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Data Data Data! How to use free data tools to create workforce development strategies
The document presents a workforce analysis strategy involving the use of free data tools to develop data-driven strategies for workforce development. It discusses various data sources, methodologies for analyzing economic and workforce data, and provides checklists for identifying key industries and occupations, as well as addressing barriers to employment. Additionally, it covers resources for demographic analysis and highlights the importance of tracking trends and data verification.
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Data Data Data! How to use free data tools to create workforce development strategies
- 1. #NYATEPFALL15 Data, Data, Data! Presentedby Rob Camoin and Ian Flatt How to use free data tools to create workforce development strategies
- 2. #NYATEPFALL15 Workforce Analysis Presentation Goals: •Present variety of quality data sources • Identify ways they can be used to support your work Purpose of Workforce Analysis: • Develop-data driven strategies • Strategically deploy resources to most high need industries and individuals
- 3. #NYATEPFALL15 Questions •Do you useeconomic/workforce data? •If yes, for what purpose? (advising clients, developing strategies, etc.?) •How could workforce and economic data support your work?
- 4. #NYATEPFALL15 Workforce Analysis Uses: • Identifygrowth industries • Identify growth occupations • Direct clients to training for in-demand occupations with strong wages • Identify populations with barriers to employment • Track progress to strategic goals
- 5. #NYATEPFALL15 Basic Guidelines • Comparedata to benchmarks – state, US, or other similar communities or regions • Track most recent data, trends over time, and projections • Verify data with employers and ED partners • Review regularly and make appropriate updates • Keep an eye on current events and trends – could change what the data is telling you
- 6. #NYATEPFALL15 Definitions North American IndustryClassification System (NAICS) Codes • Standard used by Federal statistical agencies in classifying business Standard Occupational Classification (SOC) Codes • System is used by Federal statistical agencies to classify workers into occupational categories • All workers are classified into one of 840 detailed occupations according to their occupational definition
- 7. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
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- 9. #NYATEPFALL15 US Cluster MappingProject • Product of Harvard Business School and US Economic Development Administration • Provides in-depth information about industry clusters • Data about changes in employment, unemployment rates, labor force participation, and wages • Can create custom regions (e.g. multi-county WF regions) http://www.clustermapping.us/
- 10. #NYATEPFALL15 US Cluster Mapping Strengths: •Easily download data • Can create custom regions • Variety of data • Divides clusters between “Traded” and “Local” Limitations: • Not always clear what NAICS codes the clusters refer to (check the definitions if not sure)
- 11. #NYATEPFALL15 Map a widerange of variables At the county, state, economic area, or MSA levels Select date range Create custom regions
- 12. #NYATEPFALL15 Charts summarizes employment and demographicdata More detailed charts measuring the economic health of the region Detailed information about employment in industry clusters
- 13. #NYATEPFALL15 Learn about key employment,wage, and economic data And more…
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- 17. #NYATEPFALL15 US Cluster MappingProject • Using data available from US Clusters Mapping, we can easily identify: • The largest industries
- 18. #NYATEPFALL15 US Cluster MappingProject • Using data available from US Clusters Mapping, we can easily identify: • The largest industries • Industries that added the most jobs
- 19. #NYATEPFALL15 US Cluster MappingProject • Using data available from US Clusters Mapping, we can easily identify: • The largest industries • Industries that added the most jobs • Fastest growing industries
- 20. #NYATEPFALL15 • Track Changesin Overall Employment US Cluster Mapping Project
- 21. #NYATEPFALL15 US Cluster MappingProject • Track Changes in Overall Employment • Track changes in wages
- 22. #NYATEPFALL15 US Cluster Mapping: OtherAvailable Information • Shift Share Analysis (industry competitiveness) • Location Quotient (industry specialization) • Compare region to other geographies • Identify communities with similar employment trends – can be good for future benchmarks • Demographic information • Definitions of clusters (i.e. the NAICS codes included) provided
- 23. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
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- 25. #NYATEPFALL15 NYS Department ofLabor • http://labor.ny.gov/stats/index.shtm • Offers projected changes in employment for: • Occupations • Industries • Provides data related to wages, etc. • Provides labor force and unemployment data by county, LWIA, and region
- 26. #NYATEPFALL15 Employment and wages byoccupation – available for regions only Employment and wages by industry (past and current) – available at county, LWIA, MSA, and regional levels Projections available statewide and for regions
