Is Education to Blame for the STEM Skills Gap?

1Up 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.

2Along 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.

3The 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?

4Dr. 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.

5The 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:

  1. Employers are unwilling to pay market-clearing wages for STEM skilled workers.
  2. Employers have largely abandoned their internal company training programs that were aimed at preparing new recruits for success on the job.
  3. 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.
  4. 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?” 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.

Cappelli, P. (2014, August). Skill Gaps, Skill Shortages and Skill Mismatches: Evidence for the US. Retrieved from

CBO. 2011. “CBO’s Labor Force Projections Through 2021.” Congressional Budget Office. laborforceprojections.pdf.
CVTS 2013. Continuing Vocational Training Statistics. Brussels: European Commission. Http:// aining_statistics

Charette, R. N. (2013). The STEM crisis is a myth. IEEE Spectrum. Retrieved from

Deloitte. 2011. “Boiling Point? The Skills Gap in U.S. Manufacturing.” Manufacturing Institute. 13AA.ashx.

Manpower 2012. The Talent Shortage Survey. 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.

Disrupt or Die!

Disrupt or Die

Theories of Disruptive Innovation and Value Innovation

Rodd Mann

Capella University

Doctor of Business Administration – Leadership (candidate)

Disruptive InnovationTheories of Disruptive Innovation began with the publication of Clayton M. Christensen’s much-heralded book, “Innovator’s Dilemma,” (Christensen, 1997). The Webster Thesaurus describes innovation as “change, alteration, revolution, upheaval, transformation, or metamorphosis. Technological innovation refers to a new method, idea, or product designed to save energy. In the book Mr. Christensen makes a distinction between what he refers to as “sustaining” and “disruptive” technologies.

The first deals with the more incremental improvements in technologies that a firm undertakes within their existing markets and among their existing customers. On the other hand, “disruptive” technologies primarily refer to the innovations that are more revolutionary, going well beyond the metronome of continuous improvements in the form of sustaining innovations. The disruptive category includes new technology that although it may have very little initial market acceptance and impact, it goes on to displace the technologies that were established, and eventually becomes the new normal.

USBAn example of a disruptive technology is Flash (NAND) memory. Productized in 1988, flash memory provides data storage in the form of secure digital (SD) cards for cameras, universal serial bus drives (USB) for connection to computers, and solid-state (SSD) internal and external storage drives in lieu of traditional hard disk drives. The new technology was too expensive initially and in fact cost ten times as much to store a bit of information in flash memory as it did on a platter in a hard disk drive. Interestingly the hard drive (HDD) technology beginning in the 1970’s disrupted tape drives. Even though the same ratio of 1/10th the cost to store a bit of information on a tape drive as a hard drive, the disruptor, in this case hard drives (HDD), effectively and substantially reduced the market for tape drives and relegated them to library and archival applications in high-end enterprises. A number of tape drive manufacturers went out of business beginning in the 1990’s, and today only Quantum (Colorado) remains in the United States.Zip

As the cost of Flash Memory has decreased markedly over the past twenty years, the total storage market is beginning to be impacted by this disruptive technology. When asked during an interview, “How are you going to compete with this new flash technology?” then Chief Operating Officer Bill Watkins of Seagate Technology responded, “We own most of the IP (intellectual property, patents) from the motherboard all the way to any storage peripheral, so if flash begins to eat into our market share we will sue.” Since that time hard drive manufacturers Seagate and Western Digital have acquired solid-state drive companies and invested heavily in research and development. Today these hard drive manufacturers have a full product portfolio of flash based storage devices along with their traditional hard drive product line-up.Seagate

WDCToshibaChristensen argues that these disruptive innovations are the cause of failure for the firms that are impacted by the new technology interloper. (Christensen, 1997). A follow-on to disruptive technology research, “value innovation” derives from the notion of disruptive innovation, but focuses upon what is happening in the current competitive environments so that new ways to compete in new markets and opportunities might be developed. The focus is on innovation in both cases, without which a given firm will likely miss out on these opportunities or be too late to participate.

