study regional strengths and labour gaps have been observed with respect to skills, education and training which have in turn created a more complete picture of the local labour market.

Labour Market Profile The purpose of the profile is to provide background information on the general socio-economic status in Grey County. The profile compliments research into present and future skills gaps in the Four County Region. The profile was compiled using data from the 2006 Statistics Canada Population Census and the 2011 Statistics Canada National Household Survey.

Between 2006 and 2011 the population of Grey County had a slight increase of 0.2%. In comparison to the Province of Ontario, the Four County Region has an older population. The median age in Ontario, in 2011, was 40.4 years. Grey County has the oldest population in the region with a median age of 47.3 and the highest proportion of those 85 years and older.

In Grey County the average household income was $70,736, an $8,190 increase from 2006. The average household income for Ontario in 2011 was $85,772. Grey County has the lowest average household income for the Four County Region.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 144 Approximately 22.4% of the Grey County population, 15 years and older, have not completed high school compared to 18.7% for Ontario. In general, a smaller proportion of people in Grey County have completed high school and gone on to complete higher levels of formal education compared to Ontario as a whole. However, a higher proportion of the Grey County population has completed an apprenticeship or trade program compared to the province.

The top three fields of study for women in Grey County include: health professions and related fields; business, management and public administration; and education. For men the top three fields of study include: architecture, engineering, and related technologies; business, management and public administration; and personal, protective and transportation services.

The overall labour force participation rate in Grey County is lower than the participation rate for Ontario. The participation rate for Ontario in 2011 was 65.5% compared to 63% for Grey County. The labour force participation rate was 67.5% for men and 58.6% for women in 2011 for Grey County.

The unemployment rate in 2011 for Grey County is highest among the Four County Region, but consistently lower in comparison to Ontario. Between 2006 and 2011, the Grey County unemployment rate increased from 5.2% to 7.4%. In 2011, the unemployment rate for men in Grey County was 7.7% and 7.0% for women.

The Four County Region has experienced an increase in unemployment since 2006. The 2011 Grey County unemployment rate of 7.4% is the highest in the Four County Region. Even with an increasing unemployment rate, Grey County remains below the Ontario unemployment rate of 8.3%.

Given the ever changing labour market there have been shifts related to specific industries in Grey County. There has been a decrease in Manufacturing sector jobs in Grey, and an increase in both Health Care and Social Assistance and Construction sector jobs.

Health Care and Social Assistance with 6,250 jobs (13%) was the largest employment sector in Grey County followed by Manufacturing with 5,410 jobs (11.3%). Retail Trade with 5,265 jobs (11%), Construction with 4,455 jobs (9.3%), Agriculture; forestry; fishing and hunting with 3,270 jobs, (6.8%) were also in the top five industrial sectors in Grey County.

Grey had a fairly similar distribution of employment by industrial sector compared to Ontario. The top three sectors in Ontario in 2011 in terms of jobs were Retail Trade (10.94%), Manufacturing (10.16%), and Health Care and Social Assistance (10.08%). The Agricultural sector only accounted for 1.48% of the jobs in Ontario.

For men in Grey County, the top three industries were Construction (15.48), Manufacturing (14.73%) and Retail Trade (8.92%), these were the same top three industries for the province as a whole in 2011. For women in Grey County the top three industries were Health Care and Social Assistance (23.43%), Retail Trade (13.19%) and Education (8.46%), these were the same top three industries for the province in 2011.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 145 High School Survey The high school survey of grade 12 students in Grey County consisted of 174 male respondents (47.4%) and 193 female respondents (52.6%). The majority of students were 17 years old.

The self-reported average for all classes in the last school year was quite high, but higher for females than males across all four counties. In Grey, the average for all classes in the last school year was 76.7% for males and 78.8% for females. Students reported English as the highest average, followed by Math and then Science with averages of 77.6%, 76.9% and 75.9% respectively.

Males in Grey tend to favour technology education elective courses, while females are more likely to be engaged in arts courses. There was an increase in average class scores between the two study periods, this may be due in part to surveying only Grade 12 students in 2011 versus students in Grades 10 through 12 in 2005.