- 27. #NYATEPFALL15 Industry Data Strengths: • Currentand historic data • Provided for state, regions, LWIA, and counties • Average wages assessed
- 28. #NYATEPFALL15 Industry Data Limitations: • Dataprovide at 3 level NAICS code – not specific • Industry employment projections provided for state and regions ONLY
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- 30. #NYATEPFALL15 Occupation Data • Showsdetailed occupations • Breaks out employment demand between new and replacement demand • Detailed wage information • Skill requirements and typical education requirements • Categorizes occupations by future employment prospects based on growth rates and number of openings • Available for state and regions ONLY
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- 33. #NYATEPFALL15 Labor force size,unemployment rates and numbers available by state, region, LWIA, MSA, and county
- 34. #NYATEPFALL15 Labor force peaked in2010 at 179,400 Currently around 166,100 – a decrease of 13,000 from peak
- 35. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
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- 37. #NYATEPFALL15 American Community Survey •Socioeconomic and demographic data – past and current • Age • Education • Income • Veteran status • Number of individuals with disabilities http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
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- 39. #NYATEPFALL15 Easily find dataon: age, sex, income, education, housing costs, languages spoken, and veterans
- 40. #NYATEPFALL15 Can’t find the informationyou’re looking for? Try “Advanced Search” Browse topics you are interested in
- 41. #NYATEPFALL15 Veteran Employment • Nearly9% unemployment rate • Nearly 7% live in poverty Labor Force Participation 75.3% Unemployment Rate 8.7% Poverty Rate 6.9% Veterans - ACS 2009-2013 Survey
- 42. #NYATEPFALL15 Individuals with aDisability • In the US, individuals with disabilities account for about 11% of unemployed and over 25% of people not in the labor force • Only account for 5% of employed individuals % of People with Disabilities % of Total Population Employed 33% 5% Unemployed 8% 11% Not in Labor Force 59% 26% People with Disabilities
- 43. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
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- 45. #NYATEPFALL15 Opportunity Index • Rankscommunities based on income, education, health indicators, availability of doctors, and a variety of other factors http://opportunityindex.org/ Strengths: • Available by county and state • Easily see how county compares • Regularly updated • Easy to view snapshot or data dashboard
- 46. #NYATEPFALL15 Opportunity Index • Rankscommunities based on income, education, health indicators, availability of doctors, and a variety of other factors Limitations: • Difficult to download (approve requests to download data on a case-by-case basis) • Cannot make custom regions
- 47. #NYATEPFALL15 Counties with high scoresare in dark blue
- 48. #NYATEPFALL15 Select to mapa variety of variables
- 49. #NYATEPFALL15 • “Report Card”Style Format • Breakdown and comparison to state and US • Detailed economic, education, and demographic data
- 50. #NYATEPFALL15 • See howdata has changed over time • Detailed education and demographic info • One of the only sources for “disconnected” or “idle youth”
- 51. #NYATEPFALL15 The unemployment rate inthis county has decreased since 2011, however the median income has remained stagnant and the poverty rate has increased The % of households spending more than 30% of income on housing costs has increased – could indicate a growing need for workforce housing See how data has changed over time
- 52. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
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- 54. #NYATEPFALL15 On The Map •Provides information about commuting patterns • Reveals the kinds of jobs workers commute to or from an area for • Answer questions: • Do employers need to recruit from outside of the area for fill jobs? • Do workers need to leave your area to find suitable jobs? http://onthemap.ces.census.gov/
- 55. #NYATEPFALL15 On The Map •Is your area a labor importer or exporter? • Saratoga exports about 24,000 more workers than it imports • About 36,000 workers live and work in Saratoga County
- 56. #NYATEPFALL15 On The Map •Most Saratoga residents commute to Albany for work • After Albany, about 11% are employed in the City of Saratoga Springs
- 57. #NYATEPFALL15 On The Map •Most Saratoga residents are employed in Saratoga Springs • Residents of Schenectady, Troy, and Glens Falls commute to Saratoga for work
- 58. #NYATEPFALL15 Workforce Analysis DataChecklist Largest industries Fastest growing industries Industry wages Top occupations Wages Education requirements Unemployment rates Labor force participation Age Income Education “Disconnected Youth” Veterans Individuals with disabilities Commuting patterns
- 59. #NYATEPFALL15 Other Resources • CornellCooperative Extension: Demographic information and county profiles • Detailed Migration Data: University of Wisconsin • U.S. HUD: free data on all things housing • MIT Living Wage Calculator: find out what the living wage is in your community • EMSI: proprietary source for economic and workforce data (not free)
- 60. #NYATEPFALL15 Thank you! • GiveRob or Ian your business card to receive the PowerPoint by email! • You can also find it on our blog Questions?