When Darwin’s Theory of Evolution was first proposed, it quickly led to applications far and beyond the original development of species (Hull, 1973). Today we talk of not only biological evolution but also social evolution and numerous other evolutionary metaphors – “survival of the fittest” can fit any situation we choose today.

Similarly, Mr. Christensen’s thesis has evolved a virtual cottage industry of conferences, seminars, testimonials and consultants willing to advise companies how to adapt “disruptive technology” focus in their firm, school, church, government or any organization. Today you can find scholarly writings on “Disruption Innovation from Emerging Economies” (Markides, 2012), “Innovation for the Bottom of the Pyramid,” (Prahalad, 2012), “Cost Innovation,” (Williamson, 2012), and “Reverse Innovation,” (Govindarajan and Trimble, 2012).

But problems with the theory and challenges to the underlying theoretical assumptions are beginning to show cracks inherent in the model. First of all, Mr. Christensen did not utilize scientific methods in the design of his study. Rather, he handpicked several examples he hoped would demonstrate the validity of his thesis. His conclusion was that he now understood why a given company ultimately fails. He goes on in his book to claim that by following his definitions of “disruptive technology,” a firm’s demise can be predicted.

The theory doesn’t attempt to address disruptive impacts in far-flung countries, only the impact on ‘established markets.’ What constitutes sustaining versus disruptive technology? How innovative does it have to be? Should it be revolutionary, as in the case of the smart phone? Or can it be evolutionary, as in the case of steadily improving technologies in handheld digital devices over the past ten years? Many innovations are excessive, some appeal only to the very wealthy, should they demonstrably improve our standard of life or significantly lower the cost of living?

“Disruptive Innovation” appears to be simply yet another business model characterization, a business book that seeks to explain and predict but in fact does neither. Only recently several new business strategies have been proposed, ostensibly to explain and even predict business activity and potential success or failure:

  1. In “Competitive Strategy,” (Tom Porter, 1980) discussed three primary determinants of success: Cost Leadership, Differentiation and Focus.
  2. Yet one more popular model dealt with the theory of making ‘rational choices’ (Nau, 1999). Certain tests determine whether a manager is considered to be making rational choices. The underlying assumption with ‘rational choice theory’ is that the decision-maker has the knowledge of the important exogenous variables impacting their environment. They are considered ‘individually rational’ if their choices satisfy criteria described as independent, and they are considered ‘collectively rational’ if they can go beyond ‘individual rationality’ to also include a common denominator of knowledge and prior-held beliefs.
  3. Another business model that was popularized was called “game theory.” Game theory also proposed to address a given firm’s strategy through mathematical models of the dynamics a decision-maker utilizes in all areas including both cooperative and conflicting strategies under consideration. (Wikipedia)

In fact Christensen was so convinced that he was onto something that could and would be validated as a predictive tool with the passage of time, he launched the “Disruptive Growth Fund” in 2000 (Lepore 2014). After losing more than half of its value in less than one year the fund was closed. In a Business Week interview (MacGregor, 2007) Christensen, relying upon his own theory, said that Apple could not succeed with the iPhone, “…history speaks pretty loudly on that.” Apple went on to sell $1.5 billion worth of their new smartphones in just the first five years. So apparently “disruptive technologies” are clearly identifiable all right, but only in the rear-view mirror. There is no demonstrable predictive quality to the theory. But whether we call past successes disruptive technologies, breakthrough, game-changers or anything else, the tag is simply a characterization, not a science. History also tells us something about successful entrepreneurs. They are often bright risk-takers who largely ignore the past and push on through with their vision anyway. Consider for a moment Elon Musk and Tesla. What would disruptive theory have predicted in his case?

