[ { "slide_number": 1, "markdown_text": "\n\n## Northeast 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Northeast Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Northeast Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I: Regional Context\n\n- i. Unemployment Rate\n- ii. Labor Force - Educational Requirements for Employment\n\n## Part II. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment, Gender, and Race/Ethnicity\n- iii. Occupations\n\n## Part III: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part IV: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part V: New Data Tools\n\n## Appendix\n\n- A: Critical Industry Profiles\n- B: Worker Characteristics\n\nGlossary", "report name": "2019 Northeast Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Context", "report name": "2019 Northeast Data Package" }, { "slide_number": 5, "markdown_text": "## Unemployment Rate\n\nThe Northeast region's unemployment rate historically tracks with the state average.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 1.0% | 0.0% | 1.5% | 2.0% | 2.5% | 3.0% | 3.5% | 4.0% | 4.5% | 5.0% | 6.0% | 7.0% | | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 6, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThere are fewer unemployed workers in the Northeast as of May 2019 than the prior year. The overall labor force has also increased by about 5,000, as some people who previously were no longer looking for work have returned to the labor market and are having success finding employment.\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 7, "markdown_text": "## Median Annual Wage\n\nThe Northeast's median annual wage has increased since 2015 and is the second highest of any region in the State after Greater Boston.\n\n| Berkshire | Cape and Islands | Central | Greater Boston | Northeast | Pioneer Valley | Southeast | Massachusetts | |\n|-------------|--------------------|-----------|------------------|-------------|------------------|-------------|-----------------|----|\n| $36,317 | $38,179 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $30,000 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 8, "markdown_text": "## Educational Requirements for Employment\n\nThe Northeast is projected to have the same shares of jobs that require BA+; AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 9, "markdown_text": "## Part II: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Northeast Data Package" }, { "slide_number": 10, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Northeast Data Package" }, { "slide_number": 11, "markdown_text": "## II.A: Regional Industry Overview", "report name": "2019 Northeast Data Package" }, { "slide_number": 12, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry in the Northeast. Manufacturing is the second largest industry and has seen some small employment growth since 2016\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 0 | |\n| Manufacturing | 0 | |\n| Retail Trade | 0 | |\n| Education | 0 | |\n| Professional | 0 | |\n| Construction | 0 | |\n| Administrative | 0 | |\n| Other Services | 0 | |\n| Public | 0 | |\n| Wholesale | 0 | |\n| Finance and | 0 | |\n| Transportation | 0 | |\n| Arts | 0 | |\n| Information | 0 | |\n| Management | 0 | |\n| Agriculture | 0 | |\n| Mining | 0 | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 13, "markdown_text": "## Sector Makeup by Total Wages\n\nManufacturing paid the highest total wages in in the Northeast in 2018 and grew by 3% since 2016. Health Care and Social Assistance and Professional and Technical Services follow with the next highest total wages paid in 2018 in the region.\n\n| Category | Value | |\n|-----------------|---------|----|\n| Manufacturing | $1 | |\n| Health Care | $1 | |\n| Professional | $1 | |\n| Educational | $1 | |\n| Construction | $1 | |\n| Retail Trade | $1 | |\n| Wholesale Trade | $1 | |\n| Public | $1 | |\n| Information | $1 | |\n| Administration | $1 | |\n| Education | $1 | |\n| Agriculture | $1 | |\n| Utilities | $1 | |\n| Agriculture | $1 | |\n| Mining | $1 | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 14, "markdown_text": "## II.B: Priority Industry Profiles", "report name": "2019 Northeast Data Package" }, { "slide_number": 15, "markdown_text": "## Manufacturing", "report name": "2019 Northeast Data Package" }, { "slide_number": 16, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of Manufacturing establishments in the Northeast has remained fairly stable since 2016. In the last year, Raytheon was the employer with the highest number of job postings in the Northeast (1,133), followed by ZOLL Medical Corporation (502), General Electric (452) and Pfizer (413).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 17, "markdown_text": "## Manufacturing by Education\n\n34% of workers in Manufacturing in the Northeast have a high school diploma or less. 27% of workers in Manufacturing have some college or an Associate Degree and 34% have a Bachelor's degree or higher. This educational attainment mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | % of Employees | |\n|--------|------------------|----|\n| 2015 | 35% | |\n| 2018 | 5% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 18, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in the Northeast are predominantly male. Females make up about 30% of workers in Manufacturing in the region.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n| Male | -4% | |\n| Female | -2000 | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 19, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nApproximately 80% of all Manufacturing workers in the Northeast are white, although the percentage of non-white workers has increased since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 20, "markdown_text": "## Healthcare and Social", "report name": "2019 Northeast Data Package" }, { "slide_number": 21, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 2,000 Health Care and Social Assistance establishments were added in the Northeast between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, Lahey Health posted the most jobs in the Northeast, with 1,409, followed by Beverly Hospital, a subsidiary of Lahey Health, with 1,251.\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 22, "markdown_text": "## Healthcare and Social Assistance by Education\n\nNearly 60% of workers in Healthcare and Social Assistance have some college or higher level of education in the Northeast.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 |\n|------|--------------------------------------------------------------------|\n| 100% | 82,626 |\n| 90% | 10%, 8,025 |\n| 80% | -0.2% |\n| 70% | 32%, 26,258 |\n| 60% | -3.4% |\n| 50% | 30%, 24,457 |\n| 40% | 30% |\n| 20% | 19%, 15,794 |\n| 10% | 10%, 8,092 |\n| 0% | 2015 |\n| | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 23, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----|\n| 18,833 | 67,755 | |\n| 10% | 40% | |\n| 20% | 30% | |\n| 20% | 20% | |\n| 20% | 10% | |\n| 20% | 0% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 24, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile nearly 80% of workers in the Healthcare and Social Assistance sector are white in the Northeast, since 2015, growth in employment has been increasing for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Northeast Data Package" }, { "slide_number": 25, "markdown_text": "## Professional and Technical Services", "report name": "2019 Northeast Data Package" }, { "slide_number": 26, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nThe Northeast is home to more than 3,500 establishments in the Professional and Technical Services sector, which includes computer systems design, legal, management and technical consulting, and accounting and bookkeeping services. In the last year, H&R Block had the most job postings in the Northeast with 246, followed by AECOM Technology Corp. (145) and Lanthus Medical Imaging (141).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 27, "markdown_text": "## Professional and Technical Services by Education\n\nNearly 50% of workers in the Professional and Technical Services sector in the Northeast have a Bachelor's degree or higher, while nearly 25% have some college or an Associate degree.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|----|\n| 2015 | 5% | 15%, 4,175 | 24%, 6,772 | 24%, 7,322 | 24% | |\n| 2018 | 5% | 15%, 4,175 | 24%, 6% | 24%, 7,322 | 24% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 28, "markdown_text": "## Professional and Technical Services by Gender\n\nMore than half of workers in the Professional and Technical Services sector in the Northeast are male.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +100% | |\n| Male | +100% | |\n| Female | +100% | |\n| Change in # of Employees | +60% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 29, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 85% percent of workers in the Professional and Technical Services Sector in the Northeast are white, although the number of workers of other races is increasing. With 3,036 employees, Asian workers now make up 10% of industry employment.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 30, "markdown_text": "## Occupations", "report name": "2019 Northeast Data Package" }, { "slide_number": 31, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Northeast Data Package" }, { "slide_number": 32, "markdown_text": "## Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|------------------|---------------------------------------------------|--------------------------------|--------------------------------|----------------------------|\n| Occupation Title | Occupation Title | Occupation Title | Occupation Title | Occupation Title |\n| 29-2021 | Dental Hygienists | Associate's degree | 5,360 | 4 |\n| 29-2032 | Diagnostic Medical Sonographers | Associate's degree | 2,030 | 4 |\n| 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 | 4 |\n| 15-1134 | Web Developers | Associate's degree | 90 | 4 |\n| 49-3023 | Automotive Service Technicians and Mechanics | Postsecondary non-degree award | 60 | 42,521 |\n| 31-9091 | Dental Assistants | Postsecondary non-degree award | 7,580 | 4 |\n| 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 | 4 |\n| 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 | 456,635 |\n| 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 | 43,303 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 | 46,986 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 820 | 59,966 |\n| 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| 15-1134 | Web Developers | Associate's degree | 150 | 4 |\n| 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 1,560 | 49,107 |\n| 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 50 | 4 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 2,870 | 46,986 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 1,220 | 59,966 |\n| 23-2011 | Paralegals and Legal Assistants | Associate's degree | 5,490 | 4 |\n| 15-1134 | Web Developers | Associate's degree | 1,550 | 4 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 6,350 | 46,986 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 6,990 | 4 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Northeast Data Package" }, { "slide_number": 33, "markdown_text": "## Part III: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Northeast Data Package" }, { "slide_number": 34, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Northeast Data Package" }, { "slide_number": 35, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Northeast Data Package" }, { "slide_number": 36, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 4+ Stars\n\nAt the sub-BA level, a number of 4- and 5-star occupations do not have enough regional supply to meet employer demand.\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 37, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3 Stars\n\nAt the sub-BA level, a number of 3-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n3-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Northeast Data Package" }, { "slide_number": 38, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Northeast Data Package" }, { "slide_number": 39, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Northeast Data Package" }, { "slide_number": 40, "markdown_text": "## Part IV: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Northeast Data Package" }, { "slide_number": 41, "markdown_text": "## IV. A: Apprenticeships", "report name": "2019 Northeast Data Package" }, { "slide_number": 42, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Northeast Data Package" }, { "slide_number": 43, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 44, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 45, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn the Northeast, the most popular occupations for apprentices (Electricians, Plumbers, Pipefitters, and Steamfitters, and Sheet Metal Workers) are ranked 4+ stars, indicating high wages and strong projected employer demand.\n\nSource: Division of Apprentice Standards, 2019\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|----------------|---------------|----------|\n| Electricians | 4 | 585 | 532 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 372 | 543 |\n| Carpenters | 4 | 342 | 699 |\n| Sheet Metal Workers | 4 | 186 | 250 |\n| Construction Laborers | 4 | 158 | 801 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 5 | 143 | 274 |\n| Telecommunications Equipment Installers and Repairers | 3 | 54 | 68 |\n| Brickmasons and Blockmasons | 2 | 32 | 42 |\n| Police and Sheriff's Patrol Officers | 4 | 31 | 305 |\n| Operating Engineers and Other Construction Equipment Operators | 4 | 31 | 282 |\n| Electrical Power-Line Installers and Repairers | 2 | 15 | 19 |\n| | | | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 46, "markdown_text": "## IV. B: Professional Licensing", "report name": "2019 Northeast Data Package" }, { "slide_number": 47, "markdown_text": "## Top 20 Occupations by DPL Professional Licensing\n\nIn the Northeast, a majority of the top occupations by number of Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nNortheast\n\nState\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Northeast Data Package" }, { "slide_number": 48, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment | Closer Look: DPL Licenses Matched to Multiple SOC Occupations |\n|----------------------------------------------|---------|------------|-------------------|-----------------------------------------------------------------------------------------------------------------------------------------|\n| Allied Health Occupational Therapy Assistant | 3 | 203 | 125 | DPL Board / License Type / Occupation Title STARS Licenses 2018 Employment |\n| Mental Health Counselor | 4 | 756 | 767 | Engineers and Land Surveyors |\n| Physical Therapist Assistant | 4 | 222 | 330 | ENGINEER |\n| Applied Behavior Analyst | 3 | 298 | 504 | 4 |\n| Occupational Therapist | 4 | 408 | 718 | Industrial Engineers |\n| Physical Therapist | 5 | 594 | 1,227 | Mechanical Engineers |\n| Educational Psychologist | 4 | 188 | 735 | Electrical Engineers |\n| Rehabilitation Counselor | 3 | 7 | 626 | Civil Engineers |\n| Electricians | 4 | 2,288 | 2,830 | Computer Hardware Engineers |\n| Electrician | 4 | 2,288 | 2,830 | Electronics Engineers, Except Computer |\n| Engineers And Land Surveyors | 4 | 1,178 | 7,480 | Environmental Engineers |\n| Gas Fitters | 4 | 2,249 | 2,382 | Chemical Engineers |\n| Gas Fitter | 4 | 2,249 | 2,382 | Social Workers |\n| Public Accountancy | 5 | 1,204 | 3,228 | SOCIAL WORKER, LICENSED |\n| Certified Public Accountant | 3 | 5,023 | 245 | Healthcare Social Workers |\n| Real Estate | 3 | 5,023 | 245 | Child, Family, and School Social Workers |\n| Social Workers | 4 | 1,909 | 3,938 | Mental Health and Substance Abuse Social Workers |\n| Social Worker, Licensed* | 4 | 1,909 | 3,938 | Source: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections |\n| | | | | |\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Northeast Data Package" }, { "slide_number": 49, "markdown_text": "## Part V: New Data Tools", "report name": "2019 Northeast Data Package" }, { "slide_number": 50, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Northeast Data Package" }, { "slide_number": 51, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Northeast Data Package" }, { "slide_number": 52, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Northeast Data Package" }, { "slide_number": 53, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Northeast Data Package" }, { "slide_number": 54, "markdown_text": "## Construction", "report name": "2019 Northeast Data Package" }, { "slide_number": 55, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments in the Northeast grew by more than 100 since 2016, with growth across several types of contractors. In the last year, CDM Smith was responsible for the most online job postings in the Northeast (29), followed by Roto Rooter (25) and North Shore Mechanical (22).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 56, "markdown_text": "## Construction by Education\n\nConstruction workers have a variety of educational attainment backgrounds with 27% of workers with a high school diploma or equivalent, 28% some college or Associate degree, and 23% Bachelor's degree or higher.", "report name": "2019 Northeast Data Package" }, { "slide_number": 57, "markdown_text": "## Construction by Gender\n\nMore than 80% of all Construction workers are male in the Northeast, though the number of females working in the sector grew by more than 500 since 2015.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +15% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +18% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 58, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 93% of Construction workers are white in the Northeast. There has been some small growth since 2015 in the number of Hispanic or Latino, Black or African American, and Asian workers.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Northeast Data Package" }, { "slide_number": 59, "markdown_text": "## Educational Services", "report name": "2019 Northeast Data Package" }, { "slide_number": 60, "markdown_text": "## Educational Services Groups and Employers\n\nThe number of Educational Services establishments grew slightly since 2016 in the Northeast, driven primarily by growth in the educational support services and business, computer and management training groups. North Shore Community College posted the most jobs in the Northeast over the last 12 months (244), followed by Salem State University (233) and Sylvan Learning (199).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 61, "markdown_text": "## Educational Services by Education\n\n43% of workers in Educational Services have a Bachelor's degree or higher level of education in the Northeast.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | |\n|------|--------------------------------------------------------------------|-------------|\n| 100% | 39,722 | 39,795 |\n| 90% | 8%, 3,162 | +8.88% |\n| 80% | 45%, 17,792 | -4.8% |\n| 70% | 60% | 43%, 16,944 |\n| 50% | 40% | +0.8% |\n| 30% | 25%, 9,741 | +25%, 9,815 |\n| 20% | 17%, 6,749 | +3.3% |\n| 10% | 6%, 2,278 | +15.3% |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 62, "markdown_text": "## Educational Services by Gender\n\nMore than 60% of workers in the Educational Services sector in the Northeast are female.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Northeast Data Package" }, { "slide_number": 63, "markdown_text": "## Educational Services by Race/Ethnicity\n\nNearly 92% of workers in the Educational Services sector in the Northeast are white. There has been some growth since 2015 in the numbers of people of color working in the sector in the region.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.", "report name": "2019 Northeast Data Package" }, { "slide_number": 64, "markdown_text": "## Finance and Insurance", "report name": "2019 Northeast Data Package" }, { "slide_number": 65, "markdown_text": "## Finance and Insurance Groups and Employers\n\nThe number of Finance and Insurance establishments in the Northeast has remained stable since 2016. In the last year, Anthem Blue Cross was responsible for the largest number of job postings in the Northeast (666), followed by Santander (309), TD Bank (134) and Bank of America (133).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 66, "markdown_text": "## Finance and Insurance by Education\n\nFinance and Insurance employment has declined slightly since 2015. Nearly 45% of workers in the sector in the Northeast hold a Bachelor's degree or higher.\n\n| Year | Education | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|-------------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|------|----|\n| 2015 | 40% | 60% | 70% | 80% | 90% | 100% | |\n| 2018 | 5% | 10% | 12% | 13% | 14% | 15% | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 67, "markdown_text": "## Finance and Insurance by Gender\n\nWorkers in the Finance and Insurance sector in the Northeast are primarily female (more than 60%).\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Northeast Data Package" }, { "slide_number": 68, "markdown_text": "## Finance and Insurance by Race/Ethnicity\n\nNearly 90% of all workers in the Finance and Insurance sector in the Northeast are white. The number of people of color working in the sector has had small growth since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 69, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Northeast Data Package" }, { "slide_number": 70, "markdown_text": "## Priority and Critical Industries by Age\n\n| Category | Value | |\n|--------------------------------------------------|-----------------------------------|----|\n| 14-21 | 1,213 | |\n| 22-34 | 35-44 | |\n| 45-54 | 45-54 | |\n| 55-64 | 65-99 | |\n| 65-99 | 3,763 | |\n| 1,821 | 3,763 | |\n| 6,447 | 16,994 | |\n| 7,604 | 18,957 | |\n| 7,604 | 14,797 | |\n| 6,477 | 10,639 | |\n| 6,477 | 11,947 | |\n| 7,835 | 1,272 | |\n| 527 | 3,569 | |\n| Professional, Scientific, and Technical Services | Health Care and Social Assistance | |\n| Manufacturing | Health Care and Social Assistance | |", "report name": "2019 Northeast Data Package" }, { "slide_number": 71, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 72, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 73, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 74, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 75, "markdown_text": "## Glossary", "report name": "2019 Northeast Data Package" }, { "slide_number": 76, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Northeast Data Package" }, { "slide_number": 77, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Northeast Data Package" }, { "slide_number": 78, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Northeast Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Greater Boston 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part II: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part III: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part IV: New Data Tools\n\n## Appendix\n\n- A: Regional Context\n- B: Worker Characteristics\n- C: Priority Industry Profiles\n- D: Critical Industry Profiles\n- E: Professional Licensing\n\n## Glossary", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 5, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 6, "markdown_text": "## I.A: Regional Industry Overview", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 7, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry in Greater Boston. Professional and Technical Services is the next largest industry in the region by employment, followed by Educational Services.\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 0 | |\n| Professional | 25 | |\n| Educational | 25 | |\n| Retail Trade | 25 | |\n| Finance and | 25 | |\n| Administrative | 25 | |\n| Manufacturing | 25 | |\n| Construction | 25 | |\n| Public | 25 | |\n| Information | 25 | |\n| Other Services | 25 | |\n| Wholesale | 25 | |\n| Transportation | 25 | |\n| Management | 25 | |\n| Agriculture | 25 | |\n| Mining | 25 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 8, "markdown_text": "## Sector Makeup by Total Wages\n\nProfessional and Technical Services paid the highest total wages in Greater Boston in 2018 and grew by 16% since 2016, followed by Health Care and Social Assistance with just over half as much in total wages.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 9, "markdown_text": "## I.B: Priority Industry Profiles", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 10, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 11, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 2,000 Healthcare and Social Assistance establishments were added in Greater Boston between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, Partners Healthcare posted the most online jobs in Greater Boston, with 10,898, followed by Massachusetts General Hospital, with 5,260.\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 12, "markdown_text": "## Healthcare and Social Assistance by Education\n\n64% of workers in Healthcare and Social Assistance have some college or higher level of education in Greater Boston.\n\n| | 260,937 | 260,937 | 270,737 | 270,737 |\n|----|-------------|-------------|-------------------------------------------|---------------------------------------|\n| | 8% , 20,722 | 8% , 20,722 | 8% , 21,805 | 8% , 21,805 |\n| | 80% | -2.2% | 36% , 97,651 | 36% , 97,651 |\n| | 70% | 38%, 99,861 | 38%, 99,861 | 38%, 99,861 |\n| | 60% | -3.2% | Educational attainment not available (age | |\n| | 50% | -4.0% | Bachelor's degree or advanced degree | Bachelor's degree or advanced degree |\n| | 40% | 28%, 73,067 | 28%, 73,067 | 28%, 73,067 |\n| | 30% | +10.1% | High school or equivalent, no college | High school or equivalent, no college |\n| | 20% | 17%, 44,751 | 17%, 44,751 | 17%, 44,751 |\n| | 10% | 9%, 22,536 | 9%, 22,536 | 9%, 22,536 |\n| | 0% | +18.0% | 10%, 26,595 | 10%, 26,595 |\n| | 2015 | 2015 | 2018 | 2018 |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 13, "markdown_text": "## Professional and Technical Services", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 14, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nGreater Boston is home to more than 15,500 establishments in the Professional and Technical Services sector, which includes computer systems design, legal, management and technical consulting services, and scientific R&D. In the last year, IBM had the most job postings in Greater Boston, with 2,228. Dana Farber Cancer Institute (2,222) and Cambridge Health Alliance (1,032) followed.\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 15, "markdown_text": "## Professional and Technical Services by Education\n\n50% of workers in the Professional and Technical Services sector in Greater Boston have a Bachelor's degree or higher, while more than 20% have some college or an Associate degree.