The majority of students (63%) participate in extra-curricular activities and on average spend 7.9 hours in these activities per week. The most common extra-curricular activities are related to sports and physical activity. This observation was consistent with the previous studies.

Students are continuing to be engaged in volunteer activity in Grey County. Almost 83% of females and 72% of males have volunteered in the last year. The average number of hours spent volunteering over the last year was 50.2 hours, well over the 40 hours required for their high school career. The most common industries students reported volunteering in were similar to 2005: Information, Culture, and Recreation; Religious, Civic, Environmental or Social Advocacy; Health Care or Social Assistance, and the addition of Agriculture and Education

Fewer Grey County students held a part-time or summer job than in 2005. In 2011, 70.1% of males and 72.3% of females work part-time during the school year and 78% of males and 74.5% of females work in the summer. The most common part-time and summer employment activities occurred in the following sectors: Wholesale and Retail Trade; Accommodation and Food Services; Arts, Entertainment, Recreation; and Construction and/or Specialty Trade Contractor.

Most of the students found both their part-time and summer job through a family member, friend or neighbour, this is especially true for males. Another common method was submitting an application to an employer for a job that was not advertised. Only a small number of students found their job through an employment agency or job counsellor.

Co-op education in Grey County has fairly low participation, only 11.5% of males and 18.7% of females have participated in co-op in the last year. Males participating in co-op were most likely to be involved in other services activities including repair and maintenance and automotive repair, while females participating in co-op were most likely to be involved in Health Care and Social Assistance and Educational Services.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 146 In reviewing the Four County Region as a whole, the students rated their social, interpersonal skills and teamwork skills the highest with a mean score of 3.8. Reading and creative thinking skills followed closely with a mean score of 3.7.

In Grey County, males scored themselves the highest in analytical skills, decision making and problem solving skills and teamwork skills, while females scored themselves the highest in social skills, interpersonal skills, and reading skills with 3.9 each. Gendered differences in self-assessed skill levels could be an indication of the area of concern in extending skill development and training.

In Grey, 92% of students expect to finish high school and continue onto post-secondary school or apprenticeship program. Females are more likely to be planning on attending post-secondary education than males. College is the most common post-secondary education choice for students, followed by university. Males are much more likely to enroll in a trade, vocational or apprenticeship with 23% of the male respondents planning to attend a trade program compared to 2.7% of females.

The top industry categories that male students are hoping to be employed are: Professional, Scientific and Technical Services; Construction and/or Specialty Trade Contractor; and Health Care and Social Assistance. The top industry categories for females include: Health Care and Social Assistance; Arts, Enter- tainment, Recreation; and, Professional, Scientific and Technical Services.

Youth out-migration has been an issue in rural communities. Approximately 58% of males and 66% of females expect to leave the Four County Region to find a job. This was a considerable increase since the last study period.

The unemployment rate for Grey County youth aged 15 to 24 was 21% in 2011 which was considerably higher than the provincial youth unemployment rate of 16%.

Employee Survey The employee survey of Grey County residents consisted of 149 male respondents (49.5%) and 152 female respondents (50.5%). The average age of respondents was 48.7 years.

Approximately 90% of the 301 respondents had worked in the last year from the time of the survey. Just over 75% of the respondents were employed on a full time basis. More than one fifth of the respondents held multiple jobs, this is up from 13.9% from the 2005 survey. Almost 5% believe they will be retired in one year and 28.8% of respondents reported they believe they will be retired in five years

The proportion of the respondents who have not completed high school remained consistent between 2005 and 2013 (9%). A large portion (35.7%) of Grey County respondents’ highest level of education was high school, another 34.4% reported college or a speciality school as their highest completed education. In Grey, the top three fields of post-secondary study were: business, management and public administration; health, parks, recreation and fitness; and trades.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 147 The most common occupations held by Grey County respondents included sales and service; trades, transport and equipment operators and related occupations; business, finance and administrative occupations; and, occupations in education, law and social, community. These remain fairly consistent from the last study.