The doctoral thesis that began with work Mr. Christensen had done with Mr. Bower (1995) focused upon the disk drive industry, specifically a company named “Seagate Technology.” Christensen notes that Seagate delayed moving from 5 ¼ inch drives to 3 ½ inch drives primarily because their largest customer, IBM, saw no need for the smaller form factor in their own products. At this time there were almost 100 companies participating in the disk drive market (see Appendix A). Although Christensen also examined several other product characteristics of disk drives, he did not attribute issues to any of the other significant variables that can account for the acceptance or rejection of a disk drive by the consumer:

  1. Weight
  2. Capacity
  3. Seek time / RPM
  4. Failure data / Quality / Life of the drive
  5. Cost
  6. Applications (consumer, mobile, desktop, enterprise)
  7. Power usage
  8. Number of electro-magnetic sub-assemblies in the bill of material
  9. Speeds and feeds
  10. Compatibility

So what did happen to Seagate since Mr. Christensen’s blockbuster book chose Seagate Technology as his “magnum opus” “or crowning achievement” in terms of his hand-picked cases? Today Seagate has a market capitalization of $20 billion (Yahoo Finance). For the past couple years Seagate has averaged $14 billion in revenue and $2 ½ billion in operating income. The firm generates over $3 billion per year in cash flow from operations. And only two other companies remain in the business today: Western Digital Corporation and Toshiba. As an oligopoly, in spite of the commodity nature of disk drives, all three disk drive companies generate significant revenues and profit.

What accounts for Seagate’s success? It turns out that the answer is far more mundane than the clarion call of “Disrupt of Die!” Seagate focused on technology, largely through its acquisition strategy (See Appendix B), getting into the enterprise market with its acquisition of Control Data. Being first to market with a disruptive format had nothing to do with the success of the three remaining disk drive makers. Western Digital used to describe itself as a “fast follower,” a characterization their then Chief Executive Officer, Matt Massengill, proudly and often repeated on the quarterly financial analysts’ calls. Indeed the survivors were the ones that just kept on doing better and better – incremental evolutionary improvements in technology, efficiency, cost, market share, and flexibility. Not disruptive technologies, nor sustaining technologies, nor value innovation, nor focus, nor any other erstwhile popular business competitive strategy that has been proposed, heralded, then later discarded over time when a new idea takes hold. The companies that could have been characterized for their blockbuster novel and disruptive technologies, Iomega’s Zip Drive for example, are today all out of business. The failures of all of these disk drive companies had little to do with failing to embrace new “disruptive technologies,” and a lot to do with plain old bad management. In the case of Micropolis, they were fraudulently shipping bricks in the disk drive boxes and recording these shipments as revenue. Poor management indeed.

Companies worry about disruptive technologies, because if they don’t, they will lose their competitive edge and perhaps even go out of business. But just as the Boston Consulting Group divides company businesses into four categories within a product portfolio: “Question marks,” “dogs,” “stars” and “cash cows,” each business requires a completely different management and operating strategy. Certainly the “stars” must be guarded or their flank will be attacked by disruptive technologies. But the “question marks” are these newer technologies, and every company should be doing research and development to identify the “next best thing.” Some will bet correctly, most will not. Why? Pride in the current technology, or hubris, can blind the management team to a technology that will make theirs’ obsolete. General Motors, Ford and Chrysler could have developed a blockbuster, high-end electric car. But they didn’t. It takes upstarts, bright, entrepreneurial risk takers that feel in their gut that this is the next big thing. IBM lost the PC business to Compaq primarily on portability. Compaq lost the PC business to Dell primarily on the low-cost, online configure-to-order model Dell offered. And Dell is losing the PC business to other digital device manufacturers with newer, sleek products that you can touch and feel in retail stores. The beat goes on.