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|---------|----|\n| 2015 | 5% | 13% | 21% | 40% | 30% | |\n| 2018 | 5% | 11,648 | 23.9% | 119.327 | 119.327 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 16, "markdown_text": "## Occupations", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 17, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 18, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | SOC Code | Occupation Title | Educational Requirement | All Industries, Regional | |\n|--------------------------------------|------------|---------------------------------------------------|--------------------------------|---------------------------|----------------------------|---------|\n| | 25-2011 | Preschool Teachers, Except Special Education | Associate's degree | 13,570 | 4 | $37,618 |\n| | 29-2034 | Radiologic Technologists | Associate's degree | 4,100 | 4 | $78,278 |\n| | 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 | 4 | $68,761 |\n| | 29-1126 | Respiratory Therapists | Associate's degree | 2,250 | 4 | $76,253 |\n| | 29-2032 | Diagnostic Medical Sonographers | Associate's degree | 2,030 | 4 | $83,554 |\n| | 29-2012 | Medical and Clinical Laboratory Technicians | Associate's degree | 1,620 | 4 | $43,469 |\n| | 29-2031 | Cardiovascular Technologists and Technicians | Associate's degree | 1,330 | 4 | $79,464 |\n| | 15-1152 | Computer Network Support Specialists | Associate's degree | 160 | 4 | $78,213 |\n| Health Care and Social Assistance | 15-1134 | Web Developers | Associate's degree | 90 | 5 | $87,255 |\n| | 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 | 4 | $60,315 |\n| | 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 | 4 | $40,704 |\n| | 29-2071 | Medical Records/Health Information Technicians | Postsecondary non-degree award | 4,220 | 4 | $53,043 |\n| | 29-2055 | Surgical Technologists | Postsecondary non-degree award | 2,870 | 4 | $57,975 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 | 4 | $58,800 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 | 4 | $49,065 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 820 | 5 | $62,454 |\n| | 23-2011 | Paralegals and Legal Assistants | Associate's degree | 5,490 | 4 | $59,914 |\n| | 15-1134 | Web Developers | Associate's degree | 1,550 | 5 | $87,255 |\n| | 15-1152 | Computer Network Support Specialists | Associate's degree | 610 | 4 | $78,213 |\n| Professional and Technical Services | 29-2012 | Medical and Clinical Laboratory Technicians | Associate's degree | 190 | 4 | $43,469 |\n| | 29-2071 | Medical Records/Health Information Technicians | Postsecondary non-degree award | 760 | 4 | $53,043 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 6,990 | 5 | $62,454 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 6,350 | 4 | $49,065 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 19, "markdown_text": "## Regional Priority Occupations\n\n| | Occupational Group | SOC Code | Occupation Title | 2018 Employment | Median Annual Wage | STAR | Educational Requirement | 12-Month Job Postings |\n|----|----------------------|----------------------------------------------------|--------------------|-------------------|----------------------|-----------------------------------|---------------------------|-------------------------|\n| | 29-2034 | Radiologic Technologists | 2,153 | $78,278 | 4 | Associate's degree | 782 | |\n| | 29-2012 | Medical and Clinical Laboratory Technicians | 2,076 | $43,469 | 4 | Associate's degree | 1,577 | |\n| | 29-2035 | Magnetic Resonance Imaging Technologists | 450 | $89,490 | 4 | Associate's degree | 411 | |\n| | 31-2021 | Physical Therapist Assistants | 729 | $68,761 | 4 | Associate's degree | 400 | |\n| | 29-2032 | Diagnostic Medical Sonographers | 650 | $83,554 | 4 | Associate's degree | 400 | |\n| | 29-2031 | Cardiovascular Technologists and Technicians | 581 | $79,464 | 4 | Associate's degree | 399 | |\n| | 29-2021 | Dental Hygienists | 2,048 | $83,880 | 3 | Associate's degree | 147 | |\n| | 29-2033 | Nuclear Medicine Technologists | 172 | $80,708 | 3 | Associate's degree | 28 | |\n| | 29-2056 | Veterinary Technologists and Technicians | 485 | $42,565 | 2 | Associate's degree | 48 | |\n| | 31-2011 | Occupational Therapy Assistants | 167 | $61,240 | 2 | Associate's degree | 224 | |\n| | 29-2061 | Licensed Practical and Licensed Vocational Nurses | 5,850 | $60,315 | 4 | Secondary non-degree award | 1,827 | |\n| | 29-2071 | Medical Records and Health Information Technicians | 2,319 | $53,043 | 4 | Postsecondary non-degree award | 2,233 | |\n| | 31-2022 | Physical Therapist Aides | 267 | $32,509 | 2 | High school diploma or equivalent | 61 | |\n| | 15-1132 | Software Developers, Applications | 22,575 | $106,117 | 5 | Bachelor's degree | 28,957 | |\n| | 15-1133 | Software Developers, Systems Software | 20,690 | $114,673 | 5 | Bachelor's degree | 331 | |\n| | 15-1121 | Computer Systems Analysts | 10,160 | $93,021 | 5 | Bachelor's degree | 4,624 | |\n| | 15-1142 | Network and Computer Systems Administrators | 6,359 | $92,232 | 5 | Bachelor's degree | 2,192 | |\n| | 15-1143 | Computer Network Architects | 4,034 | $122,746 | 5 | Bachelor's degree | 1,638 | |\n| | 15-1122 | Information Security Analysts | 2,471 | $106,077 | 5 | Bachelor's degree | 3,085 | |\n| | 15-1141 | Database Administrators | 2,021 | $101,562 | 5 | Bachelor's degree | 3,343 | |\n| | 15-1131 | Computer Programmers | 3,841 | $93,601 | 4 | Bachelor's degree | 1,269 | |\n| | 15-1134 | Web Developers | 3,921 | $87,255 | 5 | Associate's degree | 5,766 | |\n| | 15-1152 | Computer Network Support Specialists | 1,925 | $78,213 | 4 | Associate's degree | 458 | |\n| | 15-1151 | Computer User Support Specialists | 14,400 | $62,454 | 5 | Some college, no degree | 5,689 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 20, "markdown_text": "## Part II: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 21, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 22, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\n- How many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 23, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 4+ Stars\n\nAt the sub-BA level, a number of 4- and 5-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 24, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3 Stars\n\nAt the sub-BA level, a number of 3-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n3-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 100+ only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 25, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 26, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 27, "markdown_text": "## Part III: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 28, "markdown_text": "## III. A: Apprenticeships", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 29, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 30, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\n## Supply\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n...minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 31, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 32, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn Greater Boston, the most popular occupations for apprentices (Electricians, Carpenters, Plumbers, Pipefitters, and Steamfitters, and Construction Laborers) are ranked 4+ stars, indicating high wages and strong projected employer demand.\n\nSource: Division of Apprentice Standards, 2019\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|----------------|---------------|----------|\n| Electricians | 4 | 620 | 1,189 |\n| Carpenters | 4 | 585 | 1,342 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 310 | 823 |\n| Construction Laborers | 4 | 293 | 1,557 |\n| Structural Iron and Steel Workers | 1 | 185 | 23 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 101 | 508 |\n| Sheet Metal Workers | 2 | 100 | 69 |\n| Elevator Installers and Repairers | 4 | 99 | 54 |\n| Police and Sheriff's Patrol Officers | 4 | 60 | 821 |\n| Brickmasons and Blockmasons | 3 | 50 | 56 |\n| Glaziers | 2 | 49 | 46 |\n| | | | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 33, "markdown_text": "## III. B: Professional Licensing", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 34, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nA majority of the top occupations in Greater Boston by number of Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 35, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses greatly exceeds total employment for some occupations, such as Cosmetologists, for others, such as Mental Health Counselors, the number of jobs (2,117) outstrips the supply of licenses (1,746).\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|---------|------------|-------------------|\n| Allied Health | 4 | 1,717 | 2,032 |\n| Educational Psychologist | 3 | 1,746 | 2,117 |\n| Mental Health Counselor | 4 | 828 | 1,404 |\n| Applied Behavior Analyst | 4 | 5 | 1,972 |\n| Occupational Therapist | 5 | 1,114 | 3,850 |\n| Physical Therapist | 5 | 1,985 | |\n| Cosmetology | 4 | 6,408 | 8,705 |\n| Cosmetologist (Hairdresser) | 4 | | |\n| Electricians | 4 | 3,033 | 7,823 |\n| Electrician | 4 | | |\n| Engineers And Land Surveyors | 4 | | |\n| Engineer | 4 | 3,868 | 27,230 |\n| Gas Filters | 4 | | |\n| Gas Fitter | 4 | 2,867 | 5,378 |\n| Public Accountancy | 5 | | |\n| Certified Public Accountant | 5 | 5,773 | 25,080 |\n| Real Estate | 4 | 14,629 | 2,426 |\n| Real Estate Salesperson | 4 | | |\n| Social Workers | 4 | 5,979 | 15,971 |\n| Social Worker, Licensed | 4 | | |\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nSelected occupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 36, "markdown_text": "## Part IV: New Data Tools", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 37, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 38, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 39, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 40, "markdown_text": "## Appendix: Regional Context", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 41, "markdown_text": "## Unemployment Rate\n\nGreater Boston's unemployment rate historically tracks with the state average, though about half a percentage point lower.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 1.0% | 0.0% | 0.5% | 1.5% | 2.0% | 2.5% | 3.0% | 3.5% | 4.0% | 4.5% | 5.0% | 6.0% | | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 42, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThere are fewer unemployed workers in Greater Boston as of May 2019 than the prior year. The overall labor force has also increased by more than 19,000, as some people who previously were no longer looking for work have returned to the labor market and are having success finding employment.\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 43, "markdown_text": "## Median Annual Wage\n\nGreater Boston's median annual wage has increased since 2015 and is the highest of any region in the State; exceeding the overall state average by about $8K.\n\n| Year | Median Annual Wage | 2018 Median Annual Wage | |\n|---------|----------------------|---------------------------|----|\n| $36,317 | $56,732 | $40,646 | |\n| $38,179 | $53,153 | $42,225 | |\n| $38,433 | $45,698 | $41,303 | |\n| $38,601 | $40,163 | $38,797 | |\n| $38,600 | $46,690 | $46,690 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 44, "markdown_text": "## Educational Requirements for Employment\n\nGreater Boston is projected to have similar shares of jobs that require BA+; AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 45, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 46, "markdown_text": "## Priority and Critical Industries by Age\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 47, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 48, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 49, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 50, "markdown_text": "## Regional Priority Industries by Ethnicity\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 51, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 52, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 53, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +1% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +1% | |\n| Male | +5,000 | |\n| Female | +5,000 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 54, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile nearly 70% of workers in the Healthcare and Social Assistance sector are white in Greater Boston, since 2015, growth in employment has been increasing for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 55, "markdown_text": "## Professional and Technical Services", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 56, "markdown_text": "## Professional and Technical Services by Gender\n\nMore than half of workers in the Professional and Technical Services sector are male in Greater Boston.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 57, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nNearly 80 percent of workers in the Professional and Technical Services Sector in Greater Boston are white. The numbers of Asian workers are growing, followed by much smaller numbers of Black or African American and Hispanic or Latino workers.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 58, "markdown_text": "## Occupations", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 59, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4-Stars\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|------------------|----------------------------------------------------------|---------------------------------|--------------------------------|----------------------------|\n| Socio Code | | | 2018 Industry | STAR |\n| Occupation Title | | | Educational Requirement | Median Annual Wage |\n| 29-1021 | Dentists, General | Doctoral or professional degree | 3,140 | 4 |\n| 29-1063 | Internists, General | Doctoral or professional degree | 2,570 | 4 |\n| 19-3031 | Clinical, Counseling, and School Psychologists | Doctoral or professional degree | 1,930 | 4 |\n| 29-1065 | Pediatricians, General | Doctoral or professional degree | 1,550 | 4 |\n| 29-1066 | Psychiatrists | Doctoral or professional degree | 830 | 4 |\n| 21-1022 | Healthcare Social Workers | Master's degree | 5,340 | 4 |\n| 29-1127 | Speech-Language Pathologists | Master's degree | 2,120 | 85 |\n| 21-1012 | Educational, Guidance, School, and Vocational Counselors | Master's degree | 940 | 4 |\n| 29-1151 | Nurse Anesthetists | Master's degree | 810 | 4 |\n| 25-9031 | Instructional Coordinators | Master's degree | 430 | 4 |\n| 25-4021 | Librarians | Master's degree | 50 | 4 |\n| 21-1021 | Child, Family, and School Social Workers | Bachelor's degree | 4,860 | 4 |\n| 11-9151 | Social and Community Service Managers | Bachelor's degree | 4,810 | 4 |\n| 21-1011 | Substance Abuse and Behavioral Disorder Counselors | Bachelor's degree | 2,720 | 59,428 |\n| 29-2011 | Medical and Clinical Laboratory Technologists | Bachelor's degree | 2,380 | 74 |\n| 13-1151 | Training and Development Specialists | Bachelor's degree | 1,680 | 4 |\n| 19-4021 | Biological Technicians | Bachelor's degree | 1,630 | 4 |\n| 29-1031 | Dietitians and Nutritionists | Bachelor's degree | 1,620 | 66,157 |\n| 27-3091 | Interpreters and Translators | Bachelor's degree | 1,360 | 57 |\n| 13-1131 | Fundraisers | Bachelor's degree | 790 | 4 |\n| 27-3031 | Public Relations Specialists | Bachelor's degree | 610 | 4 |\n| 13-1141 | Compensation, Benefits, and Job Analysis Specialists | Bachelor's degree | 180 | 4 |\n| 11-3131 | Training and Development Managers | Bachelor's degree | 160 | 573,656 |\n| 15-1131 | Computer Programmers | Bachelor's degree | 150 | 93,601 |\n| 13-1023 | Purchasing Agents, Except Wholesale, Retail, and Farm | Bachelor's degree | 120 | 479,358 |\n| 13-1121 | Meeting, Convention, and Event Planners | Bachelor's degree | 110 | 55,006 |\n| 29-9011 | Occupational Health and Safety Specialists | Bachelor's degree | 100 | 489,187 |\n| 25-2052 | Special Education Teachers, Kindergarten and Elementary | Bachelor's degree | 80 | 70,881 |\n| 11-3111 | Compensation and Benefits Managers | Bachelor's degree | 80 | 123,206 |\n| 11-3061 | Purchasing Managers | Bachelor's degree | 60 | 4 |\n\nAll occupations listed are 4-star occupations requiring a Bachelor's degree or higher. Top 30 occupations by industry employment only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 60, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4-Stars\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|----------|------------------------------------------------------------|---------------------------------|--------------------------------|----------------------------|\n| SOC Code | | | Educational Requirement | 2018 Industry |\n| 15-1111 | Computer and Information Research Scientists | Doctoral or professional degree | 230 | $110,872 |\n| 21-1022 | Healthcare Social Workers | Master's degree | 340 | $62,797 |\n| 25-9031 | Instructional Coordinators | Master's degree | 160 | $78,388 |\n| 25-4021 | Librarians | Master's degree | 70 | $74,322 |\n| 19-4021 | Biological Technicians | Bachelor's degree | 2,340 | $52,472 |\n| 27-1024 | Graphic Designers | Bachelor's degree | 2,130 | $63,724 |\n| 27-3031 | Public Relations Specialists | Bachelor's degree | 2,090 | $65,254 |\n| 15-1131 | Computer Programmers | Bachelor's degree | 1,810 | $93,601 |\n| 17-2081 | Environmental Engineers | Bachelor's degree | 1,450 | $88,252 |\n| 19-2031 | Chemists | Bachelor's degree | 1,400 | $95,794 |\n| 19-2041 | Environmental Scientists and Specialists, Including Health | Bachelor's degree | 1,270 | $80,824 |\n| 13-1151 | Training and Development Specialists | Bachelor's degree | 1,150 | $71,702 |\n| 17-2031 | Biomedical Engineers | Bachelor's degree | 1,020 | $94,317 |\n| 27-3042 | Technical Writers | Bachelor's degree | 980 | $84,340 |\n| 17-2061 | Computer Hardware Engineers | Bachelor's degree | 740 | $123,890 |\n| 27-3043 | Writers and Authors | Bachelor's degree | 630 | $65,899 |\n| 27-1011 | Art Directors | Bachelor's degree | 630 | $92,729 |\n| 27-2012 | Producers and Directors | Bachelor's degree | 560 | $65,453 |\n| 27-3091 | Interpreters and Translators | Bachelor's degree | 550 | $57,901 |\n| 11-3061 | Purchasing Managers | Bachelor's degree | 440 | $130,009 |\n| 11-2011 | Advertising and Promotions Managers | Bachelor's degree | 420 | $126,960 |\n| 13-1121 | Meeting, Convention, and Event Planners | Bachelor's degree | 410 | $55,006 |\n| 11-3131 | Training and Development Managers | Bachelor's degree | 380 | $124,418 |\n| 13-1081 | Logisticians | Bachelor's degree | 380 | $82,558 |\n| 13-1023 | Purchasing Agents, Except Wholesale, Retail, and Farm | Bachelor's degree | 370 | $79,358 |\n| 13-1141 | Compensation, Benefits, and Job Analysis Specialists | Bachelor's degree | 290 | $73,656 |\n| 27-3041 | Editors | Bachelor's degree | 260 | $74,100 |\n| 13-1131 | Fundraisers | Bachelor's degree | 260 | $61,796 |\n| 13-1051 | Cost Estimators | Bachelor's degree | 250 | $74,803 |\n| 29-9011 | Occupational Health and Safety Specialists | Bachelor's degree | 220 | $89,187 |\n\nAll occupations listed are 4-star occupations requiring a Bachelor's degree or higher. Top 30 occupations by industry employment only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 61, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 5-Stars\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|-----------------------------|-----------------------------------------------------------|---------------------------------|---------------------------------|----------------------------|\n| SOC Code | | | 2018 Industry | STAR |\n| Occupation Title | | | Educational Requirement | Median Annual Wage |\n| 29-1123 Physical Therapists | | | Doctoral or professional degree | 5 |\n| 19-1042 | Medical Scientists, Except Epidemiologists | Doctoral or professional degree | 5,220 | $91,762 |\n| 29-1062 | Family and General Practitioners | Doctoral or professional degree | 2,470 | $197,623 |\n| 29-1051 | Pharmacists | Doctoral or professional degree | 2,410 | $118,211 |\n| 23-1011 | Lawyers | Doctoral or professional degree | 140 | $157,200 |\n| 29-1171 | Nurse Practitioners | Master's degree | 5,830 | $122,804 |\n| 29-1071 | Physician Assistants | Master's degree | 3,620 | $109,061 |\n| 29-1122 | Occupational Therapists | Master's degree | 3,530 | $89,168 |\n| 15-2041 | Statisticians | Master's degree | 320 | $105,495 |\n| 11-9032 | Education Administrators, Elementary and Secondary School | Master's degree | 60 | $111,894 |\n| 29-1141 | Registered Nurses | Bachelor's degree | 70,340 | $95,128 |\n| 11-9111 | Medical and Health Services Managers | Bachelor's degree | 11,020 | $130,572 |\n| 11-1021 | General and Operations Managers | Bachelor's degree | 3,470 | $127,825 |\n| 13-1071 | Human Resources Specialists | Bachelor's degree | 1,710 | $72,414 |\n| 11-3011 | Administrative Services Managers | Bachelor's degree | 1,610 | $106,702 |\n| 13-2011 | Accountants and Auditors | Bachelor's degree | 1,540 | $76,151 |\n| 11-3031 | Financial Managers | Bachelor's degree | 1,360 | $142,826 |\n| 15-1121 | Computer Systems Analysts | Bachelor's degree | 860 | $93,021 |\n| 15-1132 | Software Developers, Applications | Bachelor's degree | 750 | $106,117 |\n| 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 710 | $69,510 |\n| 15-1142 | Network and Computer Systems Administrators | Bachelor's degree | 620 | $92,232 |\n| 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 590 | $151,263 |\n| 13-1041 | Compliance Officers | Bachelor's degree | 570 | $81,241 |\n| 11-2031 | Public Relations and Fundraising Managers | Bachelor's degree | 520 | $124,807 |\n| 11-3121 | Human Resources Managers | Bachelor's degree | 490 | $135,674 |\n| 13-1111 | Management Analysts | Bachelor's degree | 430 | $98,400 |\n| 11-2021 | Marketing Managers | Bachelor's degree | 430 | $136,007 |\n| 13-2051 | Financial Analysts | Bachelor's degree | 410 | $89,077 |\n| 15-1141 | Database Administrators | Bachelor's degree | 220 | $101,562 |\n| 11-9121 | Natural Sciences Managers | Bachelor's degree | 160 | $172,136 |\n\nAll occupations listed are 5-star occupations requiring a Bachelor's degree or higher. Top 30 occupations by industry employment only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 62, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 5-Stars\n\n| | Industry | SOC Code | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|----------|------------|----------------------------------------------------------|---------------------------------|--------------------------------|----------------------------|\n| | | | Educational Requirement | 2018 Industry | STAR |\n| Industry | 23-1011 | Lawyers | Doctoral or professional degree | 12,980 | $157,200 |\n| | 19-1042 | Medical Scientists, Except Epidemiologists | Doctoral or professional degree | 6,900 | 5 |\n| | 19-1021 | Biochemists and Biophysicists | Doctoral or professional degree | 3,890 | 5 |\n| | 15-2041 | Statisticians | Master's degree | 1,910 | $106,073 |\n| | 15-1132 | Software Developers, Applications | Bachelor's degree | 12,890 | $106,117 |\n| | 11-1021 | General and Operations Managers | Bachelor's degree | 12,540 | $127,825 |\n| | 13-2011 | Accountants and Auditors | Bachelor's degree | 12,100 | $76,151 |\n| | 13-1111 | Management Analysts | Bachelor's degree | 11,670 | $98,400 |\n| | 15-1133 | Software Developers, Systems Software | Bachelor's degree | 11,460 | $114,673 |\n| | 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 6,480 | $151,263 |\n| | 11-3031 | Financial Managers | Bachelor's degree | 6,130 | $142,826 |\n| | 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 5,940 | $69,510 |\n| | 41-4011 | Sales Representatives, Technical and Scientific Products | Bachelor's degree | 5,080 | $83,382 |\n| | 15-1121 | Computer Systems Analysts | Bachelor's degree | 4,880 | $93,021 |\n| | 17-2051 | Civil Engineers | Bachelor's degree | 4,500 | $92,715 |\n| | 11-2021 | Marketing Managers | Bachelor's degree | 4,100 | $136,007 |\n| | 17-2141 | Mechanical Engineers | Bachelor's degree | 3,660 | $96,406 |\n| | 11-2022 | Sales Managers | Bachelor's degree | 3,590 | $141,391 |\n| | 13-1071 | Human Resources Specialists | Bachelor's degree | 3,550 | $72,414 |\n| | 11-9041 | Architectural and Engineering Managers | Bachelor's degree | 3,310 | $151,824 |\n| | 15-1143 | Computer Network Architects | Bachelor's degree | 3,210 | $122,746 |\n| | 17-1011 | Architects, Except Landscape and Naval | Bachelor's degree | 3,040 | $97,623 |\n| | 11-9121 | Natural Sciences Managers | Bachelor's degree | 2,960 | $172,136 |\n| | 17-2071 | Electrical Engineers | Bachelor's degree | 2,810 | $117,216 |\n| | 13-2051 | Financial Analysts | Bachelor's degree | 2,800 | $89,077 |\n| | 11-9111 | Medical and Health Services Managers | Bachelor's degree | 2,250 | $130,572 |\n| | 11-3011 | Administrative Services Managers | Bachelor's degree | 2,130 | $106,702 |\n| | 15-1142 | Network and Computer Systems Administrators | Bachelor's degree | 2,090 | $92,232 |\n| | 17-2112 | Industrial Engineers | Bachelor's degree | 1,680 | $99,814 |\n| | 41-9031 | Sales Engineers | Bachelor's degree | 1,630 | $89,289 |\n\nAll occupations listed are 5-star occupations requiring a Bachelor's degree or higher. Top 30 occupations by industry employment only.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 63, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 64, "markdown_text": "## Hospitality", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 65, "markdown_text": "## Hospitality Groups and Employers\n\nThe number of Hospitality-related establishments in Greater Boston remained stable from 2016 to 2018. Over the last 12 months, Marriott International, Inc. was responsible for the most online job postings in Greater Boston (1,952).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 66, "markdown_text": "## Hospitality by Education\n\nHospitality affords opportunities to people with a variety of educational backgrounds, nearly equal shares across attainment levels. 21% of workers have a high school diploma in Hospitality in Greater Boston, another 22% have some college or an Associate degree, and 18% have a Bachelor's degree or higher.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 67, "markdown_text": "## Hospitality by Gender\n\nEmployment in Hospitality in Greater Boston is evenly split between males and females.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +6% | |\n| Male | +6% | |\n| Female | +9% | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 68, "markdown_text": "## Hospitality by Race/Ethnicity\n\nAbout 70% of workers in Hospitality in Greater Boston are white. Numbers of Black or African American, Asian and Hispanic or Latino workers have grown in the sector since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 69, "markdown_text": "## Construction", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 70, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments in Greater Boston grew by more than 200 between 2016 and 2018, with growth across several types of contractors. In the last year, American Tower Corporation was responsible for the most online job postings in Greater Boston (245), followed by CDM Smith (207) and Suffolk Construction (152).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 71, "markdown_text": "## Construction by Education\n\nConstruction workers have a variety of educational attainment backgrounds with nearly equal shares of workers with high school diploma or equivalent (26%), some college or Associate degree (28%), and Bachelor's degree or higher (26%).\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | |\n|------|--------------------------------------------------------------------|--------------|\n| 100% | 55,391 | 66,027 |\n| 90% | 8%, 4,420 | +25.3% |\n| 80% | 27%, 15,062 | +14.1% |\n| 70% | 60% | +18.8% |\n| 50% | 28%, 15,342 | +18.8% |\n| 0% | 30% | +18.4% |\n| 20% | 26%, 14,463 | +26%, 17,120 |\n| 10% | 11%, 6,104 | +30.4% |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 72, "markdown_text": "## Construction by Gender\n\nMore than three quarters of all Construction workers are male in Greater Boston, though the number of females working in the sector grew by nearly 2,000 since 2015.\n\n| Category | Value | |\n|-----------------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +17% | |\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +1,000 | |\n| Male | +7,000 | |\n| Female | +6,000 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 73, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 90% of Construction workers are white in Greater Boston. There has been some growth since 2015 in the number of Hispanic or Latino, Black or African American, and groups of workers.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 74, "markdown_text": "## Finance and Insurance", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 75, "markdown_text": "## Finance and Insurance Groups and Employers\n\nThe number of Finance and Insurance establishments in Greater Boston has grown slightly since 2016. In the last year, Liberty Mutual was responsible for the most job postings in Greater Boston (1,758), followed by Bank of America (1,310) and Santander (1,189).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 76, "markdown_text": "## Finance and Insurance by Education\n\nFinance and Insurance employment has grown since 2015. More than 50% of workers in the sector in Greater Boston hold a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | 102,618 | -2.0% | 105,758 | | | | | |\n|-----|-------------|---------|-------------------------------------------|-----|-----|-------|--------------------------------------|----|\n| 90% | 6%, 6,043 | -1.2% | 6%, 5,921 | | | | | |\n| 80% | 54%, 55,859 | -1.2% | 52%, 55,183 | | | | | |\n| 70% | 60% | -2.0% | Educational attainment not available (age | 60% | 50% | -2.0% | Bachelor's degree or advanced degree | |\n| 40% | 30% | -5.5% | High school or equivalent, no college | | | | | |\n| 20% | 22%, 22,211 | +5.5% | Less than high school | | | | | |\n| 10% | 13%, 13,304 | +12.1% | 14%, 14,908 | | | | | |\n| 0% | 5%, 5,201 | +21.3% | 6%, 6,307 | | | | | |\n| | | | | | | | | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 77, "markdown_text": "## Finance and Insurance by Gender\n\nNumbers of workers in the Finance and Insurance sector in Greater Boston are almost evenly split between male and female.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------|----|\n| Male | +2% | |\n| Female | +1500 | |\n| Male | +2% | |\n| Female | +2% | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 78, "markdown_text": "## Finance and Insurance by Race/Ethnicity\n\nMore than 80% of all workers in the Finance and Insurance sector in Greater Boston are white. The number of Asian workers has grown the most since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 79, "markdown_text": "## Manufacturing", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 80, "markdown_text": "## Manufacturing Groups and Employers\n\nThere are slightly fewer Manufacturing establishments in Greater Boston than in 2016. Dell was the employer with the highest number of job postings in the last year (1,950), followed by Takeda Pharmaceuticals North America, Inc. (1,794) and Biogen (1,553).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 81, "markdown_text": "## Manufacturing by Education\n\n32% of workers in Manufacturing in Greater Boston have a high school diploma or less. 26% of workers in Manufacturing have some college or an Associate Degree and 37% have a Bachelor's degree or higher. This educational attainment mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|--------|----|\n| 2015 | 38%, 31,021 | -4.7% | 26%, 21,142 | 28%, 20,151 | 28% | |\n| 2018 | 37%, 28,773 | -7.2% | -4.7% | -2.8% | 16,040 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 82, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in Greater Boston are predominantly male. Female workers make up more than 30% of workers in Manufacturing in the region.\n\n| Category | Value | |\n|-----------------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | -5% | |\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | -5% | |\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for gender.", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 83, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce in Greater Boston has seen very small growth in the numbers of people of color since 2015. Nearly 80% of workers are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n| Chart Type | Description | |\n|------------------|-------------------------------------------------------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data on the x-axis and numerical data on the y-axis | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 84, "markdown_text": "## Arts, Entertainment, and Recreation", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 85, "markdown_text": "## Arts, Entertainment, and Recreation Groups and Employers\n\nThe number of Arts, Entertainment and Recreation establishments in Greater Boston grew slightly between 2016 and 2018. Over the last 12 months, Penn National Gaming, Inc. was the employer responsible for the most job postings in Greater Boston (289).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 86, "markdown_text": "## Arts, Entertainment, and Recreation by Education\n\nArts, Entertainment and Recreation, like Hospitality, affords opportunities to people with a variety of educational backgrounds. 18% of workers have a high school diploma in Hospitality in Greater Boston, 23% have some college or an Associate degree, and nearly 30% have a Bachelor's degree or higher.\n\n| Year | Education Attainment | Q2 2015 - Q2 2018 | |\n|--------|------------------------|---------------------|----|\n| 2015 | 23%, 6,293 | +20.5% | |\n| 2018 | 23%, 7,583 | +22.4% | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 87, "markdown_text": "## Arts, Entertainment, and Recreation by Gender\n\nThere are slightly more female workers than male workers in the Arts, Entertainment and Recreation industry in Greater Boston.