In 2005, verbal, reading as well as social and interpersonal skills were the top three skills among Bruce and Grey County residents.

In comparison to the 2005 study, those from Bruce Grey identified computers, mathematics and artistic skills as their weakest skills.

In Grey County, close to 60% of respondents did not participate in any training or professional development in the last year, this is up from 48% in 2005. Of those who did complete training, the most common in the last year was an industry or occupation specific course, workshop or conference. Another 6% have completed a workplace safety or first aid and over 5% have completed a college or university course.

The majority of Grey County residents who participated in the survey are very satisfied with their current employment, of which almost 90% are satisfied or very satisfied with their current employment. Almost 20% believe they are underemployed. More than half believe the wages they receive are adequate for the work they do, while 22.3% of respondents believe the wages are somewhat less than adequate.

Employer Survey There were 62 employers surveyed for Grey County, 49 of which had their head office located in Grey County. Approximately 87% of the businesses surveyed started in Grey County. The median number of years in operation in the Four County Region was 30 years, while 15 businesses had been in operation in the Four County Region for more than 50 years.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 148 From the perspective of the business owners, the top factors to locate their business in Grey County were personal preference, high quality of life, business friendly environment, competitive costs related to utilities and access to a skilled labour force.

Approximately 80% of the businesses surveyed had 100 employees or less, and only 4 businesses in Grey employ more than 200 people working on a regular basis. Approximately 78% of employers expect 10 employee retirements or less in their business in the next five years.

Employers find skilled trades or skilled professionals positions are most difficult to fill. There are also sector specific challenges in hiring. Agriculture, for instance, has had challenges finding local employees willing to be hired as a general labourers, as such there has been an increase in foreign workers in the area. The education system does not have many challenges filling teaching positions with the exception of French language teachers. There can be issues related to filling the Early Childhood Educator positions with the move to full day kindergarten. Hospitals in the area have challenges finding many positions including physicians, RPNs and RN. These challenges are often related to the lack of full-time positions available and the lack of spousal support for new hires.

Employers in Grey County are looking for the following occupations skills: • Teamwork • Verbal communication • Social/interpersonal skills • Critical thinking and problem solving

Employers are having the most difficulty finding employees who have the following occupational skills: • Sector specific skills (AutoCAD, agriculture, health) • Critical thinking and problem solving • Leadership skills • Artistic or creative skills

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 149 expecting employees to have strong computer skills. Agricultural related employers are looking for well-rounded individuals with sector specific skills as well as communication skills, social and interpersonal skills and teamwork. Skills or qualities required for teachers beyond their education requirements include: interpersonal, communication, computer, team work, leadership, organizational and problem solving or critical thinking skills.

An Integrated Perspective on the Labour Force Quantity, Quality and Availability of Employees Employers were asked to rate the quantity, quality and availability of employees in Grey County.9 Employers indicated that the management pool is lacking in terms of availability. This pool of talent is crucial for employers as the employer survey revealed that improved business management is a key factor in ensuring the future success of their business. The 2011 census indicates that business, management and public administration is the second most common post-secondary field of study for males (6.2%) in Grey County, but it lags substantially behind the most common field of study for males, architecture, engineering and related technologies (21.2%). Business, management and public administration is also the second most common post-secondary field of study for females (10.6%) just slightly behind the most common field of study for females, health professions and related fields (14.8%).

Results from the high school survey suggest that the future labour pool is not preparing itself for opportunities in the management profession. Students in Grey County had fewer business study credits than any other elective and co-op participation in Grey County is largely concentrated in industries where students likely receive minimal exposure to management positions. The most common co-op programs for males include other services (e.g. repair and maintenance) and transportation, while the most common co-op programs for females include health care and social assistance and educational services. Additionally, only a small percentage of Grey County high school students indicated an interest in pursuing a Commerce (10%) or Business (8%) program in university or college.

