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Dashboard Confessional: The State of Data in Regional Development

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Brian Kelsey's keynote presentation at EMSI's 2015 National Conference in Coeur d'Alene, Idaho.

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Dashboard Confessional: The State of Data in Regional Development

  1. 1. Dashboard Confessional: The State of Data in Regional Development 2015 National Conference | September 22, 2015 Brian Kelsey Civic Analytics LLC http://civicanalytics.com @civicanalytics
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  3. 3. 3 Data availability: What should practitioners know? • Money attracts partners, but so can thoughtful analysis of readily available data. • Applied research in economic & workforce planning is art & science – focus on the story’s ability to motivate action. • Challenge now is maintaining focus in an increasingly data- obsessed environment.
  4. 4. 4 What data has taught me about people and places
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  6. 6. 6 • Raised $20,000+ from regional businesses to support applied economic research program. • Maintained participation and buy-in from C-level executives of telecom companies during onset of dot-com recession. • Viewed as unbiased source of value-added data/insight.
  7. 7. 7 Data is a value-added service that people will pay for and passes the market failure test for justifying public sector role. Lesson #1 Compelling stories using objective data and transparent analysis build trust and get stakeholders around the table. Lesson #2
  8. 8. 9http://www.compete.org/storage/images/uploads/File/PDF%20Files/Regional_Innovation_Guidebook.pdf
  9. 9. 10http://www.theatlantic.com/business/archive/2015/02/why-the-gap-between-worker-pay-and-productivity-is-so-problematic/385931/
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  11. 11. 13 Data trumps frameworks.Lesson #3 Regions may be right unit of analysis, but pretending jurisdictional boundaries or service areas don’t matter is naïve. Lesson #4 No amount of federal or state money will fill a leadership vacuum in a region. Lesson #5
  12. 12. 15http://indicatorsproject.com/
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  14. 14. 17 Call to Action Source: http://seveds.com/wp-content/uploads/2012/08/FINALCEDSReport.2013.pdf
  15. 15. 18 Call to Action  SMART Goals Source: http://seveds.com/wp-content/uploads/2012/08/FINALCEDSReport.2013.pdf
  16. 16. 19 SMART Goals Source: http://seveds.com/wp-content/uploads/2012/08/FINALCEDSReport.2013.pdf
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  18. 18. 21East Arkansas Planning & Development District http://eapdd.com
  19. 19. 22 Indicators can be useful communication device, but must be actionable. Lesson #6 Linking, leveraging, & aligning economic, workforce, & education is impossible without access to the right data. Lesson #7 Data availability is empowering (nudging) planners toward commitment to change. Lesson #8
  20. 20. 24http://startup-ecosystem.compass.co/ser2015/
  21. 21. 25 Tech Talent: Labor Market Overview • 108,310 total jobs in tech sector • 67,546 jobs in “core” tech talent occupations w/ in-demand skills • ~2,500 to 3,500 job openings in core tech talent occupations are expected per year in Austin for 2014-2024 time period* • ~1,500 degrees and certificates in core related programs awarded by Austin area schools annually How are we defining “tech”? ATC generally follows the methodology used by TECNA/CompTIA/TechAmerica for their annual Cyberstates report.* It currently includes 49 industries. Austin’s largest tech sectors ranked by minimum of $1 billion contribution to regional gross domestic product: #1 Computer & Peripheral Equipment #2 IT Services & Applications #3 Internet & Telecommunications #4 Semiconductors #5 Software Source: EMSI, 2014. Jobs include self-employment. *Job postings are unique, de-duplicated average monthly openings advertised online during March 2014-March 2015 and include job openings at tech and non-tech businesses (i.e. total demand for core technical workers). See full Tech Talent Report for details and explanation of methodology used for estimates.
  22. 22. 26 3 12 19 9 8 Not difficult Somewhat difficult Difficult Very difficult Extremely difficult 70% reported moderate-significant difficulty in hiring but majority confident in ability to grow in Austin Source: ATC Tech Talent Employer Survey. 2 5 15 16 8 5 I don’t know Not confident Somewhat confident Confident Very confident Extremely confident ≥ Difficult: 70% ≥ Confident: 57% How confident are you that Austin will be able to meet your future workforce demand? Overall, how difficult is it to find qualified people to fill job openings at your company in Austin?