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +19% | |\n| Male | +2000 | |\n| Female | +22% | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 88, "markdown_text": "## Arts, Entertainment, and Recreation by Race/Ethnicity\n\nMore than 85% of workers in the Arts, Entertainment and Recreation industry are white in Greater Boston. Numbers of people of color working in the sector have grown in small numbers since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 89, "markdown_text": "## Retail Trade", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 90, "markdown_text": "## Retail Trade Groups and Employers\n\nThe number of Retail establishments in Greater Boston has declined by more than 200 since 2016. Grocery stores, clothing stores and gas stations all declined over the period. In the last year, Wayfair posted the most jobs in Greater Boston (2,796), followed by Whole Foods Market, Inc. (2,372) and Amazon (2,192).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 91, "markdown_text": "## Retail Trade by Education\n\nRetail, like Hospitality and Arts, Entertainment and Recreation, affords opportunities to people with a variety of educational backgrounds. Nearly equal shares of workers in Retail hold a high school diploma (21%), some college or an Associate degree (23%), or Bachelor's degree or higher (21%).\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Education | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|-------------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-------------|----|\n| 2015 | -0.2% | -0.2% | -0.2% | -0.2% | -0.2% | -0.2% | |\n| 2018 | 10%, 13,192 | 10%, 13,916 | 10%, 13,916 | 10%, 13,916 | 10%, 13,916 | 10%, 13,916 | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 92, "markdown_text": "## Retail Trade by Gender\n\nEqual shares of male and female workers are employed in the Retail sector in Greater Boston.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 93, "markdown_text": "## Retail Trade by Race/Ethnicity\n\nNearly 80% of workers in Retail are white in Greater Boston. Numbers of Black or African American, Hispanic or Latino, and Asian workers have been growing since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n| Chart Type | Description | |\n|------------------|-------------------------------------------------------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data on the x-axis and numerical data on the y-axis | |", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 94, "markdown_text": "## Appendix: Licensing Deep Dive", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 95, "markdown_text": "## Regional Occupation Demand and DPL Licensing: Deep Dive\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|--------------|------------|-------------------|\n| Allied Health | 4 | 1,717 | 2,032 |\n| Educational Psychologist | 3 | 1,746 | 2,117 |\n| Mental Health Counselor | 4 | 828 | 1,404 |\n| Applied Behavior Analyst | 5 | 1,114 | 1,972 |\n| Occupational Therapist | 5 | 1,985 | 3,850 |\n| Physical Therapist | 5 | 1,985 | 3,850 |\n| Architects | 5 | 1,564 | 3,375 |\n| Architect | 3 | 194 | 116 |\n| Chiropractors | 3 | 194 | 116 |\n| Chiropractor | 4 | 6,408 | 8,705 |\n| Cosmetology | Electricians | 4 | 3,033 |\n| Electrician | 4 | 3,033 | 7,823 |\n| Engineers And Land Surveyors | 4 | 3,868 | 27,230 |\n| Engineer* | 4 | 3,868 | 27,230 |\n| Gas Fitters | 4 | 2,867 | 5,378 |\n| Gas Fitter | 5 | 5,773 | 25,080 |\n| Public Accountancy | 5 | 5,773 | 25,080 |\n| Certified Public Accountant | 4 | 14,629 | 2,426 |\n| Real Estate | 4 | 14,629 | 2,426 |\n| Social Workers | 4 | 5,979 | 15,971 |\n| Social Worker, Licensed* | 4 | 5,979 | 15,971 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.\n\nSTARS\n\nLicenses\n\n2018\n\nEmployment!\n\n| ENGINEER | 4 | 3,868 | 27,230 |\n|--------------------------------------------------|-----|---------|----------|\n| Mechanical Engineers | 5 | 5,420 | |\n| Industrial Engineers | 5 | 4,930 | |\n| Electrical Engineers | 5 | 4,358 | |\n| Civil Engineers | 5 | 4,233 | |\n| Electronics Engineers, Except Computer | 5 | 2,372 | |\n| Biomedical Engineers | 4 | 1,889 | |\n| Computer Hardware Engineers | 4 | 1,763 | |\n| Environmental Engineers | 4 | 1,462 | |\n| Health and Safety Engineers | 3 | 463 | |\n| Aerospace Engineers | 3 | 340 | |\n| Social Workers | 4 | 5,979 | 15,971 |\n| Social Worker, Licensed* | 4 | 5,979 | 15,971 |\n| Healthcare Social Workers | 4 | 7,955 | |\n| Child, Family, and School Social Workers | 4 | 4,948 | |\n| Mental Health and Substance Abuse Social Workers | 3 | 3,068 | |\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 96, "markdown_text": "## Glossary", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 97, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 98, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 99, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Greater Boston Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Berkshire 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Berkshire Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Berkshire Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part II: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part III: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part IV: New Data Tools\n\n## Appendix\n\n- A: Regional Context\n- B: Worker Characteristics\n- C: Priority Industry Profiles\n- D: Critical Industry Profiles\n- E: Professional Licensing\n\n## Glossary", "report name": "2019 Berkshire Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Berkshire Data Package" }, { "slide_number": 5, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 6, "markdown_text": "## I.A: Regional Industry Overview", "report name": "2019 Berkshire Data Package" }, { "slide_number": 7, "markdown_text": "## Sector Makeup by Total Employment\n\nHealthcare and Social Assistance is the largest industry in the Berkshires, followed by Accommodation and Food Service and Retail, which each employ about two-thirds as many jobs as there are in Healthcare.\n\n| Category | Value | |\n|----------------|---------|----|\n| Healthcare | 16 | |\n| Accommodation | 14 | |\n| Retail | 12 | |\n| Education | 10 | |\n| Manufacturing | 8 | |\n| Construction | -0% | |\n| Administrative | -7% | |\n| Professional | -8% | |\n| Public | -1% | |\n| Other Services | -3% | |\n| Finance and | 2K | |\n| Wholesale | 1K | |\n| Transportation | 1K | |\n| Information | 1K | |\n| Retail | 1K | |\n| Other Services | -8% | |\n| Utilities | -2% | |\n| Management | -2% | |\n| Agriculture | -2% | |\n| Minoring | -2% | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 8, "markdown_text": "## Sector Makeup by Total Wages\n\nHealthcare and Social Assistance pays the most in wages of any industry in the Berkshires, followed by Educational Services and Manufacturing.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 9, "markdown_text": "## I.B: Priority Industry Profiles", "report name": "2019 Berkshire Data Package" }, { "slide_number": 10, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Berkshire Data Package" }, { "slide_number": 11, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 150 Healthcare and Social Assistance establishments were added in the Berkshires between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, Berkshire Health Systems had the largest number of job postings in the region, with 434 postings.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 12, "markdown_text": "## Healthcare and Social Assistance by Education\n\nWorkers in Healthcare and Social Assistance are almost evenly distributed between those who have a Bachelor's degree or higher, Some College or Associate degree, or High School equivalent or less.\n\n| | 11,705 | 11,705 | 12,345 | 12,345 |\n|-----|------------|------------|----------|------------|\n| | 9%, 1,051 | 9%, 1,051 | +4.9% | 9%, 1,102 |\n| | 27%, 3,184 | 27%, 3,184 | +2.0% | 26%, 3,248 |\n| 0% | 33%, 3,845 | 33%, 3,845 | +4.9% | 33%, 4,034 |\n| 40% | 23%, 2,727 | 23%, 2,727 | +7.0% | 24%, 2,918 |\n| 10% | 8%, 898 | 8%, 898 | +16.1% | 8%, 1,043 |\n| 0% | 2015 | 2015 | 2018 | 2018 |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 13, "markdown_text": "## Hospitality and Management", "report name": "2019 Berkshire Data Package" }, { "slide_number": 14, "markdown_text": "## Hospitality and Management Groups and Employers\n\nThe number of Hospitality and Management establishments in the Berkshires declined slightly from 2016 to 2018. Over the last 12 months, Canyon Ranch had the most job postings in the region, with 45. Compass Group (37) and Hyatt (33) followed.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 15, "markdown_text": "## Hospitality and Management by Education\n\nMore than 40% of workers in the Hospitality and Management sector have some college or higher level of education. 34% of this industry's workers in the Berkshires have a High school equivalent or less.\n\n| | 100% | 6,649 | -9.9% | 6,330 |\n|----|--------|------------|---------|------------|\n| | 90% | 26%, 1,700 | | 24%, 1,532 |\n| | 80% | | -0.8% | |\n| | 70% | 17%, 1,123 | | 18%, 1,114 |\n| 0% | 60% | 23%, 1,520 | | 23%, 1,479 |\n| | 40% | 23%, 1,546 | | 23%, 1,476 |\n| | 30% | 23%, 1,546 | | 23%, 1,476 |\n| | 10% | 11%, 760 | | 12%, 729 |\n| | 0% | 2015 | | 2018 |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 16, "markdown_text": "## Manufacturing", "report name": "2019 Berkshire Data Package" }, { "slide_number": 17, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of Manufacturing establishments in the Berkshires has stayed relatively stable since 2016. Over the last year, General Dynamics had the most job postings (490) in the region.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 18, "markdown_text": "## Manufacturing by Education\n\n45% of workers in Manufacturing in the Berkshires have a high school diploma or less. 30% have some college or an Associate degree and nearly 20% have a Bachelor's degree or higher. This mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | 4,382 | 3,808 |\n|-----|------------|-------------|\n| 90% | 7%, 311 | -22.7% |\n| 80% | 21%, 929 | 19%, 718 |\n| 70% | 28%, 1,245 | -9.7% |\n| 60% | 50% | 30%, 1,124 |\n| 50% | 40% | -9.2% |\n| 30% | 34%, 1,475 | -35%, 1,340 |\n| 20% | 10%, 422 | -6.6% |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 19, "markdown_text": "## Occupations", "report name": "2019 Berkshire Data Package" }, { "slide_number": 20, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 21, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | Industry-Specific, Statewide | All Industries, Regional | |\n|------------------------------------|-----------------|---------------------------------------------------|--------------------------------|--------------------|\n| Industry | SOC Code | Occupation Title | 2018 Industry | STAR |\n| | | Educational Requirement | 2018 Industry | Median Annual Wage |\n| | | Dental Hygienists | Associate's degree | 5,360 |\n| | | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 |\n| Health Care and Social Assistance | 29-2061 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 820 |\n| | | | Some college, no degree | $45,451 |\n| | | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 150 |\n| Hospitality and Management | 53-3032 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 130 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 1,130 |\n| | | | | $45,451 |\n| | | | | $44,780 |\n| | 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 1,560 |\n| Manufacturing | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 50 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 1,220 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 22, "markdown_text": "## Part II: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Berkshire Data Package" }, { "slide_number": 23, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Berkshire Data Package" }, { "slide_number": 24, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Berkshire Data Package" }, { "slide_number": 25, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3+ Stars\n\nAt the sub-BA level, a number of occupations rated 3+ stars do not have enough regional supply to meet employer demand.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 26, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Berkshire Data Package" }, { "slide_number": 27, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Berkshire Data Package" }, { "slide_number": 28, "markdown_text": "## Part III: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Berkshire Data Package" }, { "slide_number": 29, "markdown_text": "## III. A: Apprenticeships", "report name": "2019 Berkshire Data Package" }, { "slide_number": 30, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 31, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 32, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 33, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn the Berkshires, the most popular occupations for apprentices (Electricians, Carpenters, Plumbers, Pipefitters, and Steamfitters, and Construction Laborers) are ranked 4 stars, indicating high wages and strong projected employer demand.\n\n| | Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|--------------------|----------------|---------------|----------|\n| Electricians | 4 | 32 | 61 | |\n| Carpenters | 4 | 13 | 91 | |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 11 | 32 | |\n| Construction Laborers | 4 | 7 | 129 | |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 2 | 31 | |\n| Police and Sheriff's Patrol Officers | 3 | 1 | 28 | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 34, "markdown_text": "## III. B: Professional Licensing", "report name": "2019 Berkshire Data Package" }, { "slide_number": 35, "markdown_text": "## Top Occupations by DPL Professional Licensing\n\nIn the Berkshires, a majority of the top occupations by number of Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 36, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses exceeds total employment for some occupations, such as Cosmetologists, for others, such as Educational Psychologists, the number of jobs (167) outstrips the supply of licenses (53).\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|---------|------------|-------------------|\n| Allied Health | 4 | 49 | 103 |\n| Occupational Therapist | 4 | 63 | 157 |\n| Physical Therapist | 4 | 53 | 167 |\n| Educational Psychologist | | | |\n| Cosmetology | | | |\n| Cosmetologist (Hairdresser) | 3 | 387 | 330 |\n| Electricians | | | |\n| Electrician | 4 | 222 | 400 |\n| Engineers And Land Surveyors | | | |\n| Engineer | 4 | 61 | 393 |\n| Gas Filters | | | |\n| Gas Fitter | 4 | 283 | 211 |\n| Public Accountancy | | | |\n| Certified Public Accountant | 5 | 46 | 584 |\n| Real Estate | | | |\n| Real Estate Salesperson | 3 | 387 | 241 |\n| Social Workers | | | |\n| Social Worker, Licensed | 4 | 315 | 470 |\n| Social Worker Assistant | 3 | 82 | 375 |\n| | | | |\n\nSelected occupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 37, "markdown_text": "## Part IV: New Data Tools", "report name": "2019 Berkshire Data Package" }, { "slide_number": 38, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Berkshire Data Package" }, { "slide_number": 39, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Berkshire Data Package" }, { "slide_number": 40, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Berkshire Data Package" }, { "slide_number": 41, "markdown_text": "## Appendix: Regional Context", "report name": "2019 Berkshire Data Package" }, { "slide_number": 42, "markdown_text": "## Unemployment Rate\n\nBerkshire's unemployment rate has been between .5 and 1 percentage points higher than the state average for much of the past year.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 43, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nBerkshire's labor force grows during the summer months, when tourism is strongest.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 44, "markdown_text": "## Median Annual Wage\n\nBerkshire's median annual wage is the lowest across all regions, though it has increased since 2015.\n\n| Year | Median Annual Wage | 2018 Median Annual Wage | |\n|---------|----------------------|---------------------------|----|\n| $36,317 | $38,179 | $56,732 | |\n| $40,646 | $43,133 | $53,153 | |\n| $42,366 | $40,646 | $45,698 | |\n| $40,133 | $53,153 | $40,163 | |\n| $42,225 | $45,698 | $41,303 | |\n| $40,163 | $53,153 | $46,690 | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 45, "markdown_text": "## Educational Requirements for Employment\n\nOne in five of all jobs in the Berkshires in 2026 are projected to need a Bachelor's degree or higher and two-thirds will require a high school diploma/equivalency or less.\n\n\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 46, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Berkshire Data Package" }, { "slide_number": 47, "markdown_text": "## Priority and Critical Industries by Age\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 48, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 49, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 50, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 51, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 52, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 Berkshire Data Package" }, { "slide_number": 53, "markdown_text": "## Healthcare and Social\n\nAssistance", "report name": "2019 Berkshire Data Package" }, { "slide_number": 54, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n| Female | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 55, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\n[Note: Check axis scale on chart on left.] While most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been greater for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Chart Type | Description | |\n|------------------|---------------------------------------------------------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data on the x-axis and numerical values on the y-axis | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 56, "markdown_text": "## Hospitality and Management", "report name": "2019 Berkshire Data Package" }, { "slide_number": 57, "markdown_text": "## Hospitality and Management by Gender\n\nThe Hospitality and Management industry has almost equal shares of male and female workers in the Berkshires.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 58, "markdown_text": "## Hospitality and Management by Race/Ethnicity\n\nWorkers in Hospitality and Management in the Berkshires are predominantly white, with only 8% of workers identifying as Black or African American or Asian.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 59, "markdown_text": "## Manufacturing", "report name": "2019 Berkshire Data Package" }, { "slide_number": 60, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers are predominantly male.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 61, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce is predominantly white in the Berkshires, with only about 4 percent of workers identifying as Black or African American, or Asian.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 62, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Berkshire Data Package" }, { "slide_number": 63, "markdown_text": "## Educational Services", "report name": "2019 Berkshire Data Package" }, { "slide_number": 64, "markdown_text": "## Educational Services Groups and Employers\n\nThe number of Educational Services establishments in the Berkshires remained stable between 2016 and 2018. Over the last 12 months, the employer with the most online job postings in the region was Williams College, with 115.\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 65, "markdown_text": "## Educational Services by Education\n\n66% of workers in the Educational Services sector in the Berkshires have at least some college education.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|----|\n| 2015 | 6% | -6.6% | 26% | -4.7% | 21% | |\n| 2018 | 6% | -3.7% | 21% | 1.423 | 6% | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 66, "markdown_text": "## Educational Services by Gender\n\nMore than 60% of Educational Services workers are female.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Change in # of Employees | Male | |\n|----------------------------|--------|----|\n| -6% | -6% | |\n| -25% | -6% | |\n| -30% | -6% | |\n| -300% | -6% | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 67, "markdown_text": "## Educational Services by Race/Ethnicity\n\nMore than 90% of Educational Services workers are white, although the share of Black or African American, Asian, and Hispanic or Latino workers in the sector has increased since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 68, "markdown_text": "## Arts, Entertainment, and Recreation", "report name": "2019 Berkshire Data Package" }, { "slide_number": 69, "markdown_text": "## Arts, Entertainment, and Recreation Groups and Employers\n\nThe number of Arts, Entertainment and Recreation establishments in the Berkshires remained stable between 2016 and 2018. Over the last 12 months, Sterling and Francine Clark Art Institute was the employer responsible for the most job postings in the Berkshires (18).\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 70, "markdown_text": "## Arts, Entertainment, and Recreation by Education\n\nArts, Entertainment and Recreation, like Hospitality, affords opportunities to people with a variety of educational backgrounds. 21% of workers in the Berkshires have a high school diploma, 25% have some college or an Associate degree, and 26% have a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 71, "markdown_text": "## Arts, Entertainment, and Recreation by Gender\n\nEmployment in the Arts, Entertainment and Recreation sector in the Berkshires is fairly evenly split between male and female workers.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018 | |\n|-----------------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 72, "markdown_text": "## Arts, Entertainment, and Recreation by Race/Ethnicity\n\nMore than 95% of workers in the Arts, Entertainment and Recreation industry are white in the Berkshires. Numbers of people of color working in the sector have grown by a small amount since 2015.\n\n\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 73, "markdown_text": "## Finance and Insurance", "report name": "2019 Berkshire Data Package" }, { "slide_number": 74, "markdown_text": "## Finance and Insurance Groups and Employers\n\nThe number of Finance and Insurance establishments in the Berkshires has remained stable since 2016. In the last year, Berkshire Bank was responsible for the most job postings in the region (63), followed by Assurance (55) and AmeriPlan (28).\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 75, "markdown_text": "## Finance and Insurance by Education\n\nMore than 66% of Finance and Insurance workers in the Berkshires have at least some college education, although their share of total sector employment has decreased since 2015.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | |\n|------|--------------------------------------------------------------------|-----------------|\n| 100% | 2,146 | 1,930 |\n| 90% | 5%, 107 | +28.0% 7%, 137 |\n| 80% | 40%, 869 | -19.1% 36%, 703 |\n| 70% | 60% | -9.4% |\n| 60% | 50% | -9.4% |\n| 30% | 30%, 638 | 30%, 578 |\n| 20% | 21%, 440 | -7.0% 21%, 409 |\n| 10% | 4%, 92 | +12.0% 5%, 103 |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 76, "markdown_text": "## Finance and Insurance by Gender\n\nNearly 70% of Finance and Insurance workers in the Berkshires are female.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Change in of Employees of Employees | Male | Female | |\n|---------------------------------------|--------|----------|----|\n| -16% | -140 | -120 | |\n| -16% | -100 | -7% | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 77, "markdown_text": "## Finance and Insurance by Race/Ethnicity\n\nMore than 95% of all workers in the Finance and Insurance sector in the Berkshires are white. The number of Black or African American workers has grown the most since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 78, "markdown_text": "## Professional and Technical Services", "report name": "2019 Berkshire Data Package" }, { "slide_number": 79, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nProfessional and Technical Services include legal, management consulting, accounting and bookkeeping, and architectural and engineering services. There are slightly more establishments in this sector in 2018 than in 2016. H&R Block had the highest number of job postings in this sector in the Berkshires over the past year (36).\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 80, "markdown_text": "## Professional and Technical Services by Education\n\n41% of workers in Professional and Technical Services in the Berkshires have a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Education Attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|-------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-------------|----|\n| 2015 | 43%, 1,122 | 26%, 684 | +18.1% | 26%, 808 | 26% - 808 | |\n| 2018 | 7%, 194 | 25.8% | +11.8% | 41%, 1.254 | 41% - 1.254 | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 81, "markdown_text": "## Professional and Technical Services by Gender\n\nIn the Berkshires, 60% of Professional and Technical Services workers are male.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Male | Female | |\n|--------|----------|----|\n| +12% | +12% | |", "report name": "2019 Berkshire Data Package" }, { "slide_number": 82, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 92% of workers in the Professional and Technical Services industry in the Berkshires are white. Though there have been increases since 2015 in the number of Black or African American, Asian and Hispanic or Latino workers, the numbers are still relatively small.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Berkshire Data Package" }, { "slide_number": 83, "markdown_text": "## Appendix: Professional Licensing", "report name": "2019 Berkshire Data Package" }, { "slide_number": 84, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|--------------------------------------|---------|------------|--------------------------------------------------|\n| Allied Health Occupational Therapist | 4 | 49 | 103 |\n| Physical Therapist | 4 | 63 | 157 |\n| Educational Psychologist | 4 | 53 | 167 |\n| Cosmetology | 3 | 387 | 330 |\n| Cosmetologist (Hairdresser) | 3 | 387 | 330 |\n| Electricians | 4 | 222 | 400 |\n| Engineers And Land Surveyors | 4 | 61 | 393 |\n| Engineer � | 4 | 61 | 393 � |\n| Gas Fitters | 4 | 283 | 211 |\n| Gas Fitter | 4 | 283 | Social Workers |\n| Public Accountancy | 5 | 46 | 584 |\n| Certified Public Accountant | 3 | 387 | Healthcare Social Workers |\n| Real Estate | 3 | 387 | 241 |\n| Real Estate Salesperson | 4 | 387 | Mental Health and Substance Abuse Social Workers |\n| Social Workers | 4 | 315 | 470 |\n| Social Worker, Licensed � | 3 | 82 | 375 |\n| Social Worker Assistant | 3 | 82 | 470 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Berkshire Data Package" }, { "slide_number": 85, "markdown_text": "## Glossary", "report name": "2019 Berkshire Data Package" }, { "slide_number": 86, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Berkshire Data Package" }, { "slide_number": 87, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Berkshire Data Package" }, { "slide_number": 88, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Berkshire Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Pioneer Valley 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I: Regional Context\n\n- i. Unemployment Rate\n- ii. Labor Force - Educational Requirements for Employment\n\n## Part II. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part III: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part IV: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part V: New Data Tools\n\n## Appendix\n\n- A: Worker Characteristics\n- B: Priority Industry Profiles\n- C: Critical Industry Profiles\n- D: Professional Licensing\n\n## Glossary", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Context", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 5, "markdown_text": "## Unemployment Rate\n\nPioneer Valley's unemployment rate historically tracks with the state average, about a percentage point or so higher.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 0.0% | 1.0% | 2.0% | 3.0% | 4.0% | 5.0% | 6.0% | 7.0% | 8.0% | 9.0% | 10.0% | 11.0% | | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 6, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThere are slightly fewer unemployed workers in the Pioneer Valley as of May 2019 than the prior year. The overall labor force has also increased, as some people who previously were no longer looking for work have returned to the labor market and are having success finding employment.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 7, "markdown_text": "## Median Annual Wage\n\nPioneer Valley's median annual wage has increased since 2015, but is still significantly lower than the state average, and lower than all other regions except for the Berkshires.\n\n| Berkshire | Cape and Islands | Central | Greater Boston | Northeast | Pioneer Valley | Southeast | Massachusetts | |\n|-------------|--------------------|-----------|------------------|-------------|------------------|-------------|-----------------|----|\n| $36,317 | $38,179 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $30,000 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $20,000 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $10,000 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $0 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 8, "markdown_text": "## Educational Requirements for Employment\n\nPioneer Valley is projected to have the same shares of jobs that require BA+; AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 9, "markdown_text": "## Part II: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 10, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 11, "markdown_text": "## II.A: Regional Industry Overview", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 12, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry in the Pioneer Valley. The next largest sector, Educational Services, employs 30K fewer workers, followed by Retail Trade.