A great management team can take a bad business and make it successful, just as a bad management team can take a good business and cause it to fail. That is the root cause of success or failure of businesses, not “disruptive technology.” And the second lesson is that management teams inevitably get blinded by their own hubris, unable to see that the current technology, of which they are so understandably proud, is about to get trampled and taken out. Bad Mgmt




Bower, J. L., & Christensen, C. M. (1995). Disruptive technologies: catching the wave. Harvard Business Review Video.

Christensen, C. (2012). The Innovator’s Dilemma. 1997. Harvard Business School Press, Boston, MA.

Govindarajan, V. and Ramamurti, R. (2011) Reverse Innovation, Emerging Markets and Global Strategy. Global Strategy Journal, 1, 191–205.

Hull, D. L. (1973). Darwin and his critics: The reception of Darwin’s theory of evolution by the scientific community.

Lepore, J. (2014). The Disruption Machine: What the gospel of innovation gets wrong. The New Yorker.

Markides, C. C. (2012). How Disruptive Will Innovations from Emerging Markets Be? MIT Sloan Management Review, 54(1), 23.

McGregor, J. (2007). Clayton Christensen’s Innovation Brain. INNOVATION.

Nau, R. F. (1999). Arbitrage, incomplete models, and interactive rationality. Durham, NC: Duke University.

Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. FreePress, New York.

Prahalad, C. K. (2012). Bottom of the Pyramid as a Source of Breakthrough Innovations. Journal of Product Innovation Management, 29(1), 6-12.

Williamson, P.J. (2010) Cost Innovation: Preparing for a ‘Value-for-Money’ Revolution. Long Range Planning, 43, 343–353.


Appendix A

List of disk drive manufacturers since the 1980’s no longer in business today:

  1. Alps Electric
  2. Amcodyne
  3. Ampex[
  4. Apple
  5. Atasi Corp.
  6. Areal Technology
  7. Aura Associates
  8. Avatar Systems
  9. BASF
  10. Bryant Computer Products
  11. Burroughs Corporation
  12. CalComp
  13. Calluna Technologies
  14. Century Data
  15. Cogito Systems
  16. Comport
  17. Computer Memories Inc.
  18. Conner Peripherals
  19. Conner Technologies
  20. Control Data Corporation / Imprimis
  21. Cornice LLC
  22. Data General
  23. Data Products
  24. Data Recording Instruments
  25. Data Storage International
  26. Diablo Systems
  27. Digital Equipment Corporation
  28. DZU
  29. Epson
  30. Evotek
  31. ExcelStor Technology
  32. Fuji Electric
  33. Fujitsu
  34. General Electric
  35. Gigastorage
  36. Halo Data
  37. Hewlett-Packard
  38. Hitachi
  39. Hitachi Global Storage Technologies
  40. Hokushin Electric Works
  41. Honeywell Bull
  42. IBM
  43. Information Storage Systems
  44. Integral Peripherals
  45. International Memories
  46. Iomega
  48. JT Storage
  49. JVC
  50. Kalok
  51. Kyocera
  52. LaCie
  53. LaPine Technologies
  54. Marshall Laboratories
  55. Matsushita
  56. Maxtor
  57. Memorex
  58. Microcomputer Memories
  59. Micropolis Corporation
  60. Microscience International
  61. MiniScribe
  62. Ministor Peripherals
  63. Mitsubishi
  64. NEC
  65. Newbury Data Recording
  66. Nippon Peripherals
  67. Nomaï
  68. Olivetti
  69. Philips
  70. Plus Development
  71. Potter Instrument
  72. PrairieTek
  73. Priam Systems
  74. Quantum Corporation
  75. Raymond Engineering
  76. Rodime
  77. Sagem
  78. Samsung
  79. Seiko Epson
  80. Sequel
  81. Siemens
  82. Sony
  83. Storage Technology Corporation
  84. Syquest
  85. Tandon Corporation
  86. TEAC
  87. Texas Instruments
  88. Tulin Corporation
  89. Venturi International
  90. Vertex Peripherals
  91. Wang Laboratories