9 For the purpose of the survey, the quality of the labour force was described as the employees presently in the position possessing the appropriate skills to perform their functions adequately. Quantity referred to the employer being able to find the desired number of employees possessing the required skills for the position. Availability referred to the type of employee the employer was searching for in relation to their availability in the area while not currently employed or seeking to advance or change positions.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 150 Employers indicated that the skilled trades / professionals pool is lacking in terms of quality and availability. Although the high school survey revealed that 12% of students (23% males; 3% females) intended to enter an apprenticeship program after high school, the provincial average for apprenticeship entry after high school is closer to 6%. There may be an opportunity here for providing additional supports to assist high school students who want to pursue an apprenticeship program.

Employers indicated that the general labourer pool is lacking in terms of quantity. The employee survey indicates that the general population has a reasonably high skill rating in physical, mechanical and hands on skills which suggests the issue for employers is attracting experienced employees away from other, less physically demanding occupations. However, the employee population does have a low skill rating in manufacturing related skills and this is consistent with the challenge employers experience in finding persons with these skills. The high school survey revealed that students have moderate physical, mechanical or hands on skills which could be expected as this group is still in the process of gaining on the job experience to develop these skills.

Skills Gap Leadership skills and critical thinking or problem solving skills are among the most challenging skills that the majority of employers have difficulty finding. Employers identified teamwork skills as the most sought after occupational skill they are looking for in the next 2-5 years. Other important skills identified by the majority of employers include verbal communication skills, social or interpersonal skills, organizational skills, and critical thinking or problem solving skills.

The skills self-assessment by high school students reveals several potential areas for enhancing skill development and training. Overall, Grey County high school students rated themselves highest in teamwork, reading, social or interpersonal skills, problem solving, and adaptability skills. The high student rating for adaptability is an encouraging development given the importance that local employers attach to workforce development and improved worker productivity as key factors in ensuring the success of their business.

Leadership skills, organizational skills, and verbal communication skills were not rated among the top five skills by high school students but they are in strong demand by employers which indicates potential areas for enhancing skill development and training.

Gendered differences in self assessed skills are a further indication of potential areas for enhancing skill development and training. Male students rated themselves lower than females in social or interpersonal skills and creative skills, while female students rated themselves lower in mathematical skills, technological skills, and physical and mechanical skills.

The employee survey indicates that the general population has many of the skills that rank highly among employers. Overall, Grey County employees rated themselves highest in reading skills, verbal communication skills, teamwork skills, social or interpersonal skills, and critical thinking skills. Grey employees also rated themselves high in written communication, leadership and organizational skills.

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 151 While the employee population rated their information technology skills as moderate they rated their database skills as low. Grey County high school students rated their computer skills as moderate and computer studies was the least common elective course. The employer survey indicates that some employers are still experiencing challenges in finding employees with information technology and database skills which suggests a potential area for enhancing skill development and training. Indeed, computer skills (word processing, data base management, computer system maintenance) was identified as the most common type of training that employers are interested in for their current employees. Other important training needs identified by employers include customer service skills, managerial skills, and equipment operation skills.

Quality of Life as an Incentive for Living and Working in Grey County A high quality of life and a friendly business environment are key factors that influence employers to establish and maintain their business operations in Grey County. Competitive costs (hydro and gas utilities) and access to a skilled labour force are also touted by employers as key reasons for locating in Grey County.

Approximately 33% of Grey County employees reported that nothing would motivate them to move out of the Four County Region. The most popular attributes of Grey County as identified by employees include the rural / small town communities, overall good quality of life, close proximity to family and friends, and availability of parks and recreation facilities. The willingness of employees to stay in the region can also be linked to the high job satisfaction rate (89%) and general satisfaction with wages (67%).

Students are disinterested in the Grey County area as a place of future residence and work, as 63% intend to leave the area for school or a career. The two key reasons linked to this intention were consistent for both time periods: a strong desire to experience life elsewhere and the limited variety of local job opportunities.

Students were asked to identify influential factors for staying in the Four County Region as they pursue a career. Being in close proximity to family and friends was the most common reason for staying in the region (72.3%) followed by their belief that their community is a great place to live (56.2%). However, only 23.1% cited the opportunity for a job in which they are interested as a reason to stay in the area.