\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 0 | |\n| Educational | 0 | |\n| Retail Trade | 0 | |\n| Accommodatio | 0 | |\n| Manufacturing | 0 | |\n| Public | 0 | |\n| Construction | 0 | |\n| Administrative | 0 | |\n| Transportation | 0 | |\n| Finance | 0 | |\n| Other Services | 0 | |\n| Wholesale | 0 | |\n| Professional | 0 | |\n| Arts | 0 | |\n| Management | 0 | |\n| Information | 0 | |\n| Agriculture | 0 | |\n| Mining | 0 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 13, "markdown_text": "## Sector Makeup by Total Wages\n\nHealth Care and Social Assistance and Educational Services paid the highest total wages in Pioneer Valley, followed by Manufacturing.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 14, "markdown_text": "## II.B: Priority Industry Profiles", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 15, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 16, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 1,000 Health Care and Social Assistance establishments were added in Pioneer Valley between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, Baystate Health posted the most jobs in Pioneer Valley, with 2,520.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 17, "markdown_text": "## Healthcare and Social Assistance by Education\n\n57% of workers in Healthcare and Social Assistance have some college or higher level of education in the Pioneer Valley.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 |\n|------|--------------------------------------------------------------------|\n| 100% | 65,622 70,740 |\n| 90% | 10%, 6,423 9%, 6,506 |\n| 80% | 27%, 17,662 26%, 18,064 |\n| 70% | 60% |\n| 50% | 31%, 20,476 31%, 21,782 |\n| 20% | 21%, 13,905 22%, 15,512 |\n| 10% | 11%, 7,156 24.0% |\n| 0% | 2015 2018 |\n| | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 18, "markdown_text": "## Educational Services", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 19, "markdown_text": "## Educational Services Groups and Employers\n\nThe number of Educational Services establishments in Pioneer Valley grew slightly between 2016 and 2018, driven primarily by growth in educational support services. Over the last 12 months, the employer with the most job postings in Pioneer Valley was UMass Amherst, with 493.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 20, "markdown_text": "## Educational Services by Education\n\n40% of workers in Educational Services have a Bachelor's degree or higher in the Pioneer Valley.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|------|----|\n| 2015 | 42% | 40% | 40% | 40% | 40% | |\n| 2018 | 7% | 5.1% | 5.6% | 4.2% | 4.8% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 21, "markdown_text": "## Manufacturing", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 22, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of Manufacturing establishments in Pioneer Valley declined slightly between 2016 and 2018. In the last year, Advanced Drainage Systems was the employer with the highest number of job postings in Pioneer Valley (141), followed by Coca-Cola Enterprises Inc. (99), Stanley Black & Decker (67) and The Yankee Candle Company, Inc. (57).\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 23, "markdown_text": "## Manufacturing by Education\n\n45% of workers in Manufacturing in the Pioneer Valley have a high school diploma or less. 30% of workers in Manufacturing have some college or an Associate Degree and nearly 20% have a Bachelor's degree or higher. This educational attainment mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | % of Employees | |\n|--------|------------------|----|\n| 2015 | 30% | |\n| 2018 | 31% | |\n| 2017 | 31% | |\n| 2016 | 30% | |\n| 2017 | 30% | |\n| 2018 | 30% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 24, "markdown_text": "## Occupations", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 25, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 26, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|------------------|----------------------------------------------------|--------------------------------|--------------------------------|----------------------------|\n| Occupation Title | Occupation Title | Occupation Title | Occupation Title | Occupation Title |\n| 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 330 | 4 |\n| 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 330 | 4 |\n| 31-9092 | Medical Assistants | Postsecondary non-degree award | 120 | 4 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 1,670 | 4 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 2,350 | 4 |\n| 25-9041 | Teacher Assistants | Some college, no degree | 33,670 | 34,124 |\n| 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 | 4 |\n| 29-2034 | Radiologic Technologists | Associate's degree | 4,100 | 65,654 |\n| 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 | 61,914 |\n| 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 | 54,879 |\n| 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 | 36,925 |\n| 29-2071 | Medical Records and Health Information Technicians | Postsecondary non-degree award | 4,220 | 40,440 |\n| 29-2055 | Surgical Technologists | Postsecondary non-degree award | 2,870 | 58,730 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 | 40,589 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 820 | 4 |\n| 25-9041 | Teacher Assistants | Some college, no degree | 4,740 | 4 |\n| 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 50 | 61,914 |\n| 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 1,560 | 46,232 |\n| 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 2,870 | 40,589 |\n| 15-1151 | Computer User Support Specialists | Some college, no degree | 1,220 | 4 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations appear across multiple priority industries.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 27, "markdown_text": "## Part III: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 28, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 29, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 30, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 4+ Stars\n\nAt the sub-BA level, a number of 4- and 5-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 31, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3 Stars\n\nAt the sub-BA level, a number of 3-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n3-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 32, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 33, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 34, "markdown_text": "## Part IV: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 35, "markdown_text": "## IV. A: Apprenticeships", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 36, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 37, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 38, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 39, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn Pioneer Valley, the most popular occupations for apprentices (Electricians, Carpenters, Plumbers, Pipefitters, and Steamfitters, and Construction Laborers) are ranked 4 or 5 stars, indicating high wages and strong projected employer demand.\n\nSource: Division of Apprentice Standards, 2019\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|----------------|---------------|----------|\n| Electricians | 5 | 178 | 193 |\n| Carpenters | 4 | 92 | 236 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 64 | 188 |\n| Construction Laborers | 4 | 45 | 239 |\n| Sheet Metal Workers | 3 | 44 | 36 |\n| Opticians, Dispensing | 2 | 30 | 16 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 27 | 119 |\n| Roofers | 3 | 25 | 31 |\n| Police and Sheriff's Patrol Officers | 4 | 12 | 226 |\n| Operating Engineers and Other Construction Equipment Operators | 4 | 12 | 97 |\n| Electrical Power-Line Installers and Repairers | 3 | 12 | 25 |\n| Pharmacy Technicians | 2 | 10 | 151 |\n| Painting, Coating, and Decorating Workers | 2 | 7 | 31 |\n| | | | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 40, "markdown_text": "## IV. B: Professional Licensing", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 41, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nIn Pioneer Valley, a majority of the top occupations by number of associated Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 42, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses greatly exceeds total employment for some occupations, such as Cosmetologists, for others, such as Mental Health Counselors, the number of jobs (1,090) outstrips the supply of licenses (563).\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|--------------------------------|---------|------------|-------------------|\n| Allied Health | 3 | 104 | 109 |\n| Occupational Therapy Assistant | 5 | 388 | 574 |\n| Occupational Therapist | 4 | 158 | 245 |\n| Physical Therapist Assistant | 4 | 563 | 1,090 |\n| Mental Health Counselor | 4 | 563 | 1,090 |\n| Physical Therapist | 5 | 388 | 760 |\n| Applied Behavior Analyst | 4 | 186 | 367 |\n| Educational Psychologist | 5 | 221 | 765 |\n| Cosmetology | | | |\n| Cosmetologist (Hairdresser) | 5 | 2,271 | 1,662 |\n| Electricians | | | |\n| Electrician | 5 | 1,257 | 1,148 |\n| Engineers And Land Surveyors | | | |\n| Engineer | 4 | 658 | 807 |\n| Gas Fitters | | | |\n| Gas Fitter | 4 | 966 | 1,219 |\n| Public Accountancy | | | |\n| Certified Public Accountant | 5 | 256 | 2,160 |\n| Social Workers | | | |\n| Social Worker, Licensed | 4 | 1,681 | 3,211 |\n| | | | |\n\nSelected occupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 43, "markdown_text": "## Part V: New Data Tools", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 44, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 45, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 46, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 47, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 48, "markdown_text": "## Priority and Critical Industries by Age\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 49, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 50, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 51, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 52, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 53, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 54, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 55, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| % of Industry Employment | % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----------------------------|----|\n| 16.792 | 53.948 | 20% | |\n| 10% | 90% | 70% | |\n| 80% | 70% | 60% | |\n| 70% | 53.948 | 40% | |\n| 50% | 40% | 30% | |\n| 30% | 20% | 10% | |\n\n| Male | Female | |\n|--------|----------|----|\n| +1,500 | +9% | |\n| +500 | +7% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 56, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been increasing for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nPercent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 57, "markdown_text": "## Educational Services", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 58, "markdown_text": "## Educational Services by Gender\n\nMore than half of workers in the Educational Services sector are female.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 59, "markdown_text": "## Educational Services by Race/Ethnicity\n\nNearly 88% of workers in the Educational Services sector in the Pioneer Valley are white. Since 2015, there has been some growth in the numbers of people of color working in the sector (Black or African American, Asian, and Hispanic or Latino).\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 60, "markdown_text": "## Manufacturing", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 61, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in the Pioneer Valley are predominantly male. Female workers make up about 25% of workers in Manufacturing in the region.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| 0% | |\n| 10% | |\n| 20% | |\n| 30% | |\n| 40% | |\n| 50% | |\n| 60% | |\n| 70% | |\n| 80% | |\n| 90% | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| 0% | |\n| 10% | |\n| 20% | |\n| 30% | |\n| 40% | |\n| 50% | |\n| 60% | |\n| 70% | |\n| 80% | |\n| 90% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 62, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce in the Pioneer Valley has seen some growth in the numbers of people of color since 2015, though nearly 90% of workers are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 63, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 64, "markdown_text": "## Professional and Technical Services", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 65, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nPioneer Valley is home to nearly 1,500 establishments in the Professional and Technical Services sector, which includes legal, accounting and bookkeeping, management and technical consulting, and computer systems design and related services. H&R Block was the only employer with more than 100 job postings in Pioneer Valley over the last year (155), followed by Teach for America (53).\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 66, "markdown_text": "## Professional and Technical Services by Education\n\nNearly 40% of workers in the Professional and Technical Services sector in the Pioneer Valley have a Bachelor's degree or higher, while more than 25% have some college or an Associate degree.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-------|----|\n| 2015 | 39%, 3,204 | -1.8% | -2.7% | 38%, 3,116 | -2.7% | |\n| 2018 | 28%, 2,300 | -1.8% | -2.5% | 27%, 2,259 | -2.5% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 67, "markdown_text": "## Professional and Technical Services by Gender\n\nEmployment in the Professional and Technical Services sector is fairly evenly split between male and female workers.\n\n\n\nPercent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n| Male | Female | |\n|--------|----------|----|\n| -150 | -3% | |\n| -200 | -3% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 68, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 90 percent of workers in the Professional and Technical Services Sector in the Pioneer Valley are white, though the numbers of Asian and Hispanic or Latino workers are growing somewhat.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 69, "markdown_text": "## Finance and Insurance", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 70, "markdown_text": "## Finance and Insurance Groups and Employers\n\nThe number of Finance and Insurance establishments in Pioneer Valley has remained stable since 2016. In the last year, Massachusetts Mutual Life Insurance was responsible for the largest number of job postings in Pioneer Valley (378).\n\n| Year | Top 5 Industry Groups by Number of Establishments | Largest Employers by 12-Month Regional Job Postings | |\n|--------|-----------------------------------------------------|-------------------------------------------------------|----|\n| 2016 | 693 | 78 | |\n| 2018 | 691 | 77 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 71, "markdown_text": "## Finance and Insurance by Education\n\nFinance and Insurance employment has declined slightly since 2015. More than 40% of workers in the sector in the Pioneer Valley hold a Bachelor's degree or higher.\n\n| Year | Education Attainment | Occupancy | Bachelor's degree or advanced degree | Some college or Associate degree | High school or equivalent, no college | Less than high school | |\n|--------|------------------------|-------------|----------------------------------------|------------------------------------|-----------------------------------------|-------------------------|----|\n| 2015 | 40% | 28% | 28% | 28% | 28% | 28% | |\n| 2018 | 17% | 18% | 18% | 18% | 18% | 18% | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 72, "markdown_text": "## Finance and Insurance by Gender\n\nNumbers of workers in the Finance and Insurance sector in the Pioneer Valley are just over 60% female and 40% male.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n\n| Male | Female | |\n|--------|----------|----|\n| -200 | -4% | |\n| -250 | -300 | |\n| -300 | -250 | |\n| -300 | -200 | |\n| -300 | -150 | |\n| -300 | -100 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 73, "markdown_text": "## Finance and Insurance by Race/Ethnicity\n\nNearly 90% of all workers in the Finance and Insurance sector in the Pioneer Valley are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 74, "markdown_text": "## Hospitality", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 75, "markdown_text": "## Hospitality Groups and Employers\n\nThe number of Hospitality-related establishments in Pioneer Valley declined slightly between 2016 and 2018. In the last year, MGM Resorts International was responsible for the most online job postings Pioneer Valley (286), followed by Aramark (164) and Chipotle Mexican Grill (126).\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 76, "markdown_text": "## Hospitality by Education\n\nHospitality affords opportunities to people with a variety of educational backgrounds and employs significant shares of young people (\n\n| Year | Education Attainment | High school or equivalent, no college | Less than high school | |\n|--------|------------------------|-----------------------------------------|-------------------------|----|\n| 2015 | 13%, 2,895 | +10.4% | +13%, 3,029 | |\n| 2018 | 19%, 4,460 | +6.1% | +20%, 4,734 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 77, "markdown_text": "## Hospitality by Gender\n\nMore than half of workers in Hospitality in the Pioneer Valley are female.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 78, "markdown_text": "## Hospitality by Race/Ethnicity\n\nMore than 80% of workers in Hospitality in the Pioneer Valley are white. Numbers of Black or African American and Hispanic or Latino workers have grown by sizable amounts in the sector since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 79, "markdown_text": "## Agriculture", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 80, "markdown_text": "## Agriculture Groups and Employers\n\nThe number of Agricultural sector establishments in the Pioneer Valley declined slightly between 2016 and 2018. In the last year, CocaCola Enterprises, Inc. was responsible for the greatest number of online job postings related to Agriculture and Sustainable Food Systems in Pioneer Valley.\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 81, "markdown_text": "## Agriculture by Education\n\nShares of workers in Agriculture in the Pioneer Valley have a variety of educational backgrounds, with about 25% having a high school diploma or equivalent, 26% having some college or an Associate degree and 20% having a Bachelor's degree or higher.\n\n| | 100% | 928 | -3.8% | 1,063 |\n|----------------|--------|----------|------------------------------------------------------------------------------------------------------------|----------|\n| | 90% | 17%, 160 | +18.6% | 14%, 154 |\n| | 80% | 19%, 177 | +18.6% | 20%, 210 |\n| % of Employees | 60% | 23%, 213 | +28.6% | 26%, 274 |\n| | 50% | 40% | +13.4% | 25%, 263 |\n| | 30% | 25%, 232 | +11.0% | 15%, 162 |\n| | 10% | 16%, 146 | +11.0% | 2018 |\n| | 0% | 2015 | Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018 | |", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 82, "markdown_text": "## Agriculture by Gender\n\nMore than 50% of Agricultural workers in the Pioneer Valley are male.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 83, "markdown_text": "## Agriculture by Race/Ethnicity\n\nMore than 85% of Agricultural workers in the Pioneer Valley are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 84, "markdown_text": "## Appendix: Professional Licensing", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 85, "markdown_text": "## Regional Occupation Demand and DPL Licensing: Deep Dive\n\n| DPL Board/License Type | STARS | Licenses | 2018 Employment |\n|--------------------------------|---------|------------|-------------------|\n| Allied Health | 3 | 104 | 109 |\n| Occupational Therapy Assistant | 5 | 388 | 574 |\n| Occupational Therapist | 4 | 158 | 245 |\n| Physical Therapist Assistant | 4 | 563 | 1,090 |\n| Mental Health Counselor | 4 | 583 | 388 |\n| Physical Therapist | 5 | 388 | 760 |\n| Applied Behavior Analyst | 4 | 186 | 367 |\n| Educational Psychologist | 5 | 221 | 765 |\n| Rehabilitation Counselor | 3 | 7 | 820 |\n| Cosmetology | 5 | 2,271 | 1,662 |\n| Cosmetologist (Hairdresser) | 5 | 2,271 | 1,662 |\n| Electricians | 5 | 1,257 | 1,148 |\n| Electrician | 4 | 658 | 807 |\n| Engineers And Land Surveyors | 4 | 658 | 807 |\n| Engineer* | 4 | 966 | 1,219 |\n| Gas Fitters | 4 | 966 | 1,219 |\n| Gas Fitter | 4 | 966 | 1,219 |\n| Health Officers | 5 | 5 | 1,268 |\n| Certified Health Officer | 5 | 5 | 1,268 |\n| Public Accountancy | 5 | 256 | 2,160 |\n| Certified Public Accountant | 4 | 256 | 2,160 |\n| Social Workers | 4 | 1,681 | 3,211 |\n| Social Worker, Licensed* | 4 | 1,681 | 3,211 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 86, "markdown_text": "## Glossary", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 87, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 88, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 89, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Pioneer Valley Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Central 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Central Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Central Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I: Regional Context\n\n- i. Unemployment Rate\n- ii. Labor Force - Educational Requirements for Employment\n\n## Part II. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part III: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part IV: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part V: New Data Tools\n\n## Appendix\n\n- A: Worker Characteristics\n- B: Priority Industry Profiles\n- C: Critical Industry Profiles\n- D: Professional Licensing\n\n## Glossary", "report name": "2019 Central Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Context", "report name": "2019 Central Data Package" }, { "slide_number": 5, "markdown_text": "## Unemployment Rate\n\nCentral MA's unemployment rate historically tracks with the state average, though slightly higher.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | | |", "report name": "2019 Central Data Package" }, { "slide_number": 6, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThere are fewer unemployed workers in Central MA as of May 2019 than the prior year. The overall labor force has also increased, as some people who previously were no longer looking for work have returned to the labor market and are having success finding employment.\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 7, "markdown_text": "## Median Annual Wage\n\nCentral MA's median annual wage has increased since 2015, but is still lower than the state average, Greater Boston and Northeast.\n\n| Year | Median Annual Wage | 2018 Median Annual Wage | |\n|---------|----------------------|---------------------------|----|\n| $36,317 | $56,732 | $40,646 | |\n| $38,179 | $53,153 | $40,646 | |\n| $38,433 | $42,366 | $40,646 | |\n| $38,601 | $42,225 | $45,698 | |\n| $38,163 | $42,797 | $41,303 | |\n| $38,601 | $42,225 | $46,690 | |", "report name": "2019 Central Data Package" }, { "slide_number": 8, "markdown_text": "## Educational Requirements for Employment\n\nCentral MA is projected to have similar shares of jobs that require BA++; AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 9, "markdown_text": "## Part II: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Central Data Package" }, { "slide_number": 10, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Central Data Package" }, { "slide_number": 11, "markdown_text": "## II.A: Regional Industry Overview", "report name": "2019 Central Data Package" }, { "slide_number": 12, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry in Central MA and has grown 5% since 2016. Half as many workers are employed by Retail and Manufacturing, the next two largest industries in the region by employment.\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 0 | |\n| Retail Trade | 0 | |\n| Manufacturing | 0 | |\n| Education | 0 | |\n| Accommodation | 0 | |\n| Construction | 0 | |\n| Administrative | 0 | |\n| Professional | 0 | |\n| Public | 0 | |\n| Finance | 0 | |\n| Transportation | 0 | |\n| Wholesale | 0 | |\n| Other Services | 0 | |\n| Arts | 0 | |\n| Information | 0 | |\n| Management | 0 | |\n| Agriculture | 0 | |\n| Mining | 0 | |", "report name": "2019 Central Data Package" }, { "slide_number": 13, "markdown_text": "## Sector Makeup by Total Wages\n\nHealth Care and Social Assistance and Manufacturing paid the highest total wages in Central MA, followed by Educational Services.", "report name": "2019 Central Data Package" }, { "slide_number": 14, "markdown_text": "## II.B: Priority Industry Profiles", "report name": "2019 Central Data Package" }, { "slide_number": 15, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Central Data Package" }, { "slide_number": 16, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 1,000 Health Care and Social Assistance establishments were added in Central MA between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, UMass Memorial Healthcare posted the most jobs in Central MA (1,848), followed by Tenet Health System (893), and Seven Hills Foundation (868).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 17, "markdown_text": "## Healthcare and Social Assistance by Education\n\n61% of workers in Healthcare and Social Assistance have some college or higher level of education.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Education attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|-------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|------|----|\n| 2015 | 31%, 21,731 | +7.4% | +12.1% | 21%, 15,584 | 2018 | |\n| 2018 | 31%, 23,331 | +12.1% | +22.2% | 9%, 6,922 | 2018 | |", "report name": "2019 Central Data Package" }, { "slide_number": 18, "markdown_text": "## Manufacturing", "report name": "2019 Central Data Package" }, { "slide_number": 19, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of Manufacturing establishments in Central MA declined slightly between 2016 and 2018. In the last year, Waters Corporation was responsible for the largest number of job postings in Central MA (740), followed by Jabil Circuit (211), and Bristol-Myers Squibb (204).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 20, "markdown_text": "## Manufacturing by Education\n\n40% of workers in Manufacturing in Central MA have a high school diploma or less. More than a quarter of workers in Manufacturing have some college or an Associate Degree and 25% have a Bachelor's degree or higher. This mix has been relatively stable since 2015.", "report name": "2019 Central Data Package" }, { "slide_number": 21, "markdown_text": "## Transportation and Warehousing", "report name": "2019 Central Data Package" }, { "slide_number": 22, "markdown_text": "## Transportation and Warehousing Groups and Employers\n\nTransportation and warehousing includes freight trucking and taxi and limo services, among others. UPS had the largest number of job postings in the past year in this industry in Central MA, followed by FedEx.\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 23, "markdown_text": "## Transportation and Warehousing by Education\n\n45% of the workers in the Transportation and Warehousing sector have a high school diploma or less.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Education attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|-------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|----|\n| 2015 | 31%, 3,328 | 43.8% | 30%, 3,456 | 15%, 1,665 | 10% | |\n| 2018 | 14%, 1,450 | +14.8% | 30%, 3,456 | 15%, 1,665 | 10% | |", "report name": "2019 Central Data Package" }, { "slide_number": 24, "markdown_text": "## Occupations", "report name": "2019 Central Data Package" }, { "slide_number": 25, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Central Data Package" }, { "slide_number": 26, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | Socio Code | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|---------------|---------------|----------------------------------------------------|--------------------------------|--------------------------------|----------------------------|\n| 2018 Industry | 2018 Industry | 2018 Industry | 2018 Industry | 2018 Industry | 2018 Industry |\n| | 29-2021 | Dental Hygienists | Associate's degree | 5,360 | 4 |\n| | 29-2034 | Radiologic Technologists | Associate's degree | 4,100 | 4 |\n| | 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 | 4 |\n| | 29-1126 | Respiratory Therapists | Associate's degree | 2,250 | 4 |\n| | 15-1134 | Web Developers | Associate's degree | 90 | 4 |\n| | 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| | 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 | 5 |\n| | 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 | 4 |\n| | 29-2071 | Medical Records and Health Information Technicians | Postsecondary non-degree award | 4,220 | 46,510 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 | 4 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 | 44,122 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 820 | 52,664 |\n| | 17-3023 | Electrical and Electronics Engineering Technicians | Associate's degree | 2,310 | 4 |\n| | 15-1134 | Web Developers | Associate's degree | 150 | 4 |\n| | 23-2011 | Paralegals and Legal Assistants | Associate's degree | 60 | 4 |\n| | 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 1,560 | 48,410 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 50 | 453,992 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 2,870 | 44 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 1,220 | 52,664 |\n| | 17-3023 | Electrical and Electronics Engineering Technicians | Associate's degree | 140 | 4 |\n| | 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 11,090 | 4 |\n| | 49-3023 | Automotive Service Technicians and Mechanics | Postsecondary non-degree award | 410 | 442,200 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 50 | 53,992 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 910 | 44,122 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 50 | 4 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Central Data Package" }, { "slide_number": 27, "markdown_text": "## Part III: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Central Data Package" }, { "slide_number": 28, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Central Data Package" }, { "slide_number": 29, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Central Data Package" }, { "slide_number": 30, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 4+ Stars\n\nAt the sub-BA level, a number of 4- and 5-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Central Data Package" }, { "slide_number": 31, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3 Stars\n\nAt the sub-BA level, a number of 3-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n3-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Central Data Package" }, { "slide_number": 32, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Central Data Package" }, { "slide_number": 33, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Central Data Package" }, { "slide_number": 34, "markdown_text": "## Part IV: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Central Data Package" }, { "slide_number": 35, "markdown_text": "## IV. A: Apprenticeships", "report name": "2019 Central Data Package" }, { "slide_number": 36, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 37, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Central Data Package" }, { "slide_number": 38, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 39, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn Central MA, the most popular occupations for apprentices (Electrians, Plumbers, Pipefitters, and Steamfitters, and Carpenters) are ranked 4 or 5 stars, indicating high wages and strong projected employer demand.