Up until about 2014 virtually all of the research related to STEM skills shortages (especially) in technology companies was done quantitatively, with the instrument of choice the survey method and the respondents that were selected employers, businesses, technology firms. The research was conducted by government organizations, business associations and all of the large consulting firms. Pick any one of these studies and you will find consistent agreement in the methodology (quantitative), the instrument (survey) and the respondents chosen (employers). Some of the studies were conducted by Accenture (2012), Boston Consulting Group (2013), Congressional Budget Office (2011), Deloitte (2011), Manpower (2012), McKinsey (2012), President’s Council of Advisors on Science and Technology (2012), Price Waterhouse Coopers (2012), and the US Chamber of Commerce (2006). The conclusions were all the same, that is, that the education system was failing to provide STEM-qualified job applicants to industries that needed these skills in order to grow and innovate.
Along with the survey conclusions, all of which contained high Cronbach’s (alpha) that measure internal consistency, recommendations for how to retool the education system to better inculcate STEM skills in students desiring to enter the workforce were suggested, explained and elaborated upon. Quantitative methods such as these are universally considered scientific; indeed evidence-based, positivist methodologies are only re-examined to the extent that the samples taken were (preferably) random, and sufficiently large enough to yield confidence to at least two standard deviations each side of the mean (95%). The researchers dutifully reported their survey results, along with every confirming statistic to support the validity of their conclusions. Consulting houses piled on to mimic their competitor studies and they all came to the same conclusions. Therein lies the rub.
The bias lies not in the survey purpose, sample size, or design. The flaw is in the respondents chosen. Although it may seem intuitive to select employers as the respondents – after all, who better to judge the STEM skills it takes to be successful on the job? The qualitative studies that followed these methods have debunked, demystified and completely derailed the validity of the quantitative survey conclusions. Research question: What if employers had an incentive to blame education and the root cause of the problem was actually in the domain and under the control of the employers themselves? How would a researcher conduct a study to determine whether validity exists for such a theory and hypothesis?
Dr. Peter Cappelli (2014) wrote his dissertation based upon all of these studies, plus a lot of tangential (tertiary) research, mixed in with data from government (Department of Labor for example), education, and industry. Rather than cross-sectional and quantitative, Dr. Cappelli approached the business problem with an historical lens to see how technology companies went from no STEM skills gap to an alleged STEM skills gap over a period of time (longitudinal). Qualitative researchers are criticized for lacking an evidence-based approach. Lacking experimental methodologies, randomized samples well-controlled and quantitative metrics, it is difficult for the interpretative researcher to garner the respect of colleagues in the peer-review process. Research methods have not matured yet to the point of comparability regarding credibility (internal validity), evidence, transferability (external validity), confirmability (objectivity) and reliability (dependability). Yet qualitative research methodologies in the interpretivist tradition, provide far more latitude when many nuanced exogenous variables, changing over the course of time, can bring a “best” persuasive description and explanation for what is going on with the business problem at hand based upon thorough exploratory research.
The skills gaps surveys utilized skill classifications. Dr. Cappelli, in his research approach asked questions, developed strong inductive and logical support through case examples to answer these questions, then bundled the entire package to illustrate and portray an entirely different set of dynamics that accounted for the alleged STEM skills gaps. Coincident and following his initial research, others (Charette, 2013) have approached the problem with similar tools and questions, the outcome of which has buttressed Dr. Cappelli’s seminal work, laid the ground for new theory, and consequently and likely qualifies Dr. Cappelli’s work as seminal in nature. In simple terms Dr. Cappelli searched the literature and found that problems largely caused by employers themselves were at the root of the STEM skills gap.
Case after case, data upon data, and analysis over time yielded the following results, all well supported by the careful sifting and interpretation of the evidence:
- Employers are unwilling to pay market-clearing wages for STEM skilled workers.
- Employers have largely abandoned their internal company training programs that were aimed at preparing new recruits for success on the job.
- Employers have increased their hurdle rates in terms of inflated educational and experience requirements for jobs that used to be performed by less educated, less skilled workers.
- Employers have a vested interest, an incentive to continue their practices above and to push the responsibility and problem solving unto the educational system. For example, these employer claims have the effect of cajoling the government toward a policy of increasing the number of H1-B visas granted so lower compensated STEM skilled recruit can be found in other countries.
Accenture. 2012. “Solving the Skills Paradox: Seven Ways to Solve Your Critical Skills Gap.”
Boston Consulting Group. 2013. “The U.S. Skills Gap: Could it Threaten the U.S.
Manufacturing Renaissance?” https://www.bcgperspectives.com/content/articles/lean_manufacturing_us_skills_gap_co uld_threaten_manufacturing_renaissance/.
Cappelli, Peter. 1995. “Rethinking the ‘Skills Gap’.” California Management Review 37(4): 108- 124. Cappelli, Peter. 1999. The New Deal at Work: Managing the Market-Driven Workplace. Boston: Harvard Business School Press.
Cappelli, Peter. 2003 “Will There Really Be a Labor Shortage?.”Organizational Dynamic 32(3): 221-233.
Cappelli, Peter. 2012. That Pesky Skill Shortage in Manufacturing. HR Executive. http://www.hreonline.com/HRE/view/story.jhtml?id=534354686.
Cappelli, P. (2014, August). Skill Gaps, Skill Shortages and Skill Mismatches: Evidence for the US. Retrieved from http://www.nber.org/papers/w20382
CBO. 2011. “CBO’s Labor Force Projections Through 2021.” Congressional Budget Office.
http://www.cbo.gov/sites/default/files/cbofiles/ftpdocs/120xx/doc12052/03-22- laborforceprojections.pdf. CVTS 2013. Continuing Vocational Training Statistics. Brussels: European Commission. Http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Continuing_vocational_tr aining_statistics
Charette, R. N. (2013). The STEM crisis is a myth. IEEE Spectrum. Retrieved from http://www.k12accountability.org/resources/STEM-Education/The_STEM_Crisis_Is_a_Myth.pdf
Deloitte. 2011. “Boiling Point? The Skills Gap in U.S. Manufacturing.” Manufacturing Institute. http://www.themanufacturinginstitute.org/~/media/A07730B2A798437D98501E798C2E 13AA.ashx.
Manpower 2012. The Talent Shortage Survey. http://www.manpowergroup.us/campaigns/talent- shortage-2012/pdf/2012_Talent_Shortage_Survey_Results_US_FINALFINAL.pdf
McKinsey. 2012. “The World at Work: Jobs, Pay and Skills for 3.5 Billion People.” McKinsey Global Institute.
President’s Council of Advisors on Science and Technology. 2012.
PWC. 2012. “Facing the Talent Challenge: Global CEO Survey.”
U.S. Chamber of Commerce. 2006. “The State of American Business 2006.” Washington D.C.