Statistics Canada reports that rural young adults often go elsewhere for education and many never return. Some may return to raise families in their hometowns or towns similar to them, but in general, rural areas face the threat of depopulation. Of all individuals who move out of their rural community, at most 25% return to this community ten years later.10 The implication of this trend means that rural communities have to rely on a combination of return migration and in migration from other areas to maintain the population size of a given cohort.

10 Statistics Canada. Rural Youth: Stayers, Leavers and Return Migrants, 2000 http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?catno=11F0019m2000152&lang=eng

SECTION 6: SUMMARY OF FINDINGS THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 152 List of Tables Table 1: Population of Grey County 13 Table 2: Age Distribution of Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011 14 Table 3: Population by Ethnic Origin for Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011 16 Table 4: Average Household Income for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011 17 Table 5: Population by Family Income Categories in Bruce, Grey, Huron and Perth County, and Ontario, NHS 2011 18 Table 6: Average Personal Income by Place of Residence, by Gender, NHS 2011 19 Table 7: Highest Education Level for Bruce, Grey, Huron and Perth County, NHS 2011 20 Table 8: Post-Secondary Field of Study for Females for Bruce, Grey, Huron and Perth County, NHS 2011 21 Table 9: Post-Secondary Field of Study for Males for Bruce, Grey, Huron and Perth County, NHS 2011 22 Table 10: Personal Income by Place of Work for Grey County, by Education for Males, NHS 20113 23 Table 11: Personal Income by Place of Work for Grey County, by Education for Females, NHS 2011 24 Table 12: Employment Participation Rate for all ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011 25 Table 13: Employment Participation Rate for Males ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011 25 Table 14: Employment Participation Rate for Females ages 15 and over for Bruce, Grey, Huron and Perth County, and Ontario, Census 2006 and NHS 2011 25 Table 15: Employment Rate for age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011 26 Table 16: Employment Rate for Males age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011 26 Table 17: Employment Rate for Females age 15 and over, for Bruce, Grey, Huron and Perth County, Census 2006 and NHS 2011 26 Table 18: Unemployment Rate for age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 27 Table 19: Unemployment Rate for Males age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 27 Table 20: Unemployment Rate for Females age 15 and over for Bruce, Grey, Huron and Perth, Census 2006 and NHS 2011 27 Table 21: Population by Industrial Sector for all age 15 and over, NHS 2011 28 Table 22: Population by Industrial Sector for Males age 15 and over, NHS 2011 29 Table 23: Population by Industrial Sector for Females age 15 and over, NHS 2011 30 Table 24: Population by Place of Work by Industrial Sector for all age 15 and over, NHS 2011 31 Table 25: Location Quotient for Bruce, Grey, Huron and Perth Counties, NHS 2011 33 Table 26: Labour Force in Bruce, Grey, Huron and Perth County, and Ontario by Occupation, NHS 2011 34 Table 27: Male Labour Force in Bruce, Grey, Huron and Perth County, and Ontario by Occupation, NHS 2011 35 Table 28: Female Labour Force in Bruce, Grey, Huron and Perth County and Ontario by Occupation, NHS 2011 36 Table 29: Personal Income by Place of Work, by Industry, NHS 2011 37 Table 30: Surveyed Secondary Schools 44 Table 31: Response Rate by Secondary School 45 Table 32: Sample Population by Gender 46

THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 153 Table 33: Sample Population by Age 46 Table 34: Average Course Marks by Gender 47 Table 35: Average Number of Credits for Elective Courses by Gender 48 Table 36: Highest Level of English Course Completed, by Gender 49 Table 37: Highest Level of Math Course Completed, by Gender 49 Table 38: Highest Level of Science Course Completed, by Gender 50 Table 39: Extra-Curricular Participation by Gender 51 Table 40: Average Number of Hours per Week Spent on Extra-Curricular Activities, by Gender 52 Table 41: Extra-Curricular Participation in Sports or Physical Activity at School or with Other Organizations 52 Table 42: Extra-Curricular Participation in an Art, Drama or Music Group at School or With Other Organizations 53 Table 43: Extra-Curricular Participation in Student Council 53 Table 44: Extra-Curricular Participation in Another Type of Group or Club 53 Table 45: Volunteer Participation by Gender 54 Table 46: Average Number of Hours Spent Volunteering in the Past Year by Gender 55 Table 47: Reason for Starting a Volunteer Activity by Gender 55 Table 48: Volunteer Participation by Industry and Gender 56 Table 49: Volunteer Participation by Activity where Most Time was Spent, by Gender 58 Table 50: Part-time Work Participation by Gender 59 Table 51: Summer Work Participation by Gender 60 Table 52: Average Number of Hours per Week Working in Part-time Job by Gender 60 Table 53: Average Number of Weeks Working in Part-time Job by Gender 61 Table 54: Average Number of Hours per Week Working in Summer time Job by Gender 61 Table 55: Average Number of Weeks Working in Summer time Job by Gender 62 Table 56: Part-time Work Activity by Industry and Gender 63 Table 57: Summer Work Activity by Industry and Gender 64 Table 58: Method Used to Find Part-time Job by Gender 65 Table 59: Method Used to Find Summer Work by Gender 65 Table 60: Reason for Getting a Part-time Job by Gender 66 Table 61: Reason for Getting a Summer Time Job by Gender 66 Table 62: School Co-op Participation by Gender 67 Table 63: Co-op Program Activity by Industry and Gender 68 Table 64: Reason for Participating in Co-op Program by Gender 69 Table 65: Work at Home Participation by Gender 70 Table 66: Average Number of Hours per Week Working at Home in Past School Year by Gender 70 Table 67: Main Work Activity When Working at Home by Gender 71 Table 68: Average Skill Rating for Grey County Students by Gender 72 Table 69: Average Skill Rating for Four County Students by Gender 72 Table 70: Plans for the Near Future by Gender 73 Table 71: Future Plans for Post-secondary School / Training by Gender 74 Table 72: Factors that Influenced Student Plans for Post-secondary Education 75 Table 73: Level of Confidence in Being Accepted to and Completing Post-secondary Education by Gender 75 Table 74: Educational Institutions Students are Most Likely to Attend by Gender 76 Table 75: University Degree Programs Students are Most Likely to Pursue by Gender 77

THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 154 Table 76: College Programs that Students are Most Likely to Pursue by Gender 78 Table 77: Apprenticeship Programs that Students are most Likely to Pursue by Gender 79 Table 78: Industry that Students are most Likely to be Employed In by Gender 80 Table 79: Occupations that Students are most Likely to Have by Gender 81 Table 80: Factors that Directed Students toward Pursuing this Career by Gender 82 Table 81: Resources Students Spoke to about their Career Interests by Gender 82 Table 82: Students Expectations to Find a Job and Live in Bruce, Grey, Huron, Perth County by Gender 83 Table 83: Reasons for Planning to Leave Grey County to Live and Work by Gender 84 Table 84: Student Reasons for Planning to Stay in Grey County by Gender 84 Table 85: Gender of Respondents Bruce, Grey, Huron and Perth County 92 Table 86: Age of Respondents for Bruce, Grey, Huron and Perth County 92 Table 87: Respondents Household Income Categories in Bruce, Grey, Huron and Perth County 93 Table 88: Marital Status of Respondents for Bruce, Grey, Huron and Perth County 94 Table 89: Employment Status of Bruce, Grey, Huron and Perth County Respondents 95 Table 90: Respondents’ Work Status for Bruce, Grey, Huron and Perth County 95 Table 91: Income Sources for Unemployed Respondents for Bruce, Grey, Huron and Perth County 96 Table 92: Multiple Jobs for Respondents from Bruce, Grey, Huron and Perth County 97 Table 93: Employment Basis for Bruce, Grey, Huron and Perth County Respondents 97 Table 94: Employment Status for Bruce, Grey, Huron and Perth County Respondents 98 Table 95: Hours per Work at Primary Employment for Bruce, Grey, Huron and Perth County Respondents 98 Table 96: Number of Years with Primary Employer for Bruce, Grey, Huron and Perth County Respondents 99 Table 97: Secondary Employment Basis for Bruce, Grey, Huron and Perth County 100 Table 98: Employment Status for Secondary Employment for Bruce, Grey, Huron and Perth County 100 Table 99: Employment Basis for Tertiary Employment in Bruce, Grey, Huron and Perth County 101 Table 100: Employment Status of Tertiary Employment in Bruce, Grey, Huron and Perth County 101 Table 101: Occupation Classification by Respondents for Bruce, Grey, Huron and Perth County 102 Table 102: Grey County Respondents Occupation Classification Compared to NHS 2011 103 Table 103: Respondents by Industrial Sector for Bruce, Grey, Huron and Perth County 104 Table 104: Grey County Respondents Reported Industry Compared to NHS 2011 105 Table 105: Highest Education Level for Bruce, Grey, Huron and Perth County Respondents 106 Table 106: Major Field of Study of Bruce, Grey, Huron and Perth County Respondents 107 Table 107: Ability to Speak a Second Language by Bruce, Grey, Huron and Perth County Respondents 108 Table 108: Languages Spoken by Bruce, Grey, Huron and Perth County Respondents 108 Table 109: Self-Assessment of Skills by Bruce, Grey, Huron and Perth County Respondents 110 Table 110: Training and Education Upgrading of Bruce, Grey, Huron and Perth County Respondents 111 Table 111: Desired Training or Education by Bruce, Grey, Huron and Perth County Respondents 112 Table 112: Job Satisfaction of Bruce, Grey, Huron and Perth County Respondents 112 Table 113: Perceived Underemployment of Bruce, Grey, Huron and Perth County Respondents 113 Table 114: Satisfaction with Wages for Bruce, Grey, Huron and Perth County Respondents 113 Table 115: Where the Bruce, Grey, Huron and Perth County Respondents see themselves in the next year 114 Table 116: Where the Bruce, Grey, Huron and Perth County Respondents see themselves in the next five years 114 Table 117: Factors that would influence Bruce, Grey, Huron and Perth County Respondents to move out of the Region 115

THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 155 Table 118: Distance Willing to Relocate for a New Job for Bruce, Grey, Huron and Perth County Respondents 116 Table 119: Positive Community Characteristics by Bruce, Grey, Huron and Perth County Respondents 117 Table 120: Negative Community Characteristics Reported by Bruce, Grey, Huron and Perth County Respondents 118 Table 121: Reported Location of Businesses Surveyed 125 Table 122: Head Office Location of Businesses Surveyed 126 Table 123: Operating Arrangement of Businesses Surveyed 126 Table 124: Businesses / Organizations by Industry Sector 126 Table 125: Was the Survey Respondent the Owner of the Business? 127 Table 126: Did the Business Start in the Four County Region? 127 Table 127: Number of Years in Business in the Four County Region 127 Table 128: Factors Influence to Locate in the Four County Region 128 Table 129: Number of Employees 129 Table 130: Number of Expected Retirements in the Next 5 Years 129 Table 131: Percent of Employees Living within a 30 Minute Drive to Work 130 Table 132: Income by Employee Category 130 Table 133: Quality, Quantity, Availability, Stability of Each Employee Category 131 Table 134: High School Education Required 131 Table 135: Occupational Skills Needed in the Next 2-5 Years 132 Table 136: Number of employees that leave the company/business each year and their positions have to be filled 133 Table 137: Predicted Increase or Decrease of the Workforce in the Next 2 Years 134 Table 138: Recruitment Sources 134 Table 139: Difficult to Fill Positions 135 Table 140: Difficult to Find Skills 136 Table 141: Does the Business Provide Apprenticeship Opportunities? 137 Table 142: Factors to Ensure Future Success 137 Table 143: Training Opportunities Provided by Employers 138 Table 144: Training Needs 139

THE FIRST STEP – UNDERSTANDING THE SKILLS GAP IN GREY COUNTY | 156 111 Jackson St. S., Suite 1, Box 1078, Walkerton, ON N0G 2V0 Toll-free: 888-774-1468 Phone: 519-881-2725 Fax: 519-881-3661 Email: [email protected] www.planningboard.ca