\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|----------------|---------------|----------|\n| Electricians | 5 | 221 | 212 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 100 | 166 |\n| Carpenters | 4 | 86 | 404 |\n| Roofters | 3 | 65 | 73 |\n| Construction Laborers | 4 | 48 | 456 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 29 | 123 |\n| Electrical Power-Line Installers and Repairers | 3 | 20 | 44 |\n| First-Line Supervisors of Production and Operating Workers | 4 | 19 | 268 |\n| Sheet Metal Workers | 2 | 17 | 35 |\n| | | | |\n\nSource: Division of Apprentice Standards, 2019", "report name": "2019 Central Data Package" }, { "slide_number": 40, "markdown_text": "## IV. B: Professional Licensing", "report name": "2019 Central Data Package" }, { "slide_number": 41, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nA majority of the top occupations in Central by number of Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Central Data Package" }, { "slide_number": 42, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses greatly exceeds total employment for some occupations, such as Cosmetologists, for others, such as Mental Health Counselors, the number of jobs (1,571) outstrips the supply of licenses (732).\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|--------------------------------|---------|------------|-------------------|\n| Allied Health | 3 | 161 | 189 |\n| Occupational Therapy Assistant | 4 | 193 | 303 |\n| Physical Therapist Assistant | 5 | 387 | 741 |\n| Occupational Therapist | 5 | 416 | 846 |\n| Applied Behavior Analyst | 4 | 491 | 1,021 |\n| Physical Therapist | 5 | 732 | 1,571 |\n| Mental Health Counselor | 5 | | |\n| Cosmetology | 4 | | |\n| Cosmetologist (Hairdresser) | 4 | 3,320 | 1,179 |\n| Electricians | 5 | | |\n| Electrician | 5 | 1,880 | 1,257 |\n| Engineers And Land Surveyors | 4 | | |\n| Engineer | 4 | 941 | 3,329 |\n| Gas Filters | 4 | | |\n| Gas Fitter | 4 | | |\n| Public Accountancy | 5 | | |\n| Certified Public Accountant | 5 | | |\n| Real Estate | 3 | | |\n| Real Estate Salesperson | 3 | | |\n| Social Workers | 4 | | |\n| Social Worker, Licensed | 4 | | |\n| | | | |\n\nSelected occupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 Central Data Package" }, { "slide_number": 43, "markdown_text": "## Part V: New Data Tools", "report name": "2019 Central Data Package" }, { "slide_number": 44, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Central Data Package" }, { "slide_number": 45, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Central Data Package" }, { "slide_number": 46, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Central Data Package" }, { "slide_number": 47, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Central Data Package" }, { "slide_number": 48, "markdown_text": "## Priority and Critical Industries by Age\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 49, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 50, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 51, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 52, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 53, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 Central Data Package" }, { "slide_number": 54, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Central Data Package" }, { "slide_number": 55, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| % of Industry Employment | % of Industry Employment | % of Employment | |\n|----------------------------|----------------------------|-------------------|----|\n| 17.304 | 58.679 | 20% | |\n| 10% | 45 | 20% | |\n| 80% | 45 | 20% | |\n| 70% | 45 | 20% | |\n| 60% | 45 | 20% | |\n| 50% | 45 | 20% | |\n| 40% | 45 | 20% | |\n| 30% | 45 | 20% | |\n| 20% | 45 | 20% | |", "report name": "2019 Central Data Package" }, { "slide_number": 56, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been greater for black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 57, "markdown_text": "## Manufacturing", "report name": "2019 Central Data Package" }, { "slide_number": 58, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers are predominantly male, although since 2015 the number of female workers has grown 4 percent and makes up nearly 30% of workers.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------|----|\n| 0% | 0% | |\n| 10% | 26.094 | |\n| 90% | 10.447 | |\n| 80% | 10.0 | |\n| 70% | 70% | |\n| 60% | 60% | |\n| 50% | 50% | |\n| 40% | 40% | |\n| 30% | 30% | |\n| 20% | 20% | |\n| 10% | 10% | |\n| 0% | 0% | |", "report name": "2019 Central Data Package" }, { "slide_number": 59, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce in Central MA is slowly becoming more diverse, though the greatest share of workers are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.", "report name": "2019 Central Data Package" }, { "slide_number": 60, "markdown_text": "## Transportation and Warehousing", "report name": "2019 Central Data Package" }, { "slide_number": 61, "markdown_text": "## Transportation and Warehousing by Gender\n\nTwo-thirds of the workers in the Transportation and Warehousing sector are male, although the number of female workers has grown by 10 percent since 2015.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +7% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +10% | |", "report name": "2019 Central Data Package" }, { "slide_number": 62, "markdown_text": "## Transportation and Warehousing by Race/Ethnicity\n\nThe Transportation and Warehousing sector is predominantly white, though numbers of Black or African American, Asian and Hispanic or Latino workers are increasing since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 63, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Central Data Package" }, { "slide_number": 64, "markdown_text": "## Professional and Technical Services", "report name": "2019 Central Data Package" }, { "slide_number": 65, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nCentral MA is home to more than 2,000 establishments in the Professional and Technical Services sector, which includes computer systems design, management and technical consulting, legal, and accounting and bookkeeping services. In the last year, H&R Block had the most job postings in Central MA (169), followed by Charles River Laboratories (109) and Advantage Sales & Marketing (94).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 66, "markdown_text": "## Professional and Technical Services by Education\n\n45% of workers in Professional and Technical Services in Central MA have a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|-------|\n| 2015 | 47%, 7,516 | -1.6% | 25%, 3,999 | -1.6% | 25% | 3.936 |\n| 2018 | 6%, 900 | 1.3% | 16%, 2,590 | 1.004 | 16% | 2.59 |", "report name": "2019 Central Data Package" }, { "slide_number": 67, "markdown_text": "## Professional and Technical Services by Gender\n\nEmployment in the Professional and Technical Services sector is fairly evenly split between male and female workers.\n\n| Category | Value | |\n|------------------------------------------|---------|----|\n| Female | 0% | |\n| Male | -100 | |\n| Change in % of Employees in of Employees | -150 | |\n| Male | -3% | |\n| Female | 0% | |", "report name": "2019 Central Data Package" }, { "slide_number": 68, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 80 percent of workers in the Professional and Technical Services Sector in Central MA are white, though the numbers of Asian and Hispanic or Latino workers are growing somewhat.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 69, "markdown_text": "## Construction", "report name": "2019 Central Data Package" }, { "slide_number": 70, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments in Central MA grew by nearly 200 between 2016 and 2018, with growth across several types of contractors. In the last year, R H White Companies, Inc. was responsible for the largest number of public online job postings in the Central MA, with 48, followed by Toll Brothers, Inc. (27) and Free Building Company, Inc. (19).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 71, "markdown_text": "## Construction by Education\n\n50% of Construction workers in Central MA have some college or higher level of education.\n\n| | 100% | 15,108 | 17,128 | | | | | |\n|-----------|------------|------------|-------------------------------------------|----|-----|-----|---------------------------------------|----|\n| | 90% | 10%, 1,482 | +20.3% | | | | | |\n| | 80% | 22%, 3,375 | +10.7% | | | | | |\n| | 70% | 60% | +12.9% | | | | | |\n| Employees | 28%, 4,186 | 28%, 4,724 | Educational attainment not available (age | | 50% | 40% | High school or equivalent, no college | |\n| | 30% | 29%, 4,442 | Less than high school | | | | | |\n| | 20% | 11%, 1,623 | +11.7% | | | | | |\n| | 10% | 0% | +18.6% | | | | | |\n| | 2015 | 2018 | | | | | | |", "report name": "2019 Central Data Package" }, { "slide_number": 72, "markdown_text": "## Construction by Gender\n\nApproximately 80% of Construction workers in Central MA are male.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |", "report name": "2019 Central Data Package" }, { "slide_number": 73, "markdown_text": "## Construction by Race/Ethnicity\n\nNearly 95% of Construction workers in Central MA are white, although the share of non-white workers has grown since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n| Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018 | |\n|-------------------------------------------------------------------------|-------------------------------------------------------------------------|----|\n| +2,000 | +12% | |\n| +1,800 | +1600 | |\n| +1,600 | +1,400 | |\n| +1,200 | +1,200 | |\n| +1,000 | +1,000 | |\n| +800 | +800 | |\n| +600 | +600 | |\n| +35% | +35% | |\n| +200 | +200 | |\n| 0 | 0 | |\n| Black or African American | Asian | |\n| White | Other | |\n| Black or African American | Hispanic or Latino | |", "report name": "2019 Central Data Package" }, { "slide_number": 74, "markdown_text": "## Retail Trade", "report name": "2019 Central Data Package" }, { "slide_number": 75, "markdown_text": "## Retail Trade Groups and Employers\n\nThe number of Retail establishments in Central MA has remained fairly stable since 2016. In the last year, BJ's Wholesale Club, Inc. was responsible for the most online job postings in Central MA (587), followed by CVS Health (486).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 76, "markdown_text": "## Retail Trade by Education\n\n25% of Retail workers are less than 24 years old. Of those aged 24 or older, 54% have some college or higher level of education.\n\n| Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | Education Attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | | |\n|--------------------------------------------------------------------|-------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|------------|------------|----|\n| 23%, 8,805 | 16%, 6,182 | +1.8% | 24%, 8,961 | 24%, 9,099 | 24%, 9,099 | 24%, 9,099 | |\n| 25%, 9,215 | -1.3% | -1.3% | 24%, 9,099 | 24%, 9,099 | 24%, 9,099 | 24%, 9,099 | |\n| 10%, 3,608 | +8.2% | 10%, 3,905 | 24%, 9,099 | 24%, 9,099 | 24%, 9,099 | 24%, 9,099 | |", "report name": "2019 Central Data Package" }, { "slide_number": 77, "markdown_text": "## Retail Trade by Gender\n\nEmployment in the Retail Trade sector is fairly evenly split between male and female workers.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Male | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Female | |", "report name": "2019 Central Data Package" }, { "slide_number": 78, "markdown_text": "## Retail Trade by Race/Ethnicity\n\nMore than 85% of Retail Trade workers in Central MA are white. There has been some growth in the number of Hispanic or Latino, Black or African American, and Asian workers since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n| Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018 | |\n|-------------------------------------------------------------------------|-------------------------------------------------------------------------|----|\n| +600 | +20% | |\n| +17% | +400 | |\n| +18% | +600 | |\n| +16% | +400 | |\n| +20% | +200 | |", "report name": "2019 Central Data Package" }, { "slide_number": 79, "markdown_text": "## Hospitality", "report name": "2019 Central Data Package" }, { "slide_number": 80, "markdown_text": "## Hospitality Groups and Employers\n\nThe number of Hospitality-related establishments in Central MA grew slightly between 2016 and 2018. In the last year, Chipotle Mexican Grill was responsible for the most online job postings in the region (155), followed by Sodexo (148) and Great Wolf Resorts (109).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 81, "markdown_text": "## Hospitality by Education\n\n36% of Hospitality workers are less than 24 years old. Of those aged 24 or older, 49% have a high school diploma or less.\n\n| | 26,623 | 26,623 | 28,315 | 28,315 | | | | | | |\n|----|------------|------------|-------------|-------------------------------------------|----|-----|------------|-------|---------------------------------------|----|\n| | 37%, 9,882 | 37%, 9,882 | 36%, 10,225 | 36%, 10,225 | | | | | | |\n| 0% | 13%, 3,448 | +13.3% | 14%, 3,907 | Educational attainment not available (age | | 40% | 19%, 5,050 | +6.6% | High school or equivalent, no college | |\n| | 30% | 20%, 5,287 | +4.7% | Less than high school | | | | | | |\n| | 10% | 11%, 2,956 | +10.6% | 12%, 3,269 | | | | | | |\n| | 0% | 2015 | 2018 | | | | | | | |", "report name": "2019 Central Data Package" }, { "slide_number": 82, "markdown_text": "## Hospitality by Gender\n\nEmployment in the Retail Trade sector is fairly evenly split between male and female workers.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +600 | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +600 | |\n| Male | +600 | |\n| Female | +7% | |", "report name": "2019 Central Data Package" }, { "slide_number": 83, "markdown_text": "## Hospitality by Race/Ethnicity\n\nMore than 80% of Hospitality workers in Central MA are white. There has been some growth in the number of Black or African American, Asian, and Hispanic or Latino workers since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 84, "markdown_text": "## Educational Services", "report name": "2019 Central Data Package" }, { "slide_number": 85, "markdown_text": "## Educational Services Groups and Employers\n\nThe number of Educational Services establishments in Central MA remained stable between 2016 and 2018. Over the last 12 months, the employer with the most online job postings in the region was UMass Medical School, with 1,070.\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 86, "markdown_text": "## Educational Services by Education\n\n53% of workers in the Educational Services sector in Central MA have at least some college education.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|----|\n| 2015 | 28% | 27% | 10,326 | 13%, 4,716 | 12% | |\n| 2018 | 28% | 27% | 10,014 | 13%, 4,716 | 12% | |", "report name": "2019 Central Data Package" }, { "slide_number": 87, "markdown_text": "## Educational Services by Gender\n\nMore than 60% of Educational Services workers are female.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 88, "markdown_text": "## Educational Services by Race/Ethnicity\n\nMore than 90% of Educational Services workers are white, although the share of Black or African American, Asian, and Hispanic or Latino workers in the sector has increased since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Central Data Package" }, { "slide_number": 89, "markdown_text": "## Appendix: Professional Licensing", "report name": "2019 Central Data Package" }, { "slide_number": 90, "markdown_text": "## Regional Occupation Demand and DPL Licensing: Deep Dive\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|----------------------------------------------|---------|------------|-------------------|\n| Allied Health Occupational Therapy Assistant | 3 | 161 | 189 |\n| Physical Therapist Assistant | 4 | 193 | 303 |\n| Occupational Therapist | 5 | 387 | 741 |\n| Applied Behavior Analyst | 4 | 416 | 846 |\n| Physical Therapist | 5 | 491 | 1,021 |\n| Mental Health Counselor | 5 | 732 | 1,571 |\n| Educational Psychologist | 4 | 179 | 604 |\n| Cosmetology | 4 | 3,320 | 1,179 |\n| Cosmetologist (Hairdresser) | 4 | 3,320 | 1,179 |\n| Electricians | 5 | 1,880 | 1,257 |\n| Electrician | 5 | 1,880 | 1,257 |\n| Engineers And Land Surveyors | 4 | 941 | 3,329 |\n| Engineer* | 4 | 941 | 3,329 |\n| Gas Fitters | 4 | 1,679 | 1,039 |\n| Gas Filter | 4 | 1,679 | 1,039 |\n| Public Accountancy | 5 | 617 | 2,406 |\n| Certified Public Accountant | 5 | 617 | 2,406 |\n| Real Estate | 3 | 3,578 | 294 |\n| Real Estate Salesperson | 3 | 3,578 | 294 |\n| Social Workers | 4 | 1,289 | 3,633 |\n| Social Worker, Licensed* | 4 | 1,289 | 3,633 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019;\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Central Data Package" }, { "slide_number": 91, "markdown_text": "## Glossary", "report name": "2019 Central Data Package" }, { "slide_number": 92, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Central Data Package" }, { "slide_number": 93, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Central Data Package" }, { "slide_number": 94, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Central Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Massachusetts 2019 Data Package\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 State Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives for Regions\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 State Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I. Industry Overview and Profiles\n\nA: Sector Makeup by Employment and Wages\n\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part II: Supply Gap Analysis\n\n- i. Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part III: Workforce Supply Analysis\n\nA: Apprenticeships\n\n- B: Professional Licensing\n\n## Part IV: New Data Tools\n\n## Appendix\n\nA: Regional Context\n\nB: Worker Characteristics\n\nC: Priority Industry Profiles\n\nD: Professional Licensing\n\n## Glossary", "report name": "2019 State Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 State Data Package" }, { "slide_number": 5, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 State Data Package" }, { "slide_number": 6, "markdown_text": "## I.A: Industry Overview", "report name": "2019 State Data Package" }, { "slide_number": 7, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry by employment in Massachusetts, employing around 300,000 more persons than the next largest industries, Retail Trade, Professional and Technical Services, and Accommodation and Food Services.\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 0 | |\n| Retail Trade | 100 | |\n| Professional | 100 | |\n| Accommodation | 100 | |\n| Educational | 100 | |\n| Manufacturing | 100 | |\n| Administrative | 100 | |\n| Construction | 100 | |\n| Finance and | 100 | |\n| Purchased | 100 | |\n| Wholesale | 100 | |\n| Other Services | 100 | |\n| Transportation | 100 | |\n| Information | 100 | |\n| Arts | 100 | |\n| Management | 100 | |\n| Agriculture | 100 | |\n| Mining | 100 | |", "report name": "2019 State Data Package" }, { "slide_number": 8, "markdown_text": "## Sector Makeup by Total Wages\n\nProfessional and Technical services paid the highest total wages in Massachusetts, followed by Healthcare and Social Assistance.\n\n| Category | Value | |\n|-----------------|---------|----|\n| Professional | $12 | |\n| Health Care | $5.2 B | |\n| Finance | $5.1 B | |\n| Education | $5.1 B | |\n| Manufacturing | $5.3 B | |\n| Construction | $5.1 B | |\n| Retail Trade | $5.1 B | |\n| Wholesale Trade | $5.1 B | |\n| Information | $5.1 B | |\n| Public | $5.1 B | |\n| Administrative | $5.1 B | |\n| Management | $5.1 B | |\n| Transportation | $5.1 B | |\n| Other Services | $5.1 B | |\n| Real Estate | $5.1 B | |\n| Agriculture | $5.1 B | |\n| Mining | $5.1 B | |", "report name": "2019 State Data Package" }, { "slide_number": 9, "markdown_text": "## I.B: Industry Profiles", "report name": "2019 State Data Package" }, { "slide_number": 10, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 State Data Package" }, { "slide_number": 11, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nMore than 7,000 Health Care and Social Assistance establishments were added in Massachusetts between 2016 and 2018, driven primarily by the increase in Individual and Family Services. Over the last 12 months, Partners Healthcare posted the most jobs in the state, with 12,222.\n\n", "report name": "2019 State Data Package" }, { "slide_number": 12, "markdown_text": "## Healthcare and Social Assistance by Education\n\n61% of Healthcare and Social Assistance workers in Massachusetts have some college or higher level of education.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | |\n|-------------|--------------------------------------------------------------------|--------------|\n| 100% | 606,745 | 638,386 |\n| 9% , 53,440 | -2.9% | 9%, 54,983 |\n| 80% | -0.0% | 32%, 203,738 |\n| 70% | 34%, 203,800 | 4.3% |\n| 60% | +4.3% | 29%, 187,912 |\n| 50% | 30%, 180,108 | 29%, 187,912 |\n| 30% | +10.0% | 20%, 126,933 |\n| 20% | 19%, 115,388 | +20.0% |\n| 10% | 9%, 54,009 | 10%, 64,820 |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 State Data Package" }, { "slide_number": 13, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| % of Industry Employment | % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----------------------------|----|\n| 148,329 | 490,056 | 20% | |\n| 10% | 50% | 30% | |\n| 0% | 10% | 20% | |\n\n| % of Industry Employment | % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----------------------------|----|\n| +5,000 | +4% | +5% | |\n| +25,000 | +20,000 | +25% | |\n| +15,000 | +10,000 | +15% | |\n| +5,000 | +5,000 | +5% | |\n| +4,000 | +4,000 | +4% | |\n| Male | Female | Male | |", "report name": "2019 State Data Package" }, { "slide_number": 14, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been increasing for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nPercent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 State Data Package" }, { "slide_number": 15, "markdown_text": "## Manufacturing", "report name": "2019 State Data Package" }, { "slide_number": 16, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of Manufacturing establishments in Massachusetts declined slightly between 2016 and 2018. In the last year, Takeda Pharmaceuticals was the employer with the highest number of job postings in Massachusetts (3,033), followed by Raytheon (2,879).\n\n", "report name": "2019 State Data Package" }, { "slide_number": 17, "markdown_text": "## Manufacturing by Education\n\n36% of Manufacturing workers in Massachusetts have a high school diploma or less. 27% of workers in Manufacturing have some college or an Associate Degree and 30% have a Bachelor's degree or higher. This educational attainment mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | % of Employees | |\n|--------|------------------|----|\n| 2015 | 31% | |\n| 2018 | 6% | |\n| 2017 | 4% | |\n| 2016 | 2% | |\n| 2015 | 1% | |", "report name": "2019 State Data Package" }, { "slide_number": 18, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in Massachusetts are still predominantly male, although the share of female workers has increased since 2015.\n\n| Category | Value | |\n|--------------------------|---------|----|\n| Female | -3% | |\n| Male | -3% | |\n| Change in # of Employees | -3% | |", "report name": "2019 State Data Package" }, { "slide_number": 19, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nMore than 80% of Manufacturing workers in Massachusetts are white. However, the share of Manufacturing workers who identify as Black or African American, Asian, or Hispanic or Latino has increased since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 State Data Package" }, { "slide_number": 20, "markdown_text": "## Professional and Technical Services", "report name": "2019 State Data Package" }, { "slide_number": 21, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nMassachusetts is home to more than 33,000 establishments in the Professional and Technical Services sector, which includes legal, architectural and engineering, management and technical consulting, and computer systems design and related services. Over the last 12 months, IBM posted the most jobs (2,700), followed by Deloitte (2,563) and Dana Farber Cancer Institute (2,084).\n\n", "report name": "2019 State Data Package" }, { "slide_number": 22, "markdown_text": "## Professional and Technical Services by Education\n\nNearly 50% of workers in the Professional and Technical Services sector have a Bachelor's degree or higher, and an additional 23% have some college or an Associate degree.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|--------|----|\n| 2015 | 6% | 14% | 16% | 30.6% | 21.221 | |\n| 2018 | 4% | 22% | 65.210 | 12.3% | 23% | |", "report name": "2019 State Data Package" }, { "slide_number": 23, "markdown_text": "## Professional and Technical Services by Gender\n\nEmployment in the Professional and Technical Services sector is fairly evenly split between male and female workers.\n\n| Category | Value | |\n|-----------------------------------------------------|---------|----|\n| Female | 100% | |\n| Male | 90% | |\n| Change in of Industry Employment, Q2 2018 | 143,636 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 16,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 15,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 14,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 11% | |", "report name": "2019 State Data Package" }, { "slide_number": 24, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 80% of workers in the Professional and Technical Services sector in Massachusetts are white, although Asian workers make up the fastest-growing segment of the industry workforce.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 State Data Package" }, { "slide_number": 25, "markdown_text": "## Construction", "report name": "2019 State Data Package" }, { "slide_number": 26, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments in Massachusetts increased slightly between 2016 and 2018. Over the last year, Roto Roooter was responsible for the greatest number of online job postings related to Construction in Massachusetts.\n\n", "report name": "2019 State Data Package" }, { "slide_number": 27, "markdown_text": "## Construction by Education\n\nConstruction workers in Massachusetts come from a variety of educational backgrounds, with about 28% having a high school diploma or equivalent, 28% having some college or an Associate degree and 23% having a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | 141,414 | 141,414 | 163,593 | 163,593 | | | | | | |\n|----------------|-------------|-------------|-------------|-------------------------------------------|----|----|----|----|--------------------------------------|----|\n| | 9%, 12,227 | +23.0% | 9%, 15,037 | | | | | | | |\n| | 24%, 33,684 | +12.8% | 23%, 38,011 | | | | | | | |\n| % of Employees | 60% | 28%, 39,594 | +14.8% | 28%, 45,466 | | | | | | |\n| | | | | Educational attainment not available (age | | | | | Bachelor's degree or advanced degree | |\n| | | | | Some college or Associate degree | | | | | | |\n| | | | | High school or equivalent, no college | | | | | | |\n| | | | | Less than high school | | | | | | |\n| | | | | 28%, 45,413 | | | | | | |\n| | | | | 20% | | | | | | |\n| | | | | 10% | | | | | | |\n| | | | | 11% , 15,975 | | | | | | |\n| | | | | +23.1% | | | | | | |\n| | | | | 2018 | | | | | | |\n| | | | | | | | | | | |\n| | | | | | | | | | | |", "report name": "2019 State Data Package" }, { "slide_number": 28, "markdown_text": "## Construction by Gender\n\nMore than 80% of Construction workers in Massachusetts are male.