  23. 23. 27 Employees Respondents Number* Difficulty Average Confidence Average 1 to 10 19 3.1 2.8 11 to 50 15 3.5 2.5 51 to 125 7 3.6 2.4 126 to 500 6 2.5 2.8 501+ 3 2.3 3.7 Total (Ans) 50 3.1 2.7 Source: ATC Tech Talent Employer Survey. Second-stage firms have reached a growth stage of $1M to $50M in receipts and 10 to 100 employees. For more on second-stage company research see Edward Lowe Foundation at http://edwardlowe.org/who-we-serve/secondstage. *Complete responses only (n = 50). Differences not statistically significant. 1 = Not difficult 2 = Somewhat difficult 3 = Difficult 4 = Very difficult 5 = Extremely difficult 1 = Not confident 2 = Somewhat confident 3 = Confident 4 = Very confident 5 = Extremely confident 0 = I don’t know 2nd Stage/Growth Stage companies may be feeling disproportionate impact of perceived shortage Overall, how difficult is it to find qualified people to fill job openings at your company in Austin? How confident are you that Austin will be able to meet your future workforce demand? 31% respondents reported that unfilled jobs having harmful to extremely harmful effect. Not harmful/didn’t know: 33%
  24. 24. 28 Tech Talent Pipeline Challenges • 42% of respondents require at least 5 years of work experience for job applicants to be considered qualified for technical jobs. • 25% of respondents don’t hire recent college graduates and 24% don’t offer internships. • Only 12% of respondents reported that they consider recent college graduates qualified, or don’t ask for min years work experience. Source: ATC Tech Talent Employer Survey.
  25. 25. 29 Cost of living is (still) lower in Austin, but salary gaps are significant with other leading regional markets Median Wage Bottom 10% Top 10% San Jose $116,314 $74,110 $178,693 Seattle $102,066 $66,706 $148,824 Washington DC $101,712 $62,899 $154,565 San Francisco $100,547 $63,398 $155,480 Boston $96,616 $61,797 $148,387 Durham-Chapel Hill $88,691 $56,992 $135,886 Raleigh $83,054 $53,955 $123,386 Dallas $81,848 $50,710 $127,150 Austin $80,454 $49,150 $127,442 Salt Lake City $75,254 $47,424 $111,155 National $81,037 $49,275 $129,480 Table shows wage comparisons for core occupation (19) jobs in tech as of 2013 (latest available). Bottom 10% and Top 10% refer to the wage level signifying that 10% of all jobs pay below (or above). Study Follow-Up: We need better grasp on impact of lower salaries in Austin to understand how talent supply is affected – e.g., where are most job offer declines occurring, early-career, mid, senior? Source: EMSI, U.S. Bureau of Labor Statistics. Data is for 2013. Includes self-employment.
  26. 26. 30 Tech skills should be CTE priority in K-12 but current offerings in Austin not aligned w/ employer needs ISD Certifications Offered Avg N/A Network+ 1.9 44% Cisco Net Associate (CCNA) 1.8 47% A+ 1.8 50% Cisco Entry Net Tech (CCENT) 1.7 47% Internet & Comp Core Cert (IC3) 1.7 48% Sun Cert Java Associate (SCJA) 1.6 47% Adobe Dreamweaver 1.5 48% Internet Webmaster (CIW) 1.5 48% Strata IT Fundamentals 1.3 55% TestOut PC Pro 1.3 54% 1 = Not important 2 = Somewhat important 3 = Important 4 = Very important 5 = Extremely important N/A = Not applicable 60% of respondents reported that all certifications currently offered in Austin area school districts were not applicable or not important. Source: ATC Tech Talent Employer Survey. List of certifications offered in Austin area school districts was provided by E3 Alliance (October 2014). Scores were averaged from number of respondents providing a rating or answering N/A (i.e. blank responses were excluded). Employer Needs Avg JavaScript 3.8 Linux 3.5 Java 3.4 C++ 3.1 PHP 3.1 Python 3.1 Ruby 3.0 C# 2.9 Perl 2.6 Haskell 2.0 Others: Lisp 1.7/40% Go 1.5/45% Write-ins: Objective-C Swift Career & tech education (CTE)
  27. 27. 31 Data trumps frameworks, and also buzzwords (skills gap). Lesson #9 EMSI deserves credit for anticipating how data can empower economic/workforce practitioners to drive change in regions. Lesson #10
  28. 28. 33 We’ve made great progress breaking down data and program silos. Call to action for teachers/trainers: helping next generation of applied researchers raised on infographics, dashboards, and “big data” learn how to ask good questions. Source: xkcd
  29. 29. 7600 Burnet Road, Suite 108 Austin, Texas 78757 @civicanalytics http://civicanalytics.com

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