Editor's Notes
- #2 Questions for audience: Have you used economic and labor force data in the past? For what purpose (strategy, advising clients, etc.)? Are you able to find the data you need to perform your job? How comfortable are you using data? What are the greatest opportunities to incorporate data into your job?
- #6 Benchmarks provide context for changes – if employment grew by 2% in your community, how does that compare to other communities? Is that strong or weak growth? Meet with employers and talk about the trends you are seeing in data – are they experiencing similar changes Meet with your ED partners – are they noticing similar trends? Don’t let all the work go to waste – regularly update your data and revisit your strategies – are they still appropriate? Don’t get bogged down in the data – things going on in the real world can shift trends or change projections. For example, an industry could go from adding jobs to shedding jobs due to automation
- #8 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis
- #12 Quickly compare your county or region to others – using the map function Map a variety of variables – including employment, wages, industry specialization, poverty rate, and population growth
- #14 Data is presented in quality, professional charts that can easily be inserted into annual or board reports
- #16 In the Capital Region, the Financial Services and Information Technology clusters have the highest wages – at $116,000 and $98,000 respectively – these are near the US averages
- #17 Once you have identified the industry clusters important to your region, find out which sub-clusters in that industry cluster account for the most employment, fastest employment growth, and highest wages
- #18 Largest industries – can have huge demand for new workers Replacement demand is often a major driven of demand for workers The foundation of economy – large disruptions in your top industries can have ripple effect throughout economy
- #19 Shows the industries that have the most demand for new workers Just b/c an industry is declining in employment does not mean it should be ignored Could still have demand for new workers due to people retiring May be reducing its workforce because of automation – while it may not need as many workers, it may need workers with higher skill levels
- #20 By observing the % of change in the industry – that is, how much employment in the industry changed as a percentage of the original employment level – you can see which industries have an especially high demand for workers, compared to the original employment levels. While sometimes, high growth rates in an industry can be associated with industries that still have a relatively small workforce. A high employment growth rate in an industry can have ramifications for the types of training that need to be provided – for example, if an industry grows from 50 to 100 workers (a growth rate of 100%), the educational institutions in the area may not have the capacity or the programs in place to train that number of workers
- #24 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis
- #28 For example, we can learn that employment in Food Manufacturing is projected to grow by 410 jobs in the Southern Tier region – we do not know specifically which industries are projected to grow
- #29 For example, we can learn that employment in Food Manufacturing is projected to grow by 410 jobs in the Southern Tier region – we do not know specifically which industries are projected to grow
- #30 Get a sense of the industries that are projected to add the most jobs Unfortunately – not at a very detailed level of industry classification However, once you know the industries projected to add the most jobs, you can find out more information about the cluster using the US Cluster Mapping
- #35 Herkimer/Madison/Oneida LWIA
- #36 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis
- #44 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis
- #53 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis
- #59 These are the types of data that we have found most useful when conducting economic, workforce, and labor market analyses Will not use every data point for every type of analysis