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 State Data Package" }, { "slide_number": 29, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 90% of Construction workers in Massachusetts are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n## Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 State Data Package" }, { "slide_number": 30, "markdown_text": "## Occupations", "report name": "2019 State Data Package" }, { "slide_number": 31, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 State Data Package" }, { "slide_number": 32, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries", "report name": "2019 State Data Package" }, { "slide_number": 33, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4-Stars\n\n| | Industry | Occupation Title | Industry-Specific | All Industries | |\n|----------|------------|---------------------------------------------------------|---------------------------------|------------------|------|\n| Industry | SOC Code | Occupation Title | Educational Requirement | 2018 Industry | STAR |\n| | 29-1021 | Dentists, General | Doctoral or professional degree | 3,140 | 4 |\n| | 29-1062 | Family and General Practitioners | Doctoral or professional degree | 2,470 | 4 |\n| | 19-3031 | Clinical, Counseling, and School Psychologists | Doctoral or professional degree | 1,930 | 4 |\n| | 29-1065 | Pediatricians, General | Doctoral or professional degree | 1,550 | 4 |\n| | 29-1041 | Optometrists | Doctoral or professional degree | 1,060 | 4 |\n| | 29-1066 | Psychiatrists | Doctoral or professional degree | 830 | 4 |\n| | 21-1022 | Healthcare Social Workers | Master's degree | 5,340 | 61 |\n| | 29-1151 | Nurse Anesthetists | Master's degree | 810 | 4 |\n| | 25-9031 | Instructional Coordinators | Master's degree | 430 | 74 |\n| | 25-1072 | Nursing Instructors and Teachers, Postsecondary | Master's degree | 120 | 4 |\n| | 25-4021 | Librarians | Master's degree | 50 | 68 |\n| | 21-1021 | Child, Family, and School Social Workers | Bachelor's degree | 4,860 | 43 |\n| | 11-9151 | Social and Community Service Managers | Bachelor's degree | 4,810 | 65 |\n| | 13-1151 | Training and Development Specialists | Bachelor's degree | 1,680 | 68 |\n| | 19-4021 | Biological Technicians | Bachelor's degree | 1,630 | 51 |\n| | 29-1031 | Dietitians and Nutritionists | Bachelor's degree | 1,620 | 64 |\n| | 13-1131 | Fundraisers | Bachelor's degree | 790 | 4 |\n| | 27-3031 | Public Relations Specialists | Bachelor's degree | 610 | 62 |\n| | 13-1041 | Compliance Officers | Bachelor's degree | 570 | 77 |\n| | 13-1141 | Compensation, Benefits, and Job Analysis Specialists | Bachelor's degree | 180 | 4 |\n| | 13-2031 | Budget Analysts | Bachelor's degree | 180 | 4 |\n| | 11-3131 | Training and Development Managers | Bachelor's degree | 160 | 117 |\n| | 15-1131 | Computer Programmers | Bachelor's degree | 150 | 4 |\n| | 13-1121 | Meeting, Convention, and Event Planners | Bachelor's degree | 110 | 52 |\n| | 29-9011 | Occupational Health and Safety Specialists | Bachelor's degree | 100 | 4 |\n| | 25-2054 | Special Education Teachers, Secondary School | Bachelor's degree | 90 | 74 |\n| | 25-2052 | Special Education Teachers, Kindergarten and Elementary | Bachelor's degree | 80 | 72 |\n| | 11-3111 | Compensation and Benefits Managers | Bachelor's degree | 80 | 117 |\n| | 11-3061 | Purchasing Managers | Bachelor's degree | 60 | 4 |\n| | 27-1024 | Graphic Designers | Bachelor's degree | 50 | 60 |\n\nAll occupations listed are 4-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 34, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4-Stars\n\n| Industry | SOC Code | Occupation Title | Industry-Specific | All Industries |\n|------------|------------------------------------------------------|---------------------------------|---------------------|------------------|\n| 19-1021 | Biochemists and Biophysicists | Educational Requirement | 2018 Industry | STAR |\n| 17-2072 | Electronics Engineers, Except Computer | Doctoral or professional degree | 490 | $101,550 |\n| 19-2031 | Chemists | Bachelor's degree | 1,330 | 4 |\n| 11-3061 | Purchasing Managers | Bachelor's degree | 1,140 | $87,240 |\n| 27-1024 | Graphic Designers | Bachelor's degree | 920 | $121,980 |\n| 41-9031 | Sales Engineers | Bachelor's degree | 850 | $60,530 |\n| 13-1051 | Cost Estimators | Bachelor's degree | 660 | $96,260 |\n| 13-1041 | Compliance Officers | Bachelor's degree | 620 | $72,520 |\n| 13-1081 | Logisticians | Bachelor's degree | 550 | $75,220 |\n| 19-4021 | Biological Technicians | Bachelor's degree | 420 | $51,290 |\n| 17-2031 | Biomedical Engineers | Bachelor's degree | 420 | $94,640 |\n| 17-2061 | Computer Hardware Engineers | Bachelor's degree | 370 | $120,860 |\n| 17-2041 | Chemical Engineers | Bachelor's degree | 360 | $95,690 |\n| 15-1131 | Computer Programmers | Bachelor's degree | 340 | $92,200 |\n| 13-1151 | Training and Development Specialists | Bachelor's degree | 330 | $68,470 |\n| 27-3042 | Technical Writers | Bachelor's degree | 300 | $84,340 |\n| 27-3031 | Public Relations Specialists | Bachelor's degree | 300 | $62,290 |\n| 13-2031 | Budget Analysts | Bachelor's degree | 230 | $83,240 |\n| 29-9011 | Occupational Health and Safety Specialists | Bachelor's degree | 230 | $82,440 |\n| 27-1011 | Art Directors | Bachelor's degree | 120 | $90,910 |\n| 13-1141 | Compensation, Benefits, and Job Analysis Specialists | Bachelor's degree | 110 | $70,940 |\n| 13-1121 | Meeting, Convention, and Event Planners | Bachelor's degree | 90 | $52,480 |\n| 11-3131 | Training and Development Managers | Bachelor's degree | 70 | $117,330 |\n| 13-2041 | Credit Analysts | Bachelor's degree | 60 | $76,220 |\n| 11-3111 | Compensation and Benefits Managers | Bachelor's degree | 50 | $117,930 |\n\nAll occupations listed are 4-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 35, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4-Stars\n\n| | Industry | Occupation Title | Industry-Specific | All Industries | |\n|------------------|-------------------------------|------------------------------------------------------|---------------------------------|------------------|----------|\n| Industry | SOC Code | Occupation Title | Educational Requirement | 2018 Industry | STAR |\n| 19-1021 | Biochemists and Biophysicists | Doctoral or professional degree | 3,890 | 4 | $101,550 |\n| 19-1021 | 29-1131 | Veterinarians | Doctoral or professional degree | 1,320 | 4 |\n| 19-1021 | 21-1022 | Healthcare Social Workers | Master's degree | 340 | 4 |\n| 19-1021 | 17-1011 | Architects, Except Landscape and Naval | Bachelor's degree | 3,040 | 4 |\n| 19-1021 | 19-4021 | Biological Technicians | Bachelor's degree | 2,340 | 4 |\n| 19-1021 | 27-1024 | Graphic Designers | Bachelor's degree | 2,130 | 4 |\n| 19-1021 | 27-3031 | Public Relations Specialists | Bachelor's degree | 2,090 | 662,290 |\n| 19-1021 | 15-1131 | Computer Programmers | Bachelor's degree | 1,810 | 4 |\n| 19-1021 | 41-9031 | Sales Engineers | Bachelor's degree | 1,630 | 4 |\n| 19-1021 | 17-2081 | Environmental Engineers | Bachelor's degree | 1,450 | 84,920 |\n| 19-1021 | 19-2031 | Chemists | Bachelor's degree | 1,400 | 87,240 |\n| 19-1021 | 17-207 | Electronics Engineers, Except Computer | Bachelor's degree | 1,320 | $116,580 |\n| 19-1021 | 19-2041 | Environmental Scientists and Specialists | Bachelor's degree | 1,270 | $77,280 |\n| 19-1021 | 13-1151 | Training and Development Specialists | Bachelor's degree | 1,150 | $68,470 |\n| Professional and | 13-1041 | Compliance Officers | Bachelor's degree | 1,080 | $77,990 |\n| Professional and | 17-2031 | Biomedical Engineers | Bachelor's degree | 1,020 | $94,640 |\n| Professional and | 27-3042 | Technical Writers | Bachelor's degree | 980 | $84,340 |\n| Professional and | 17-2061 | Computer Hardware Engineers | Bachelor's degree | 740 | $120,860 |\n| Professional and | 27-3043 | Writers and Authors | Bachelor's degree | 630 | $64,380 |\n| Professional and | 27-1011 | Art Directors | Bachelor's degree | 630 | $90,910 |\n| Professional and | 27-2012 | Producers and Directors | Bachelor's degree | 560 | $61,810 |\n| Professional and | 11-3061 | Purchasing Managers | Bachelor's degree | 440 | $121,980 |\n| Professional and | 11-2011 | Advertising and Promotions Managers | Bachelor's degree | 420 | $121,770 |\n| Professional and | 13-1121 | Meeting, Convention, and Event Planners | Bachelor's degree | 410 | $52,480 |\n| Professional and | 11-3131 | Training and Development Managers | Bachelor's degree | 380 | $117,330 |\n| Professional and | 13-1081 | Logisticians | Bachelor's degree | 380 | $75,220 |\n| Professional and | 13-2031 | Budget Analysts | Bachelor's degree | 310 | $83,240 |\n| Professional and | 13-1141 | Compensation, Benefits, and Job Analysis Specialists | Bachelor's degree | 290 | $70,940 |\n| Professional and | 17-2041 | Chemical Engineers | Bachelor's degree | 280 | $95,690 |\n| Professional and | 13-1131 | Fundraisers | Bachelor's degree | 260 | $59,950 |\n\nAll occupations listed are 4-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 36, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 5-Stars\n\n| Industry | SOC Code | Occupation Title | Industry-Specific | All Industries |\n|------------|----------------------------------------------------------|---------------------------------|---------------------|------------------|\n| 29-1123 | Physical Therapists | Educational Requirement | 2018 Industry | STAR |\n| 19-1042 | Medical Scientists, Except Epidemiologists | Doctoral or professional degree | 7,390 | 5 |\n| 29-1051 | Pharmacists | Doctoral or professional degree | 5,220 | 5 |\n| 23-1011 | Lawyers | Doctoral or professional degree | 2,410 | 5 |\n| 29-1171 | Nurse Practitioners | Master's degree | 140 | 5 |\n| 29-1071 | Physician Assistants | Master's degree | 3,620 | 5 |\n| 29-1122 | Occupational Therapists | Master's degree | 3,530 | 5 |\n| 29-1127 | Speech-Language Pathologists | Master's degree | 2,120 | 5 |\n| 21-1012 | Educational, Guidance, School, and Vocational Counselors | Master's degree | 940 | 5 |\n| 15-2041 | Statisticians | Master's degree | 320 | 5 |\n| 29-1141 | Registered Nurses | Bachelor's degree | 70,340 | 5 |\n| 11-9111 | Medical and Health Services Managers | Bachelor's degree | 11,020 | 5 |\n| 11-1021 | General and Operations Managers | Bachelor's degree | 3,470 | 5 |\n| 13-1071 | Human Resources Specialists | Bachelor's degree | 1,710 | 5 |\n| 11-3011 | Administrative Services Managers | Bachelor's degree | 1,610 | 5 |\n| 13-2011 | Accountants and Auditors | Bachelor's degree | 1,540 | 5 |\n| 11-3031 | Financial Managers | Bachelor's degree | 1,360 | 5 |\n| 15-1121 | Computer Systems Analysts | Bachelor's degree | 860 | 5 |\n| 15-1132 | Software Developers, Applications | Bachelor's degree | 750 | 5 |\n| 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 620 | 5 |\n| 15-1142 | Network and Computer Systems Administrators | Bachelor's degree | 620 | 5 |\n| 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 590 | 5 |\n| 11-2031 | Public Relations and Fundraising Managers | Bachelor's degree | 520 | 5 |\n| 11-3121 | Human Resources Managers | Bachelor's degree | 490 | 5 |\n| 13-1111 | Management Analysts | Bachelor's degree | 430 | 5 |\n| 11-2021 | Marketing Managers | Bachelor's degree | 430 | 5 |\n| 13-2051 | Financial Analysts | Bachelor's degree | 410 | 5 |\n| 15-1141 | Database Administrators | Bachelor's degree | 220 | 5 |\n| 11-9121 | Natural Sciences Managers | Bachelor's degree | 160 | 5 |\n| 15-1122 | Information Security Analysts | Bachelor's degree | 140 | 5 |\n\nAll occupations listed are 5-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 37, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 5-Stars\n\n| | Industry | Occupation Title | Industry-Specific | All Industries |\n|----------|------------|----------------------------------------------------|---------------------------------|------------------|\n| Industry | SOC Code | Occupation Title | Educational Requirement | STAR |\n| | 19-1042 | Medical Scientists, Except Epidemiologists | Doctoral or professional degree | 410 |\n| | 23-1011 | Lawyers | Doctoral or professional degree | 330 |\n| | 15-2041 | Statisticians | Master's degree | 120 |\n| | 17-2112 | Industrial Engineers | Bachelor's degree | 6,440 |\n| | 11-1021 | General and Operations Managers | Bachelor's degree | 6,380 |\n| | 17-2141 | Mechanical Engineers | Bachelor's degree | 4,470 |\n| | 15-1133 | Software Developers, Systems Software | Bachelor's degree | 3,860 |\n| | 11-3051 | Industrial Production Managers | Bachelor's degree | 3,360 |\n| | 17-2071 | Electrical Engineers | Bachelor's degree | 3,070 |\n| | 11-9041 | Architectural and Engineering Managers | Bachelor's degree | 2,840 |\n| | 41-4011 | Sales Representatives, Wholesale and Manufacturing | Bachelor's degree | 2,720 |\n| | 13-2011 | Accountants and Auditors | Bachelor's degree | 2,090 |\n| | 11-3031 | Financial Managers | Bachelor's degree | 2,020 |\n| | 11-2022 | Sales Managers | Bachelor's degree | 1,990 |\n| | 11-2021 | Marketing Managers | Bachelor's degree | 1,670 |\n| | 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 1,310 |\n| | 15-1132 | Software Developers, Applications | Bachelor's degree | 1,300 |\n| | 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 1,240 |\n| | 15-1121 | Computer Systems Analysts | Bachelor's degree | 1,080 |\n| | 11-3011 | Administrative Services Managers | Bachelor's degree | 850 |\n| | 13-1071 | Human Resources Specialists | Bachelor's degree | 840 |\n| | 15-1142 | Network and Computer Systems Administrators | Bachelor's degree | 720 |\n| | 11-3121 | Human Resources Managers | Bachelor's degree | 690 |\n| | 13-2051 | Financial Analysts | Bachelor's degree | 640 |\n| | 13-1111 | Management Analysts | Bachelor's degree | 400 |\n| | 11-9121 | Natural Sciences Managers | Bachelor's degree | 390 |\n| | 15-1143 | Computer Network Architects | Bachelor's degree | 190 |\n| | 15-1122 | Information Security Analysts | Bachelor's degree | 190 |\n| | 15-1141 | Database Administrators | Bachelor's degree | 170 |\n| | 11-2031 | Public Relations and Fundraising Managers | Bachelor's degree | 150 |\n\nAll occupations listed are 5-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 38, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 5-Stars\n\n| Industry | SOC Code | Occupation Title | Industry-Specific | All Industries |\n|------------|----------------------------------------------------|---------------------------------|---------------------|------------------|\n| 19-1042 | Lawyers | Educational Requirement | 2018 Industry | STAR |\n| 15-2041 | Medical Scientists, Except Epidemiologists | Doctoral or professional degree | 12,980 | 5 |\n| 15-1132 | Statisticians | Master's degree | 1,910 | 5 |\n| 11-1021 | Software Developers, Applications | Bachelor's degree | 12,890 | 5 |\n| 13-2011 | General and Operations Managers | Bachelor's degree | 12,540 | 5 |\n| 13-1111 | Accountants and Auditors | Bachelor's degree | 12,100 | 5 |\n| 15-1133 | Management Analysts | Bachelor's degree | 11,670 | 5 |\n| 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 6,480 | 5 |\n| 11-3031 | Financial Managers | Bachelor's degree | 6,130 | 5 |\n| 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 5,940 | 67,920 |\n| 41-4011 | Sales Representatives, Wholesale and Manufacturing | Bachelor's degree | 5,080 | 83,590 |\n| 15-1121 | Computer Systems Analysts | Bachelor's degree | 4,880 | 91,510 |\n| 17-2051 | Civil Engineers | Bachelor's degree | 4,500 | 588,780 |\n| 11-2021 | Marketing Managers | Bachelor's degree | 4,100 | 132,210 |\n| 17-2141 | Mechanical Engineers | Bachelor's degree | 3,660 | 93,630 |\n| 11-2022 | Sales Managers | Bachelor's degree | 3,590 | 5 |\n| 13-1071 | Human Resources Specialists | Bachelor's degree | 3,550 | 68,110 |\n| 11-9041 | Architectural and Engineering Managers | Bachelor's degree | 3,310 | 149,740 |\n| 15-1143 | Computer Network Architects | Bachelor's degree | 3,210 | 5 |\n| 11-9121 | Natural Sciences Managers | Bachelor's degree | 2,960 | 164,590 |\n| 17-2071 | Electrical Engineers | Bachelor's degree | 2,810 | 5 |\n| 13-2051 | Financial Analysts | Bachelor's degree | 2,800 | 87,060 |\n| 11-9111 | Medical and Health Services Managers | Bachelor's degree | 2,250 | 5 |\n| 11-3011 | Administrative Services Managers | Bachelor's degree | 2,130 | 5 |\n| 15-1142 | Network and Computer Systems Administrators | Bachelor's degree | 2,090 | 586,770 |\n| 17-2112 | Industrial Engineers | Bachelor's degree | 1,680 | 98,280 |\n| 11-3121 | Human Resources Managers | Bachelor's degree | 1,360 | 5 |\n| 15-1122 | Information Security Analysts | Bachelor's degree | 1,300 | 5 |\n| 11-2031 | Public Relations and Fundraising Managers | Bachelor's degree | 1,030 | 5 |\n\nAll occupations listed are 5-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 39, "markdown_text": "## BA+ Occupations Associated with Priority Industries, 4+ Stars\n\n| Industry | SOC Code | Occupation Title | Industry-Specific | All Industries | |\n|--------------|------------|----------------------------------------------------|-------------------------|------------------|----------|\n| | 11-9021 | Construction Managers | Educational Requirement | 2018 Industry | STAR |\n| | 11-1021 | General and Operations Managers | Bachelor's degree | 5,380 | 5 |\n| | 13-1051 | Cost Estimators | Bachelor's degree | 3,720 | 4 |\n| | 13-2011 | Accountants and Auditors | Bachelor's degree | 890 | 5 |\n| | 17-2051 | Civil Engineers | Bachelor's degree | 850 | 5 |\n| | 11-3031 | Financial Managers | Bachelor's degree | 600 | 5 |\n| | 41-4011 | Sales Representatives, Wholesale and Manufacturing | Bachelor's degree | 370 | 88,590 |\n| | 11-2022 | Sales Managers | Bachelor's degree | 250 | 5 |\n| | 11-3011 | Administrative Services Managers | Bachelor's degree | 200 | 101,250 |\n| Construction | 13-1071 | Human Resources Specialists | Bachelor's degree | 190 | 568,110 |\n| | 13-1161 | Market Research Analysts and Marketing Specialists | Bachelor's degree | 140 | 567,920 |\n| | 17-2112 | Industrial Engineers | Bachelor's degree | 140 | 598,280 |\n| | 17-2141 | Mechanical Engineers | Bachelor's degree | 130 | 93,630 |\n| | 29-9011 | Occupational Health and Safety Specialists | Bachelor's degree | 130 | 82,440 |\n| | 11-2021 | Marketing Managers | Bachelor's degree | 110 | 532,210 |\n| | 11-3021 | Computer and Information Systems Managers | Bachelor's degree | 110 | 5147,030 |\n| | 11-3121 | Human Resources Managers | Bachelor's degree | 90 | 5123,750 |\n| | 13-1041 | Compliance Officers | Bachelor's degree | 60 | 477,990 |\n| | 17-1011 | Architects, Except Landscape and Naval | Bachelor's degree | 60 | 93,920 |\n\nAll occupations listed are 4- or 5-star occupations requiring a Bachelor's degree or higher. Top occupations determined by statewide industry employment.", "report name": "2019 State Data Package" }, { "slide_number": 40, "markdown_text": "## Part II: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 State Data Package" }, { "slide_number": 41, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 State Data Package" }, { "slide_number": 42, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 State Data Package" }, { "slide_number": 43, "markdown_text": "## More Openings than Qualified: State Sub-BA Occupations\n\nAt the sub-BA level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.", "report name": "2019 State Data Package" }, { "slide_number": 44, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 State Data Package" }, { "slide_number": 45, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.", "report name": "2019 State Data Package" }, { "slide_number": 46, "markdown_text": "## Part III: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 State Data Package" }, { "slide_number": 47, "markdown_text": "## III. A: Apprenticeships", "report name": "2019 State Data Package" }, { "slide_number": 48, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 State Data Package" }, { "slide_number": 49, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 State Data Package" }, { "slide_number": 50, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 State Data Package" }, { "slide_number": 51, "markdown_text": "## State Occupation Demand and Supply of Apprentices\n\nAcross the state, the most popular occupations for apprentices (Electricians, Carpenters, Plumbers, Pipefitters, and Steamfitters, and Construction Laborers) are ranked 4 or 5 stars, indicating high wages and strong projected employer demand.\n\nSource: Division of Apprentice Standards, 2019\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-------------------------------------------------------------------------------|----------------|---------------|----------|\n| Electricians | 5 | 1,951 | 2,805 |\n| Carpenters | 4 | 1,311 | 3,761 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 1,023 | 2,328 |\n| Construction Laborers | 4 | 636 | 3,974 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 417 | 1,463 |\n| Structural Iron and Steel Workers | 4 | 411 | 101 |\n| Sheet Metal Workers | 4 | 407 | 559 |\n| Elevator Installers and Repairers | 4 | 378 | 78 |\n| Opticians, Dispensing | 3 | 249 | 143 |\n| Roofers | 3 | 226 | 250 |\n| Police and Sheriff's Patrol Officers | 4 | 140 | 1,986 |\n| Telecommunications Equipment Installers and Repairers, Except Line Installers | 3 | 128 | 501 |\n| Painting, Coating, and Decorating Workers | 2 | 125 | 43 |\n| Brickmasons and Blockmasons | 3 | 124 | 181 |\n| Glaziers | 3 | 120 | 123 |\n| Firefighters | 3 | 101 | 1,053 |\n| | | | |", "report name": "2019 State Data Package" }, { "slide_number": 52, "markdown_text": "## III. B: Professional Licensing", "report name": "2019 State Data Package" }, { "slide_number": 53, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nA majority of the top occupations by number of associated Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nNot inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 State Data Package" }, { "slide_number": 54, "markdown_text": "## Occupation Demand and DPL Professional Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses greatly exceeds total employment for some occupations, such as Real Estate Sales Persons, for others, such as Physical Therapists, the number of jobs (9,429) outstrips the supply of licenses (4,482).\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|---------|------------|-------------------|\n| Allied Health | 5 | 5,028 | 7,556 |\n| Mental Health Counselor | 5 | 5,028 | 5,536 |\n| Occupational Therapist | 5 | 3,020 | 5,536 |\n| Educational Psychologist | 4 | 2,614 | 5,305 |\n| Applied Behavior Analyst | 4 | 2,138 | 4,443 |\n| Physical Therapist | 5 | 4,482 | 9,429 |\n| Electricians | | | |\n| Electrician | 5 | 12,781 | 18,249 |\n| Engineers And Land Surveyors | | | |\n| Engineer | 4 | 8,300 | 48,881 |\n| Gas Fitters | | | |\n| Gas Fitter | 4 | 12,117 | 15,004 |\n| Public Accountancy | | | |\n| Certified Public Accountant | 5 | 9,542 | 38,572 |\n| Real Estate | | | |\n| Real Estate Salesperson | 4 | 36,172 | 6,059 |\n| Social Workers | | | |\n| Social Worker, Licensed | 4 | 13,948 | 24,165 |\n| Speech And Audiology | | | |\n| Speech Pathologist | 5 | 4,035 | 4,462 |\n| | | | |\n\nSelected occupations ranked 4+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 State Data Package" }, { "slide_number": 55, "markdown_text": "## Part IV: New Data Tools", "report name": "2019 State Data Package" }, { "slide_number": 56, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 State Data Package" }, { "slide_number": 57, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 State Data Package" }, { "slide_number": 58, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 State Data Package" }, { "slide_number": 59, "markdown_text": "## Appendix: Regional Context", "report name": "2019 State Data Package" }, { "slide_number": 60, "markdown_text": "## Unemployment Rate\n\n", "report name": "2019 State Data Package" }, { "slide_number": 61, "markdown_text": "## Unemployed v. Employed in Labor Force\n\n", "report name": "2019 State Data Package" }, { "slide_number": 62, "markdown_text": "## Median Annual Wage\n\n", "report name": "2019 State Data Package" }, { "slide_number": 63, "markdown_text": "## Educational Requirements for Employment\n\nMassachusetts is projected to have the same shares of jobs that require a BA+, AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 State Data Package" }, { "slide_number": 64, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 State Data Package" }, { "slide_number": 65, "markdown_text": "## Priority Industries by Age\n\n", "report name": "2019 State Data Package" }, { "slide_number": 66, "markdown_text": "## Priority Industries by Gender\n\n", "report name": "2019 State Data Package" }, { "slide_number": 67, "markdown_text": "## Priority Industries by Educational Attainment\n\n", "report name": "2019 State Data Package" }, { "slide_number": 68, "markdown_text": "## Priority Industries by Race\n\n", "report name": "2019 State Data Package" }, { "slide_number": 69, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 State Data Package" }, { "slide_number": 70, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 State Data Package" }, { "slide_number": 71, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 State Data Package" }, { "slide_number": 72, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| % of Industry Employment | % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----------------------------|----|\n| 148,329 | 490,056 | 20% | |\n| 10% | 50% | 30% | |\n| 0% | 10% | 20% | |\n\n| % of Industry Employment | % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----------------------------|----|\n| +5,000 | +4% | +5% | |\n| +25,000 | +20,000 | +25% | |\n| +15,000 | +10,000 | +15% | |\n| +5,000 | +5,000 | +5% | |\n| +4% | +4% | +4% | |\n| Male | Female | Male | |", "report name": "2019 State Data Package" }, { "slide_number": 73, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been increasing for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 State Data Package" }, { "slide_number": 74, "markdown_text": "## Manufacturing", "report name": "2019 State Data Package" }, { "slide_number": 75, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in Massachusetts are still predominantly male, although the share of female workers has increased since 2015.\n\n| Category | Value | |\n|--------------------------|---------|----|\n| Female | -3% | |\n| Male | -3% | |\n| Change in # of Employees | -3% | |", "report name": "2019 State Data Package" }, { "slide_number": 76, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nMore than 80% of Manufacturing workers in Massachusetts are white. However, the share of Manufacturing workers who identify as Black or African American, Asian, or Hispanic or Latino has increased since 2015.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n| Chart Type | Description | |\n|------------------|--------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data | |", "report name": "2019 State Data Package" }, { "slide_number": 77, "markdown_text": "## Professional and Technical Services", "report name": "2019 State Data Package" }, { "slide_number": 78, "markdown_text": "## Professional and Technical Services by Gender\n\nEmployment in the Professional and Technical Services sector is fairly evenly split between male and female workers.\n\n| Category | Value | |\n|-----------------------------------------------------|---------|----|\n| Female | 100% | |\n| Male | 90% | |\n| Change in of Industry Employment, Q2 2018 | 143,636 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 16,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 15,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 14,500 | |\n| Change in of Industry Employment, Q2 2015 - Q2 2018 | 11% | |", "report name": "2019 State Data Package" }, { "slide_number": 79, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nMore than 80% of workers in the Professional and Technical Services sector in Massachusetts are white, although Asian workers make up the fastest-growing segment of the industry workforce.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 State Data Package" }, { "slide_number": 80, "markdown_text": "## Construction", "report name": "2019 State Data Package" }, { "slide_number": 81, "markdown_text": "## Construction by Gender\n\nMore than 80% of Construction workers in Massachusetts are male.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 State Data Package" }, { "slide_number": 82, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 90% of Construction workers in Massachusetts are white.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n## Percent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 State Data Package" }, { "slide_number": 83, "markdown_text": "## Appendix: Professional Licensing", "report name": "2019 State Data Package" }, { "slide_number": 84, "markdown_text": "## Occupation Demand and DPL Licensing: Deep Dive\n\n| DPL Board/License Type | STARS | Licenses | 2018 Employment | Closer Look: DPL Licenses Matched to Multiple SOC Occupations |\n|------------------------------|---------|------------|-------------------|----------------------------------------------------------------------------------|\n| Allied Health | 5 | 5,028 | 7,556 | DPL Board / License Type / Occupation Title STARS Licenses 2018 Employment |\n| Mental Health Counselor | 5 | 3,020 | 5,536 | Engineers and Land Surveyors |\n| Occupational Therapist | 4 | 2,614 | 5,305 | ENGINEER |\n| Educational Psychologist | 4 | 2,138 | 4,443 | Industrial Engineers |\n| Applied Behavior Analyst | 4 | 2,138 | 4,443 | Mechanical Engineers |\n| Physical Therapist | 5 | 4,482 | 9,429 | Electrical Engineers |\n| Electricians | 5 | 12,781 | 18,249 | Civil Engineers |\n| Electrician | 5 | 12,781 | 48,881 | Electronics Engineers, Except Computer |\n| Engineers And Land Surveyors | 4 | 8,300 | 48,881 | Environmental Engineers |\n| Gas Fitters | 4 | 12,117 | 15,004 | Biomedical Engineers |\n| Gas Filter | 4 | 12,117 | 2,782 | Computer Hardware Engineers |\n| Public Accountancy | 5 | 9,542 | 38,572 | Chemical Engineers |\n| Certified Public Accountant | 5 | 9,542 | 38,572 | Social Workers |\n| Real Estate | 4 | 36,172 | 6,059 | SOCIAL WORKER, LICENSED 4 13,948 24,165 |\n| Social Workers | 4 | 13,948 | 24,165 | Child, Family, and School Social Workers |\n| Social Worker, Licensed* | 4 | 13,948 | 4,462 | Healthcare Social Workers |\n| Speech And Audiology | 5 | 4,035 | 4,462 | Source: Division of Professional Licensure, 2000-2019; |\n| Speech Pathologist | 5 | 4,035 | 4,462 | Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections |\n| Veterinarian | 4 | 1,503 | 1,746 | |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 4+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 State Data Package" }, { "slide_number": 85, "markdown_text": "## Glossary", "report name": "2019 State Data Package" }, { "slide_number": 86, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 State Data Package" }, { "slide_number": 87, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 State Data Package" }, { "slide_number": 88, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 State Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Cape & Islands 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Cape Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Cape Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment\n- iii. Occupations\n\n## Part II: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part III: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part IV: New Data Tools\n\n## Appendix\n\n- A: Regional Context\n- B: Worker Characteristics\n- C: Priority Industry Profiles\n- D: Critical Industry Profiles\n- E: Professional Licensing\n\n## Glossary", "report name": "2019 Cape Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Cape Data Package" }, { "slide_number": 5, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Cape Data Package" }, { "slide_number": 6, "markdown_text": "## I.A: Regional Industry Overview", "report name": "2019 Cape Data Package" }, { "slide_number": 7, "markdown_text": "## Sector Makeup by Total Employment\n\nAccommodation and Food Service is the largest industry in the Cape & Islands, followed by Retail and Healthcare and Social Assistance.\n\n| Category | Value | |\n|-----------------|---------|----|\n| Accommodation | 20 K | |\n| Retail Trade | 20 K | |\n| Health Care | 19 K | |\n| Construction | 19 K | |\n| Education | 7 K | |\n| Arts | 7 K | |\n| Public | 7 K | |\n| Professional | 7 K | |\n| Transportation | 7 K | |\n| Manufacturing | 7 K | |\n| Finance and | 7 K | |\n| Real Estate | 7 K | |\n| Information | 7 K | |\n| Wholesale Trade | 7 K | |\n| Agriculture | 7 K | |\n| Utilities | 7 K | |\n| Management | 7 K | |\n| Mining | 7 K | |", "report name": "2019 Cape Data Package" }, { "slide_number": 8, "markdown_text": "## Sector Makeup by Total Wages\n\nIn the Cape & Islands, Healthcare and Social Assistance pays the most in wages, followed closely by Accommodation and Food Service.", "report name": "2019 Cape Data Package" }, { "slide_number": 9, "markdown_text": "## I.B: Priority Industry Profiles", "report name": "2019 Cape Data Package" }, { "slide_number": 10, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Cape Data Package" }, { "slide_number": 11, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nThe number of Healthcare and Social Assistance establishments in the Cape & Islands has grown since 2016 by more than 20, with much of this growth from the Individual and Family Services subsector (which includes home and community based care organizations). Cape Cod Healthcare had the largest number of job postings over the past year with 960 postings.\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 12, "markdown_text": "## Healthcare and Social Assistance by Education\n\nWorkers in Healthcare and Social Assistance are almost evenly distributed between those who have a Bachelor's degree or higher, Some College or Associate degree, or High School equivalent or less.", "report name": "2019 Cape Data Package" }, { "slide_number": 13, "markdown_text": "## Hospitality", "report name": "2019 Cape Data Package" }, { "slide_number": 14, "markdown_text": "## Hospitality Groups and Employers\n\nThe number of Hospitality establishments in the Cape & Islands grew by 4 since 2016. Chatham Bars Inn had the greatest number of job postings over the past year (89), followed by Chipotle Mexican Grill (69) and Reinhart Foodservice (68).\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 15, "markdown_text": "## Hospitality by Education\n\nMore than 40% of workers in the Hospitality industry have some college or higher level of education. 34% of this industry's workers in the Cape & Islands have a High school equivalent or less.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | 12,494 | -3,3% | 13,195 |\n|-----|------------|---------|-------------|\n| 80% | 24%, 3,001 | +12.3% | 22% , 2,902 |\n| 70% | 16%, 2,042 | +17% | 17%, 2,294 |\n| 60% | 24%, 2,961 | +7.1% | 24%, 3,171 |\n| 50% | 24%, 2,963 | +5.8% | 24%, 3,135 |\n| 40% | 24%, 2,963 | +10.9% | 20% |\n| 10% | 12%, 1,527 | +10.9% | 13% , 1,693 |\n| 0% | 2015 | 2018 | |\n| | | | |", "report name": "2019 Cape Data Package" }, { "slide_number": 16, "markdown_text": "## Construction", "report name": "2019 Cape Data Package" }, { "slide_number": 17, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments on the Cape & Islands has grown since 2016 by more than 130. Employers like W Vernon Whitely Plumbing and Heating and Roto Rooter posted less than 10 jobs over the past year. It is worth noting that many construction jobs are not posted publicly, instead finding talent through unions and apprenticeship programs.\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 18, "markdown_text": "## Construction by Education\n\nConstruction employment in the Cape & Islands has increased since 2015. The shares of workers by educational attainment has stayed the same, with more than 50% having some college or higher and more than 40% having a High school equivalent or less.\n\n| | 7,342 | 7,342 | 8,573 | 8,573 | |\n|----|------------|------------|------------|------------|------------|\n| | 8% , 563 | 8% , 563 | 8% , 704 | 8% , 704 | |\n| | 21%, 1,538 | 21%, 1,538 | 21%, 1,831 | 21%, 1,831 | |\n| | 70% | 70% | +16.3% | +16.3% | |\n| | 29%, 2,128 | 29%, 2,128 | 29%, 2,474 | 29%, 2,474 | |\n| | 0% | 40% | +12.2% | +12.2% | |\n| | 30% | 31%, 2,250 | 31%, 2,250 | 29%, 2,525 | 29%, 2,525 |\n| | 10% | 12%, 863 | 12%, 863 | 12%, 1,039 | 12%, 1,039 |\n| | 0% | 2015 | 2015 | 2018 | 2018 |", "report name": "2019 Cape Data Package" }, { "slide_number": 19, "markdown_text": "## Occupations", "report name": "2019 Cape Data Package" }, { "slide_number": 20, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Cape Data Package" }, { "slide_number": 21, "markdown_text": "## Selected Sub-BA Occupations Associated with Priority Industries\n\n| Industry | SOC Code | Occupation Title | Educational Requirement | 2018 Industry Employment | STAR | Median Annual Wage |\n|------------------------|------------|----------------------------------------------------|--------------------------------|-----------------------------|--------|----------------------|\n| Hospitality | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 1,590 | 4 | $47,243 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 4,220 | 4 | $60,475 |\n| Construction | 53-3032 | Heavy and Tractor-Trailer Truck Drivers | Postsecondary non-degree award | 2,820 | 4 | $56,606 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 3,910 | 4 | $47,243 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 130 | 4 | $60,120 |\n| | 29-2021 | Dental Hygienists | Associate's degree | 5,360 | 4 | $80,759 |\n| | 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 | 4 | $65,825 |\n| | 29-2032 | Diagnostic Medical Sonographers | Associate's degree | 2,030 | 5 | $84,630 |\n| | 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 | 4 | $52,061 |\n| Health Care and Social | 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 | 4 | $43,032 |\n| Assistance | 29-2071 | Medical Records and Health Information Technicians | Postsecondary non-degree award | 4,220 | 4 | $46,202 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 | 4 | $60,475 |\n| | 49-3023 | Automotive Service Technicians and Mechanics | Postsecondary non-degree award | 60 | 4 | $46,945 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 | 4 | $47,243 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 820 | 4 | $60,120 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Cape Data Package" }, { "slide_number": 22, "markdown_text": "## Part II: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Cape Data Package" }, { "slide_number": 23, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Cape Data Package" }, { "slide_number": 24, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Cape Data Package" }, { "slide_number": 25, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3+ Stars\n\nAt the sub-BA level, a number of occupations rated 3+ stars do not have enough regional supply to meet employer demand.\n\n\n\n3+ star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 10+ only.", "report name": "2019 Cape Data Package" }, { "slide_number": 26, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Cape Data Package" }, { "slide_number": 27, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Cape Data Package" }, { "slide_number": 28, "markdown_text": "## Part III: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Cape Data Package" }, { "slide_number": 29, "markdown_text": "## III. A: Apprenticeships", "report name": "2019 Cape Data Package" }, { "slide_number": 30, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 31, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Cape Data Package" }, { "slide_number": 32, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 33, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn the Cape & Islands, the most popular occupations for apprentices (including Construction Laborers, Electricians, Plumbers, Pipefitters, and Steamfitters) are ranked 4 stars, indicating high wages and strong projected employer demand.\n\nSource: Division of Apprentice Standards, 2019\n\n| Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|----------------|---------------|----------|\n| Construction Laborers | 4 | 12 | 162 |\n| Electricians | 4 | 11 | 78 |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 7 | 117 |\n| Police and Sheriff's Patrol Officers | 4 | 6 | 91 |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 6 | 73 |\n| Carpenters | 4 | 5 | 275 |\n| Firefighters | 4 | 2 | 92 |\n| Correctional Officers and Jailers | 2 | 1 | 53 |\n| Heavy and Tractor-Trailer Truck Drivers | 4 | 1 | 206 |\n| Telecommunications Equipment Installers and Repairers | 3 | 1 | 19 |\n| Medical Records and Health Information Technicians | 4 | 1 | 54 |\n| | | | |", "report name": "2019 Cape Data Package" }, { "slide_number": 34, "markdown_text": "## III. B: Professional Licensing", "report name": "2019 Cape Data Package" }, { "slide_number": 35, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nIn the Cape & Islands, a majority of the top occupations by professional licensure are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Cape Data Package" }, { "slide_number": 36, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\nComparing the number of license holders with total occupational employment offers another indicator of skill shortages or surpluses in occupational labor markets. While the number of professional licenses exceeds total employment for some occupations, such as Real Estate Salespersons, for others, such as Physical Therapists, the number of jobs (322) outstrips the supply of licenses (187).\n\n| | DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|---------|------------|-------------------|\n| Allied Health | | | | |\n| Mental Health Counselor | 4 | 194 | 147 | |\n| Physical Therapist | 5 | 187 | 322 | |\n| Occupational Therapist | 4 | 104 | 197 | |\n| Physical Therapist Assistant | 4 | 50 | 136 | |\n| Architects | | | | |\n| Architect | 4 | 57 | 103 | |\n| Cosmetology | | | | |\n| Cosmetologist (Hairdresser) | 4 | 898 | 889 | |\n| Electricians | | | | |\n| Electrician | 4 | 481 | 526 | |\n| Engineers And Land Surveyors | 4 | 198 | 418 | |\n| Engineer | 4 | | | |\n| Gas Fitters | 4 | 807 | 808 | |\n| Gas Fitter | 4 | | | |\n| Public Accountancy | 5 | 110 | 569 | |\n| Certified Public Accountant | Real Estate | 5 | 569 | |\n| Real Estate Salesperson | 4 | 2,516 | 399 | |\n| Social Workers | 3 | 488 | 530 | |\n| Social Worker, Licensed | Source: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections | | | |\n\nSelected occupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019. See Appendix for additional detail.", "report name": "2019 Cape Data Package" }, { "slide_number": 37, "markdown_text": "## Part IV: New Data Tools", "report name": "2019 Cape Data Package" }, { "slide_number": 38, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Cape Data Package" }, { "slide_number": 39, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Cape Data Package" }, { "slide_number": 40, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Cape Data Package" }, { "slide_number": 41, "markdown_text": "## Appendix: Regional Context", "report name": "2019 Cape Data Package" }, { "slide_number": 42, "markdown_text": "## Unemployment Rate\n\nThe Cape & Islands unemployment rate was higher than the state average during the winter and early spring months this past year, and was slightly lower than the state average over last summer. This reflects the strength of seasonal employment in the region.\n\n| Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | Jun-19 | Jul-19 | Aug-19 | Sep-19 | Oct-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 0.0% | 1.0% | 2.0% | 3.0% | 4.0% | 5.0% | 6.0% | 7.0% | 8.0% | 9.0% | 10.0% | 11.0% | | |", "report name": "2019 Cape Data Package" }, { "slide_number": 43, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThe Cape & Islands labor force is largest in the summer months when tourism is the strongest.\n\n| Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | Jun-19 | Jul-19 | Aug-19 | Sep-19 | Oct-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 128,238 | 123,428 | 122,705 | 118,794 | 117,169 | 118,028 | 122,340 | 129,633 | 141,480 | 149,454 | 148,472 | 134,110 | 128,986 | |", "report name": "2019 Cape Data Package" }, { "slide_number": 44, "markdown_text": "## Median Annual Wage\n\nThe Cape & Islands median annual wage has increased since 2015, almost twice as much as the state average increase over the same period ($3,933 vs. $1,990).\n\n| Berkishre | Cape and Islands | Central | Greater Boston | Northeast | Pioneer Valley | Southeast | Massachusetts | |\n|-------------|--------------------|-----------|------------------|-------------|------------------|-------------|-----------------|----|\n| $36,317 | $38,179 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |\n| $30,000 | $36,317 | $38,433 | $40,646 | $43,133 | $53,153 | $56,732 | $45,698 | |", "report name": "2019 Cape Data Package" }, { "slide_number": 45, "markdown_text": "## Educational Requirements for Employment\n\nNearly one in five jobs in the Cape & Islands in 2026 are projected to need a Bachelor's degree or higher and more than two-thirds will require a high school diploma or less.\n\n\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 46, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Cape Data Package" }, { "slide_number": 47, "markdown_text": "## Regional and State Priority Industries by Age\n\n| Category | Value | |\n|--------------------------------------------------|---------|----|\n| Accommodation and Food Services | 100% | |\n| Construction | 2,346 | |\n| Health Care and Social Assistance | 1,867 | |\n| Manufacturing | 3,169 | |\n| Professional, Scientific, and Technical Services | 3,46 | |\n| Health Care and Social Assistance | 1,04 | |\n| Health Care and Social Assistance | 1,092 | |\n| Health Care and Social Assistance | 1,092 | |", "report name": "2019 Cape Data Package" }, { "slide_number": 48, "markdown_text": "## Regional and State Priority Industries by Gender\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 49, "markdown_text": "## Regional and State Priority Industries by Educational Attainment\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 50, "markdown_text": "## Regional and State Priority Industries by Race\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 51, "markdown_text": "## Regional and State Priority Industries by Ethnicity\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 52, "markdown_text": "## Appendix: Priority Industry Profiles", "report name": "2019 Cape Data Package" }, { "slide_number": 53, "markdown_text": "## Healthcare and Social\n\nAssistance", "report name": "2019 Cape Data Package" }, { "slide_number": 54, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | 0% | |\n| Male | 10% | |\n| Female | 3618 | |\n| Change in of Employees | 15,006 | |\n| Change in of Employees in of Employees | 10% | |\n\n| Male | Female | |\n|--------|----------|----|\n| Male | Female | |", "report name": "2019 Cape Data Package" }, { "slide_number": 55, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile most workers in the Healthcare and Social Assistance sector are white, since 2015, growth in employment has been greater for Black or African American, Asian, and Hispanic or Latino populations.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nPercent and Absolute Change in Industry Employment, Q2 2015 - Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Cape Data Package" }, { "slide_number": 56, "markdown_text": "## Hospitality", "report name": "2019 Cape Data Package" }, { "slide_number": 57, "markdown_text": "## Hospitality by Gender\n\nThe Hospitality industry has almost equal shares of male and female workers in the Cape & Islands. Males have joined the industry in greater numbers than females since 2015.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |", "report name": "2019 Cape Data Package" }, { "slide_number": 58, "markdown_text": "## Hospitality by Race/Ethnicity\n\nWorkers in Hospitality in the Cape & Islands are predominantly white, with about 15% identifying as Black or African American or Asian.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Cape Data Package" }, { "slide_number": 59, "markdown_text": "## Construction", "report name": "2019 Cape Data Package" }, { "slide_number": 60, "markdown_text": "## Construction by Gender\n\nConstruction is a predominantly male industry with just 20% female workers.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Cape Data Package" }, { "slide_number": 61, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 90% of construction workers are white. Numbers of Black or African American, Asian, and Hispanic or Latino workers are growing, but still represent small numbers of workers on the Cape & Islands.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 62, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Cape Data Package" }, { "slide_number": 63, "markdown_text": "## Manufacturing", "report name": "2019 Cape Data Package" }, { "slide_number": 64, "markdown_text": "## Manufacturing Groups and Employers\n\nThe number of manufacturing establishments has declined slightly since 2016 in the Cape & Islands. PepsiCo, Inc had the most job postings (47) in the region over the past year. While Bakeries are one of the subsectors with the largest number of establishments, biotech, pharma and marine science companies like Teledyne, Pfizer and Hydroid had 10 or more openings over the past year.\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 65, "markdown_text": "## Manufacturing by Education\n\n37% of workers in Manufacturing in the Cape & Islands have a high school diploma or less. 28% have some college or an Associate degree and nearly 26% have a Bachelor's degree or higher. This mix has been relatively stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| | 2,271 | 2,244 |\n|------|---------|-----------|\n| 100% | 9%, 204 | 9%, 211 |\n| 90% | 80% | -0.9% |\n| 70% | 70% | -3.8% |\n| 60% | 60% | -3.8% |\n| 50% | 50% | 28%, 635 |\n| 40% | 40% | -3.2% |\n| 30% | 30% | -27%, 621 |\n| 20% | 20% | -2.8% |\n| 10% | 10% | 218 |\n| 0% | 0% | 2018 |\n| | | |", "report name": "2019 Cape Data Package" }, { "slide_number": 66, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers are predominantly male, though nearly 35% of workers are female on the Cape & Islands-a higher share than several other regions.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|----|\n| Male | |\n| Female | |\n| Male | |\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Cape Data Package" }, { "slide_number": 67, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce is predominantly white in the Cape & Islands, with only about 6 percent of workers identifying as Black or African American, or Asian.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 68, "markdown_text": "## Professional and Technical Services", "report name": "2019 Cape Data Package" }, { "slide_number": 69, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nProfessional and Technical Services include legal, accounting and bookkeeping, and architectural and engineering services. The number of establishments in this sector have been stable since 2016. Marine Biological Laboratory had the highest number of job postings in this sector in the Cape & Islands over the past year (131).\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 70, "markdown_text": "## Professional and Technical Services by Education\n\n43% of workers in Professional and Technical Services in the Cape & Islands have a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|--------|----|\n| 2015 | 31%, 2,250 | 29%, 2,128 | 21%, 1,538 | 29%, 2,474 | 29% | |\n| 2018 | 12%, 863 | +12.2% | +16.3% | +16.3% | +12.2% | |", "report name": "2019 Cape Data Package" }, { "slide_number": 71, "markdown_text": "## Professional and Technical Services by Gender\n\nIn the Cape & Islands there are nearly equal shares of male and female workers in Professional and Technical Services.\n\n| % of Industry Employment | % of Industry Employment | |\n|----------------------------|----------------------------|----|\n| 2,219 | 40% | |\n| 2,19 | 30% | |\n| 0% | 10% | |\n\n| Male | Female | |\n|--------|----------|----|\n| Male | Female | |", "report name": "2019 Cape Data Package" }, { "slide_number": 72, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\nNearly 94% of workers in the Professional and Technical Services industry in the Cape & Islands are white. Though there have been increases since 2015 in the number of Asian and Hispanic or Latino workers, the numbers are still small.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Cape Data Package" }, { "slide_number": 73, "markdown_text": "## Appendix: Professional Licensing", "report name": "2019 Cape Data Package" }, { "slide_number": 74, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|------------------------------|---------|------------|-------------------|\n| Allied Health | 4 | 194 | 147 |\n| Mental Health Counselor | 5 | 187 | 322 |\n| Physical Therapist | 4 | 104 | 197 |\n| Occupational Therapist | 4 | 50 | 136 |\n| Physical Therapist Assistant | 4 | 50 | 136 |\n| Architects | 4 | 57 | 103 |\n| Architect | 3 | 365 | 123 |\n| Cosmetology | 4 | 898 | 889 |\n| Aesthetician | 3 | 365 | 123 |\n| Cosmetologist (Hairdresser) | 4 | 898 | 889 |\n| Electricians | 4 | 481 | 526 |\n| Electrician | 4 | 481 | 526 |\n| Engineers And Land Surveyors | 4 | 198 | 418 |\n| Engineer* | 4 | 198 | 418 |\n| Gas Filters | 4 | 807 | 808 |\n| Gas Fitter | 4 | 807 | 808 |\n| Public Accountancy | 5 | 110 | 569 |\n| Certified Public Accountant | 5 | 110 | 569 |\n| Real Estate | 4 | 2,516 | 399 |\n| Real Estate Salesperson | 4 | 2,516 | 399 |\n| Social Workers | 3 | 488 | 530 |\n| Social Worker, Licensed* | 3 | 488 | 530 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019; Bureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Cape Data Package" }, { "slide_number": 75, "markdown_text": "## Glossary", "report name": "2019 Cape Data Package" }, { "slide_number": 76, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Cape Data Package" }, { "slide_number": 77, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Cape Data Package" }, { "slide_number": 78, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Cape Data Package" }, { "slide_number": 1, "markdown_text": "\n\n## Southeast 2019 Data Package Update\n\nRegional Workforce Skills Planning Initiative", "report name": "2019 Southeast Data Package" }, { "slide_number": 2, "markdown_text": "## Objectives\n\n- · Update contextual regional labor market information\n- · Narrow scope of data/discussion to focus on regional priority/critical industries\n- · Confirm regional high priority industries and occupations through updated demand star rankings and skill gap analysis\n- · Evaluate any new demographic, labor pool, and talent pipeline considerations impacting workforce skill gaps\n- · Introduce new dynamic data tools", "report name": "2019 Southeast Data Package" }, { "slide_number": 3, "markdown_text": "## Table of Contents\n\n## Part I: Regional Context\n\n- i. Unemployment Rate\n- ii. Labor Force - Educational Requirements for Employment\n\n## Part II. Regional Industry Overview and Profiles\n\n- A: Sector Makeup by Employment and Wages\n- B: Priority Industry Profiles\n- i. Groups and Employers\n- ii. Employment by Educational Attainment, Gender, and Race/Ethnicity\n- iii. Occupations\n\n## Part III: Supply Gap Analysis\n\n- i. Regional Sub-BA Occupations\n- ii. State BA+ Occupations\n\n## Part IV: Workforce Supply Analysis\n\n- A: Apprenticeships\n- B: Professional Licensing\n\n## Part V: New Data Tools\n\n## Appendix\n\n- A: Critical Industry Profiles\n- B: Worker Characteristics\n\nGlossary", "report name": "2019 Southeast Data Package" }, { "slide_number": 4, "markdown_text": "## Part I: Regional Context", "report name": "2019 Southeast Data Package" }, { "slide_number": 5, "markdown_text": "## Unemployment Rate\n\nThe Southeast's unemployment rate historically tracks with the state average, though about a quarter of a percentage point higher.\n\n| May-18 | Jun-18 | Jul-18 | Aug-18 | Sep-18 | Oct-18 | Nov-18 | Dec-18 | Jan-19 | Feb-19 | Mar-19 | Apr-19 | May-19 | |\n|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----|\n| 0.0% | 1.0% | 2.0% | 3.0% | 4.0% | 5.0% | 6.0% | 7.0% | 8.0% | 9.0% | 10.0% | 11.0% | | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 6, "markdown_text": "## Unemployed v. Employed in Labor Force\n\nThere are fewer unemployed workers in the Southeast as of May 2019 than the prior year. The overall labor force has also increased by about 10,000, as some people who previously were no longer looking for work have returned to the labor market and are having success finding employment.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 7, "markdown_text": "## Median Annual Wage\n\nThe Southeast's median annual wage has increased since 2015. The state average exceeds the Southeast by about $7K.\n\n| Year | Median Annual Wage | 2018 Median Annual Wage | |\n|---------|----------------------|---------------------------|----|\n| $36,317 | $56,732 | $40,646 | |\n| $38,179 | $53,153 | $40,646 | |\n| $38,433 | $42,366 | $43,133 | |\n| $38,601 | $42,225 | $45,698 | |\n| $38,163 | $42,797 | $41,303 | |\n| $38,601 | $42,100 | $46,690 | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 8, "markdown_text": "## Educational Requirements for Employment\n\nThe Southeast is projected to have similar shares of jobs that require BA+; AS, Cert. or Some College, and HS or Below in 2026 as in 2016.\n\n\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 9, "markdown_text": "## Part II: Regional Industry Overview and Profiles\n\nWho are the employers in our region?", "report name": "2019 Southeast Data Package" }, { "slide_number": 10, "markdown_text": "## Terminology\n\n| Industry Sector | Sectors that represent general categories of economic activities, 2 digit NAICS |\n|-------------------|---------------------------------------------------------------------------------------------------------------------|\n| Industry Group | More detailed production-oriented combinations of establishments with similar customers and services, 4 digit NAICS |", "report name": "2019 Southeast Data Package" }, { "slide_number": 11, "markdown_text": "## II.A: Regional Industry Overview", "report name": "2019 Southeast Data Package" }, { "slide_number": 12, "markdown_text": "## Sector Makeup by Total Employment\n\nHealth Care and Social Assistance is the largest industry in the Southeast. Retail Trade is the next largest industry in the region by employment, followed by Accommodation and Food Service.\n\n| Category | Value | |\n|----------------|---------|----|\n| Health Care | 120 | |\n| Retail Trade | 107 K | |\n| Accommodatio | -1% | |\n| Manufacturing | 77 K | |\n| Educational | +2% | |\n| Construction | +3% | |\n| Administrative | +2% | |\n| Finance | +3% | |\n| Wholesale | +2% | |\n| Trade | +3% | |\n| Other | +3% | |\n| Service | +3% | |\n| Professional | +2% | |\n| Public | +1% | |\n| Transportation | +1% | |\n| Arts | +1% | |\n| Management | +1% | |\n| Information | +1% | |\n| Real Estate | +1% | |\n| Utilities | +1% | |\n| Agriculture | +1% | |\n| Mining | +1% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 13, "markdown_text": "## Sector Makeup by Total Wages\n\nHealth Care and Social Assistance paid the highest total wages in the Southeast in 2018. Construction is the next highest paying sector with about half as much paid in total wages.\n\n| Category | Value | |\n|-----------------|-------------|----|\n| Health Care | $1 | |\n| Construction | $1 | |\n| Manufacturing | $6.68 B | |\n| Retail Trade | $6.62 B | |\n| Finance and | $5.52 B | |\n| Educational | $5.50 B | |\n| Wholesale Trade | $5.50 B | |\n| Professional | $5.50 B | |\n| Public | $5.50 B | |\n| Administrative | $5.50 B | |\n| Accommodation | $5.50 B | |\n| Management | $5.50 B | |\n| Transportation | $5.07 B | |\n| Other Services | Information | |\n| Agriculture | Agriculture | |\n| Minoring | Agriculture | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 14, "markdown_text": "## II.B: Priority Industry Profiles", "report name": "2019 Southeast Data Package" }, { "slide_number": 15, "markdown_text": "## Healthcare and Social Assistance", "report name": "2019 Southeast Data Package" }, { "slide_number": 16, "markdown_text": "## Healthcare and Social Assistance Groups and Employers\n\nNearly 1,000 Health Care and Social Assistance establishments were added in the Southeast between 2016 and 2018, driven primarily by the increase in Individual and Family Services establishments. Over the last 12 months, Southcoast Health System posted the most jobs in the Southeast with 1,348.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 17, "markdown_text": "## Healthcare and Social Assistance by Education\n\n60% of workers in Healthcare and Social Assistance have some college or higher level of education in the Southeast.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | |\n|------|--------------------------------------------------------------------|--------------|\n| 100% | 97,854 | 103,313 |\n| 90% | 10%, 9,514 | +1.1% |\n| 80% | 30%, 29,023 | +2.4% |\n| 70% | 60% | +4.4% |\n| 50% | 31%, 30,511 | +31%, 31,858 |\n| 2% | 30% | +8.4% |\n| 20% | 21%, 20,446 | +19.0% |\n| 10% | 9%, 8,360 | +10% |\n| 0% | 2015 | 2018 |\n| | | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 18, "markdown_text": "## Healthcare and Social Assistance by Gender\n\nThere are far more women than men working in Healthcare and Social Assistance, overall. This reflects the mix of occupations in the sector.\n\n| Category | Value | |\n|---------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +5% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +5% | |\n| Male | +7% | |\n| Female | +5% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 19, "markdown_text": "## Healthcare and Social Assistance by Race/Ethnicity\n\nWhile nearly 80% of workers in the Healthcare and Social Assistance sector are white in the Southeast, since 2015, growth in employment has been increasing in the sector for people of color.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 20, "markdown_text": "## Professional and Technical Services", "report name": "2019 Southeast Data Package" }, { "slide_number": 21, "markdown_text": "## Professional and Technical Services Groups and Employers\n\nThe Southeast is home to almost 3,800 establishments in the Professional and Technical Services sector, which includes legal services, management and technical consulting, accounting and bookkeeping, computer systems design and related services. In the last year, H&R Block had the most job postings in the Southeast with 287, followed by Advantage Sales & Marketing with 214.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 22, "markdown_text": "## Professional and Technical Services by Education\n\n42% of workers in the Professional and Technical Services sector in the Southeast have a Bachelor's degree or higher, while more than 25% have some college or an Associate degree.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|------------|----|\n| 2015 | 45%, 9,324 | 44.1% | 7.5% | 26%, 5,698 | 42%, 9,272 | |\n| 2018 | 6%, 1,168 | 7.5% | 18%, 3,878 | 23.8% | 7%, 1,446 | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 23, "markdown_text": "## Professional and Technical Services by Gender\n\nWorkers in Professional and Technical Services in the Southeast are pretty evenly divided between males and females.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for gender.", "report name": "2019 Southeast Data Package" }, { "slide_number": 24, "markdown_text": "## Professional and Technical Services by Race/Ethnicity\n\n88% percent of workers in the Professional and Technical Services Sector in the Southeast are white. The numbers of Asian workers are growing, followed by much smaller numbers of Black or African American and Hispanic or Latino workers.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018", "report name": "2019 Southeast Data Package" }, { "slide_number": 25, "markdown_text": "## Finance and Insurance", "report name": "2019 Southeast Data Package" }, { "slide_number": 26, "markdown_text": "## Finance and Insurance Groups and Employers\n\nThe number of Finance and Insurance establishments in the Southeast has grown slightly since 2016. In the last year, Anthem Blue Cross had the largest number of job postings in the Southeast (657), followed by Citizens Financial Group (451), Santander Bank (396) and State Street Bank (373).\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 27, "markdown_text": "## Finance and Insurance by Education\n\nNearly 50% of workers in the Finance and Insurance sector in the Southeast hold a Bachelor's degree or higher.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| Year | Educational attainment not available (age | Some college or Associate degree | High school or equivalent, no college | Less than high school | | |\n|--------|---------------------------------------------|------------------------------------|-----------------------------------------|-------------------------|-----|----|\n| 2015 | 49% | 47% | 5% | 26% | 12% | |\n| 2018 | 6% | 26% | 4% | 12% | 10% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 28, "markdown_text": "## Finance and Insurance by Gender\n\n60% of workers in the Finance and Insurance sector in the Southeast are female.\n\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018 | |\n|-------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------|----|\n| Male | +300 | |\n| Female | +700 | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 29, "markdown_text": "## Finance and Insurance by Race/Ethnicity\n\nMore than 80% of all workers in the Finance and Insurance sector in the Southeast are white. The number of Asian workers has grown the most since 2015, with other race/ethnic groups also showing small gains.\n\n| Category | % of Industry Employment | |\n|---------------------------------------------------------------------------------------------|----------------------------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | Black or African American | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | White | |\n| Black or African American | +11% | |\n| White | +100 | |\n| Black or African American | +25% | |\n| Asian | +28% | |\n| Other | +800 | |\n\n| Category | % of Industry Employment | |\n|---------------------------------------------------------------------------------------------|----------------------------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +28% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +25% | |\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +28% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 30, "markdown_text": "## Occupations", "report name": "2019 Southeast Data Package" }, { "slide_number": 31, "markdown_text": "## Terminology\n\n| Occupation | A job or profession, not specific to an industry, defined by Standard Occupational Classification (SOC) code |\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Demand Star Ranking | Ranking of highest-demand, highest-wage jobs in Massachusetts, based on short-term employment projections (2020), long-term employment projections (2026), 12-month job postings from Burning Glass, and median regional occupation wages. |", "report name": "2019 Southeast Data Package" }, { "slide_number": 32, "markdown_text": "## Sub-BA Occupations Associated with Priority Industries\n\n| | Industry | Occupation Title | Industry-Specific, Statewide | All Industries, Regional |\n|-----------------------------|------------|----------------------------------------------------|--------------------------------|----------------------------|\n| | SOC Code | Educational Requirement | 2018 Industry | STAR |\n| Finance and Insurance | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 3,480 |\n| Finance and Insurance | 15-1151 | Computer User Support Specialists | Some college, no degree | 980 |\n| | 29-2031 | Cardiovascular Technologists and Technicians | Associate's degree | 1,330 |\n| | 29-2021 | Dental Hygienists | Associate's degree | 5,360 |\n| | 29-2032 | Diagnostic Medical Sonographers | Associate's degree | 2,030 |\n| | 31-2021 | Physical Therapist Assistants | Associate's degree | 2,510 |\n| | 29-2034 | Radiologic Technologists | Associate's degree | 4,100 |\n| | 29-1126 | Respiratory Therapists | Associate's degree | 2,250 |\n| Health Care and Social | 49-3023 | Automotive Service Technicians and Mechanics | Postsecondary non-degree award | 60 |\n| Assistance | 31-9091 | Dental Assistants | Postsecondary non-degree award | 7,580 |\n| | 49-9021 | HVAC Mechanics and Installers | Postsecondary non-degree award | 210 |\n| | 29-2061 | Licensed Practical and Licensed Vocational Nurses | Postsecondary non-degree award | 14,000 |\n| | 31-9092 | Medical Assistants | Postsecondary non-degree award | 13,300 |\n| | 29-2071 | Medical Records and Health Information Technicians | Postsecondary non-degree award | 4,220 |\n| | 31-9097 | Phlebotomists | Postsecondary non-degree award | 3,320 |\n| | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 4,110 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 820 |\n| | 29-2071 | Medical Records and Health Information Technicians | Postsecondary non-degree award | 760 |\n| Professional and Technical | 43-3031 | Bookkeeping, Accounting, and Auditing Clerks | Some college, no degree | 6,350 |\n| | 15-1151 | Computer User Support Specialists | Some college, no degree | 6,990 |\n\nAll occupations listed are 4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Bolded occupations occur across multiple industries.", "report name": "2019 Southeast Data Package" }, { "slide_number": 33, "markdown_text": "## Part III: Supply Gap Analysis\n\nWhich occupations are likely to not have enough talent to meet employer demand?", "report name": "2019 Southeast Data Package" }, { "slide_number": 34, "markdown_text": "## How do we calculate a supply gap ratio?\n\nSupply Gap Ratio = Projected Qualified Individuals Per Opening\n\n- · Supply Gap Ratio is a proxy measure for understanding what occupations are likely to not have enough talent to meet employer demand.\n- · Supply / Demand = Supply Gap Ratio\n- · 100 qualified individuals / 50 potential openings = supply gap ratio of 2\n- · 2 qualified individuals per opening (More supply than demand)\n- · 6 qualified individuals / 12 potential openings = supply gap ratio of 0.5\n- · 0.5 qualified individuals per opening (Less supply than demand)", "report name": "2019 Southeast Data Package" }, { "slide_number": 35, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\n## Supply\n\nHow many potential job openings do we expect for a given occupation?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nNOTE TO DATA USERS: Beginning with this data package, Burning Glass is used to measure advertised online postings, replacing Help Wanted Online as the third component of indexed demand.\n\nNote that this substitution may be responsible for some of the variance between indexed demand as calculated in the original and updated data packages. Direct value comparisons of the occupational demand measures, STAR rankings, and supply gap ratios should be limited.\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?\n\nSum of available workers or graduates related to an occupation from multiple data sets…\n\n- · Unique UI claims, 2018 (DUA)\n- · Relevant completer data\n- · Voc-Tech completers, 2015-2017 average (DESE), 50% available*\n- · Community College completers, 2015-2017 average (DHE), 90% available\n- · State University completers, 2015-2017 average (DHE), 71% available\n- · Private University completers, 2015-2017 average (iPEDS), 55% available\n\n*All retention figures are statewide, studies cited in Data Tool **Occupations requiring post-secondary education only", "report name": "2019 Southeast Data Package" }, { "slide_number": 36, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 4+ Stars\n\nAt the sub-BA level, a number of 4- and 5-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n4- and 5-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Southeast Data Package" }, { "slide_number": 37, "markdown_text": "## More Openings than Qualified: Regional Sub-BA Occupations, 3 Stars\n\nAt the sub-BA level, a number of 3-star occupations do not have enough regional supply to meet employer demand.\n\n\n\n3-star occupations requiring a postsecondary non-degree award, some college, or an Associate's degree. Demand Index 20+ only.", "report name": "2019 Southeast Data Package" }, { "slide_number": 38, "markdown_text": "## State Supply Gap Overview: BA+ Clusters\n\nThe Computer and Mathematical, Architecture and Engineering, and Legal occupation clusters average the lowest ratios of qualified individuals per opening at the BA+ level.\n\n\n\nOccupations requiring a Bachelor's degree or higher, grouped by 2-digit SOC code. Occupation demand Index 100+. (Star rankings not available at the 2-digit SOC level.)", "report name": "2019 Southeast Data Package" }, { "slide_number": 39, "markdown_text": "## More Openings than Qualified: State BA+ Occupations\n\nAt the BA+ level, there are a number of 4- and 5-star occupations for which demand exceeds the supply of qualified individuals statewide.\n\n\n\n- 4- and 5-star occupations requiring a Bachelor's degree or higher. Demand Index 100+ only.\n\nOccupations new to the graph may have previously had a supply gap ratio> 1, a star ranking", "report name": "2019 Southeast Data Package" }, { "slide_number": 40, "markdown_text": "## Part IV: Workforce Supply Analysis\n\nHow many qualified individuals do we potentially have available to fill a relevant job opening?", "report name": "2019 Southeast Data Package" }, { "slide_number": 41, "markdown_text": "## IV. A: Apprenticeships", "report name": "2019 Southeast Data Package" }, { "slide_number": 42, "markdown_text": "## How do we calculate demand and supply?\n\n## Demand\n\nHow many potential jobs exist for apprentices in a given occupation in our region?\n\nNew Demand Measure, or the average of total number of jobs for each occupation across three data sets…\n\n- · 2020 projections from openings and replacement (OES)\n- · 2026 projections from openings and replacement (OES)\n- · New data source: Burning Glass 12-month job postings (2019)\n\nHow many apprentices are qualified to work in these occupations?\n\nTotal currently enrolled apprentices…\n\n- · Division of Apprentice Standards, 2019\n\n…minus the fraction of total occupation employment assumed to be made up of apprentices\n\n- · Bureau of Labor Statistics short-term projections (OES) - 2018 employment base\n\nTotal Number of Apprentices\n\nTotal 2018 Employment in Apprentice Trades\n\n*All apprentice employment assumptions are statewide-methodology detailed in apprenticeships data tool.", "report name": "2019 Southeast Data Package" }, { "slide_number": 43, "markdown_text": "## Top 15 State Occupations by Apprenticeships\n\nElectricians, Carpenters, and Plumbers, Pipefitters, and Steamfitters make up more than half of all apprenticeships statewide. All three of these occupations are ranked 4- or 5-stars, as are several other occupations with a large number of apprentices.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 44, "markdown_text": "## State Supply Gap Overview: Apprenticeships\n\nEmployer demand exceeds the supply of apprentices for a number of 4- and 5-star occupations statewide. Of these, Police and Sheriff's Patrol Officers, Firefighters, and Construction Laborers have the fewest apprentices per opening.\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 45, "markdown_text": "## Regional Occupation Demand and Supply of Apprentices\n\nIn the Southeast, the most popular occupations for apprentices (including Electricians, Carpenters, Plumbers, Pipefitters, and Steamfitters, and Heating, Air Conditioning, and Refrigeration Mechanics and Installers) are ranked 4+ stars, indicating high wages and strong projected employer demand.\n\n| | Occupation Title | STAR Ranking | Apprentices | Demand |\n|-----------------------------------------------------------------------|--------------------|----------------|---------------|----------|\n| Electricians | | 4 | 304 | 499 |\n| Carpenters | 4 | 188 | 663 | |\n| Plumbers, Pipefitters, and Steamfitters | 4 | 159 | 439 | |\n| Heating, Air Conditioning, and Refrigeration Mechanics and Installers | 4 | 109 | 317 | |\n| Construction Laborers | 4 | 73 | 599 | |\n| Structural Iron and Steel Workers | 4 | 57 | 38 | |\n| Sheet Metal Workers | 3 | 53 | 101 | |\n| Opticians, Dispensing | 2 | 41 | 42 | |\n| Firefighters | 4 | 32 | 128 | |\n| Glaziers | 2 | 17 | 28 | |\n| Telecommunications Equipment Installers and Repairers | 3 | 17 | 85 | |\n| First-Line Supervisors of Production and Operating Workers | 4 | 17 | 477 | |\n| Police and Sheriff's Patrol Officers | 4 | 14 | 266 | |\n| Teacher Assistants | 2 | 12 | 1,430 | |\n| Operating Engineers and Other Construction Equipment Operators | 4 | 12 | 134 | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 46, "markdown_text": "## IV. B: Professional Licensing", "report name": "2019 Southeast Data Package" }, { "slide_number": 47, "markdown_text": "## Top 15 Occupations by DPL Professional Licensing\n\nIn the Southeast, a majority of the top occupations by number of Division of Professional Licensure licenses are 4- or 5-star occupations.\n\n\n\nThis analysis is not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Southeast Data Package" }, { "slide_number": 48, "markdown_text": "## Regional Occupation Demand and DPL Licensing\n\n| DPL Board / License Type | STARS | Licenses | 2018 Employment |\n|--------------------------------|---------|------------|----------------------|\n| Allied Health | 3 | 384 | 250 |\n| Occupational Therapy Assistant | 3 | 960 | 1,636 |\n| Mental Health Counselor | 4 | 960 | 1,721 |\n| Applied Behavior Analyst | 3 | 354 | 721 |\n| Occupational Therapist | 5 | 570 | 1,207 |\n| Physical Therapist | 5 | 774 | 2,008 |\n| Physical Therapist Assistant | 4 | 291 | 764 |\n| Educational Psychologist | 5 | 218 | 934 |\n| Electricians | 4 | 3,620 | 3,517 |\n| Engineers And Land Surveyors | 3 | 3,994 | Industrial Engineers |\n| Engineer* | 3 | 1,396 | 3,994 |\n| Land Surveyor | 3 | 89 | 194 |\n| Funeral Directors | 3 | 253 | 142 |\n| Funeral Director | 4 | 3,266 | 3,590 |\n| Gas Filters | 4 | 3,266 | 3,590 |\n| Gas Filter | 5 | 1,536 | 3,886 |\n| Public Accountancy | 5 | 1,536 | 3,886 |\n| Certified Public Accountant | - | 8,005 | - |\n| Real Estate | - | 8,005 | - |\n| Social Workers | 4 | 2,287 | 4,296 |\n| Social Worker, Licensed* | 4 | 2,287 | 4,296 |\n| Veterinarian | 3 | 267 | 280 |\n| Veterinarian | 3 | 267 | 280 |\n\n*Matched to multiple SOC occupations. All license-occupation matches available in data tool.\n\nSource: Division of Professional Licensure, 2000-2019.\n\nBureau of Labor Statistics, Occupational Employment Statistics, 2020 Projections\n\nOccupations ranked 3+ stars only. Not inclusive of occupations licensed by agencies other than the Division of Professional Licensure. Licenses must have been issued between 2000 and 2019, and not be expired as of 2019.", "report name": "2019 Southeast Data Package" }, { "slide_number": 49, "markdown_text": "## Part V: New Data Tools", "report name": "2019 Southeast Data Package" }, { "slide_number": 50, "markdown_text": "## Dynamic Data Tools\n\nAs an extension of the data package update, a set of new dynamic data tools have been developed to support regional planning work.\n\nThese tools are intended to act as a resource for your teams to compare data across regions and generate insights beyond the analysis in this data package, with respect to five different areas:\n\n- 1. Licensure\n- 2. Apprenticeships\n- 3. Regional Sector Makeup\n- 4. Educational Attainment and Employment\n- 5. Worker Characteristics", "report name": "2019 Southeast Data Package" }, { "slide_number": 51, "markdown_text": "## Education Program Supply\n\n\n\nOnline Tool: http://massconnecting.org/pathwaymapping/default.asp#mapping", "report name": "2019 Southeast Data Package" }, { "slide_number": 52, "markdown_text": "## Discussion Questions\n\n- · How does this data inform your ongoing work to support regional priority industry and occupations?\n- · How can you act on this data to accelerate your blueprint priorities?\n- · This year, we're asking regional teams to develop an \"update\" to their blueprints. With this data in mind, what might be important to include in your update?", "report name": "2019 Southeast Data Package" }, { "slide_number": 53, "markdown_text": "## Appendix: Critical Industry Profiles", "report name": "2019 Southeast Data Package" }, { "slide_number": 54, "markdown_text": "## Manufacturing", "report name": "2019 Southeast Data Package" }, { "slide_number": 55, "markdown_text": "## Manufacturing Groups and Employers\n\nThere are fewer Manufacturing establishments in the Southeast than in 2016. In the last year, Johnson & Johnson was responsible for the largest number of job postings in the Southeast (486), followed by Cardinal Health, Inc. (167).\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 56, "markdown_text": "## Manufacturing by Education\n\n32% of workers in Manufacturing in the Southeast have a high school diploma or less. 28% of workers in Manufacturing have some college or an Associate Degree and 25% have a Bachelor's degree or higher. This educational attainment mix has been stable since 2015.\n\nIndustry Employment by Educational Attainment, Q2 2015 - Q2 2018\n\n| % of Employees | % of Employees | |\n|------------------|------------------|----|\n| 28%, 11,609 | -1.8% | |\n| 28%, 11,401 | -3.1% | |\n| 28%, 11,359 | -1.0% | |\n| 28%, 14%, 5,564 | -0.9% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 57, "markdown_text": "## Manufacturing by Gender\n\nManufacturing workers in the Southeast are predominantly male. Females make up just over 30% of workers in Manufacturing in the region.\n\n| Category | Value | |\n|-----------------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | -2% | |\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | -2% | |\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | -2% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 58, "markdown_text": "## Manufacturing by Race/Ethnicity\n\nThe Manufacturing workforce in the Southeast has seen small growth in the numbers of people of color since 2015. More than 80% of workers are white in this sector.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\n| Chart Type | Description | |\n|------------------|-------------------------------------------------------------------------------------------|----|\n| vbar_categorical | A vertical bar chart with categorical data on the x-axis and numerical data on the y-axis | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 59, "markdown_text": "## Construction", "report name": "2019 Southeast Data Package" }, { "slide_number": 60, "markdown_text": "## Construction Groups and Employers\n\nThe number of Construction establishments in the Southeast grew by more than 200 since 2016, with growth across several types of contractors. In the last year, Roto Rooter was responsible for the most online job postings in the Southeast (100), followed by Toll Brothers Inc. (36) and Clough Harbour Associates (28).\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 61, "markdown_text": "## Construction by Education\n\nConstruction workers have a variety of educational attainment backgrounds with 28% of workers with a high school diploma or equivalent, 28% some college or Associate degree, and 23% Bachelor's degree or higher.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - 2018\n\n| | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 | Industry Employment by Educational Attainment, Q2 2015 - Q2 2018 |\n|-----|--------------------------------------------------------------------|--------------------------------------------------------------------|--------------------------------------------------------------------|\n| | 30,832 | | 35,128 |\n| | 9%, 2,676 | | 10%, 3,350 |\n| | 23%, 6,977 | | 23%, 7.925 |\n| | 70% | | 70% |\n| 0% | 28%, 8,567 | +13.3% | 28%, 9,707 |\n| 40% | 29%, 8,943 | +11.0% | 28%, 9,926 |\n| 20% | 12%, 3,669 | +15.0% | 12%, 4,220 |\n| 0% | 2015 | | |\n| | | | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 62, "markdown_text": "## Construction by Gender\n\nMore than 80% of all Construction workers are male in the Southeast, though the number of females working in the sector grew by nearly 1,000 since 2015.\n\n| Category | Value | |\n|-----------------------------------------------------------------------------------------------------|---------|----|\n| US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +18% | |\n| Source: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018 | +18% | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 63, "markdown_text": "## Construction by Race/Ethnicity\n\nMore than 92% of Construction workers are white in the Southeast. There has been some small growth since 2015 in the number of Hispanic or Latino, Black or African American, and Asian workers.\n\n\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2018\n\n*Absolute value change is shown on the vertical axis. Labels indicate the percent change in employment for each racial/ethnic category.\n\nSource: US Census Longitudinal Employer-Household Dynamics: Quarterly Workforce Indicators, Q2 2015 - Q2 2018\n\n| | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 | Percent and Absolute Change* in Industry Employment, Q2 2015 - Q2 2018 |\n|----|--------------------------------------------------------------------------|--------------------------------------------------------------------------|--------------------------------------------------------------------------|--------------------------------------------------------------------------|--------------------------------------------------------------------------|--------------------------------------------------------------------------|\n| | +4,000 | +13% | | | | +4,500 |\n| | +3,500 | | | | | +4,000 |\n| | +3,000 | | | | | +3,500 |\n| | +2,500 | | | | | +3,500 |\n| | +2,000 | | | | | +2,500 |\n| | +1,500 | | | | | +2,000 |\n| | +1,500 | | | | | +1,500 |\n| | +37% | | | | | +35% |\n| | +28% | | | | | +500 |\n| | Other | | | | | Hispanic or Latino |\n| | Asian | | | | | Not Hispanic |\n| | Other | | | | | Latino |\n| | | | | | | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 64, "markdown_text": "## Appendix: Worker Characteristics", "report name": "2019 Southeast Data Package" }, { "slide_number": 65, "markdown_text": "## Priority and Critical Industries by Age\n\n| Category | Value | |\n|-----------------------------------------|---------|----|\n| Construction | 1588 | |\n| Finance and Insurance | 336 | |\n| Health Care and Social Assistance | 4,465 | |\n| Manufacturing | 1,182 | |\n| Professional, Scientific, and Technical | 547 | |\n| Services | 5,870 | |", "report name": "2019 Southeast Data Package" }, { "slide_number": 66, "markdown_text": "## Priority and Critical Industries by Gender\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 67, "markdown_text": "## Priority and Critical Industries by Educational Attainment\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 68, "markdown_text": "## Priority and Critical Industries by Race\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 69, "markdown_text": "## Priority and Critical Industries by Ethnicity\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 70, "markdown_text": "## Glossary", "report name": "2019 Southeast Data Package" }, { "slide_number": 71, "markdown_text": "## Standard Occupational Classification (SOC)\n\nThe 2018 Standard Occupational Classification (SOC) system is used by federal statistical agencies to classify workers and jobs into occupational categories for the purpose of collecting, calculating, analyzing, or disseminating data.\n\nTo facilitate classification and presentation of data, the SOC is organized into a tiered system with four levels: major group, minor group, broad occupation, and detailed occupation. The 23 major groups (below) are broken into minor groups, which, in turn, are divided into broad occupations. At the highest level of specification, there are 867 detailed occupations with unique SOC codes.\n\n| Code | Title | Code | Title |\n|---------|------------------------------------------------------------|---------|-----------------------------------------------------------|\n| 11-0000 | Management Occupations | 35-0000 | Food Preparation and Serving Related Occupations |\n| 13-0000 | Business and Financial Operations Occupations | 37-0000 | Building and Grounds Cleaning and Maintenance Occupations |\n| 15-0000 | Computer and Mathematical Occupations | 39-0000 | Personal Care and Service Occupations |\n| 17-0000 | Architecture and Engineering Occupations | 41-0000 | Sales and Related Occupations |\n| 19-0000 | Life, Physical, and Social Science Occupations | 43-0000 | Office and Administrative Support Occupations |\n| 21-0000 | Community and Social Service Occupations | 45-0000 | Farming, Fishing, and Forestry Occupations |\n| 23-0000 | Legal Occupations | 47-0000 | Construction and Extraction Occupations |\n| 25-0000 | Educational Instruction and Library Occupations | 49-0000 | Installation, Maintenance, and Repair Occupations |\n| 27-0000 | Arts, Design, Entertainment, Sports, and Media Occupations | 51-0000 | Production Occupations |\n| 29-0000 | Healthcare Practitioners and Technical Occupations | 53-0000 | Transportation and Material Moving Occupations |\n| 31-0000 | Healthcare Support Occupations | 55-0000 | Military Specific Occupations |\n| 33-0000 | Protective Service Occupations | | |\n\nA complete description of SOC codes, titles and definitions can be found at www.bls.gov/soc/", "report name": "2019 Southeast Data Package" }, { "slide_number": 72, "markdown_text": "## Standard Occupational Classification (SOC)\n\nEach item in the 2018 SOC is designated by a six-digit code.\n\n- · Major group codes end with 0000 (e.g., 29-0000 Healthcare Practitioners and Technical Occupations).\n- · Minor groups generally end with 000 (e.g., 29-1000 Health Diagnosing or Treating Practitioners)-the exceptions are minor groups 15-1200 Computer Occupations, 31-1100 Home Health and Personal Care Aides; and Nursing Assistants, Orderlies, and Psychiatric Aides, and 51-5100 Printing Workers, which end with 00.\n- · Broad occupations end with 0 (e.g., 29-1020 Dentists).\n- · Detailed occupations end with a number other than 0 (e.g., 29-1022 Oral and Maxillofacial Surgeons).\n\n", "report name": "2019 Southeast Data Package" }, { "slide_number": 73, "markdown_text": "## North American Industry Classification System (NAICS)\n\nThe 2017 North American Industry Classification System (NAICS) is an industry classification system that groups establishments into industries based on the similarity of their production processes. It is a comprehensive system covering all economic activities. There are 20 sectors and 1,057 industries in 2017 NAICS United States.\n\nNAICS uses a six-digit coding system to identify particular industries and their placement in this hierarchical structure of the classification system. The first two digits of the code designate the sector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry.\n\nThe NAICS sectors and their two-digit codes are:\n\n| Code | Industry | Code | Industry |\n|--------|----------------------------------------------|--------|--------------------------------------------------------------------------|\n| 11 | Agriculture, Forestry, Fishing and Hunting | 53 | Real Estate and Rental and Leasing |\n| 21 | Mining, Quarying, and Oil and Gas Extraction | 54 | Professional, Scientific, and Technical Services |\n| 22 | Utilities | 55 | Management of Companies and Enterprises |\n| 23 | Construction | 56 | Administrative and Support and Waste Management and Remediation Services |\n| 31-33 | Manufacturing | 61 | Educational Services |\n| 42 | Wholesale Trade | 62 | Health Care and Social Assistance |\n| 44-45 | Retail Trade | 71 | Arts, Entertainment, and Recreation |\n| 48-49 | Transportation and Warehousing | 72 | Accommodation and Food Services |\n| 51 | Information | 81 | Other Services (except Public Administration) |\n| 52 | Finance and Insurance | 92 | Public Administration |\n\nA complete description of NAICS codes, industries and definitions can be found at https://www.census.gov/eos/www/naics/", "report name": "2019 Southeast Data Package" } ]