Udacity, the online education company, recognized an inefficiency in the supply chain for highly technical labor that many firms face today. This inefficiency is rooted in the existing upstream suppliers of that labor (e.g. universities) and has been exacerbated by the increasing digitalization of the workforce. In 2013, Udacity purposefully pivoted to a strategy that explicitly addressed this inefficiency by offering alternative education programs and credentials that cut the lead time in the supply chain for highly technical talent significantly.
Context: Digitalization and “Skill-Biased Technical Change”
Nearly a decade ago, Harvard labor economists Claudia Goldin and Larry Katz popularized a model called “skill-biased technical change” that helped explain why returns to labor in some parts of the labor market increase more than others . As firms innovate and develop products and services that leverage advanced technical methods to stay competitive and grow, the relative importance of technically trained workers rises commensurately. The “technical-change” that has taken place over the past 30 years has prompted firms to increasingly demand labor that is highly skilled – particularly in terms of digital skills. The upshot is that the price of labor with the “right” technical skills is becoming relatively more expensive for firms.
Take for example artificial intelligence and machine learning specialists – a highly technical occupation experiencing impressive demand today (growth in job postings for these positions was up 16% from the previous year in 2016) . When many firms believe it’s a strategic necessity to acquire AI/machine learning specialists and the pool of workers that have that specialized skill set is limited, firms will compete with each other to acquire that talent. The outcome of this competition is higher compensation for AI/machine learning specialists and higher labor expenses for firms.
The Challenge Firms Face with Their Supply Chains for Labor
Why is there a dearth of highly trained technical talent? In large part, because the lead times in the “supply chains for labor” that firms face are incredibly long. Human capital is similar to physical goods in that it needs to be sourced and procured in a way that aligns with the strategic aims of the firm. Any firm that employs workers has a “supply chain for labor” in the same way that a firm has a supply chain for the products it produces. When a firm uses this supply chain “lens” to think about its pipeline of human capital it can reap competitive benefits .
But why the long lead times for technical talent? In a large part, it comes back to the upstream suppliers of that technical talent: colleges and universities. The number of graduate degree programs focusing on AI/machine learning methods is limited, and where they do exist the time from acceptance to graduation is typically over two years. With only one type of upstream supplier of AI/machine learning specialists, there is a 2-3-year lag from when the “order” is put out into the labor market (i.e. the increased hiring demand) to when it can be “filled” by the upstream supplier (i.e. graduates of programs).
Udacity’s Insight and Its Shorter-Term Strategy
How could this 2-3-year lead time be cut down? Enter Udacity.
The challenge that Udacity faced in its early days was figuring out a profitable business model that supported its massive online course products . What if realized over the past few years is that there was an opportunity to essentially be a more efficient upstream supplier in the supply chain for highly technical labor and, in doing so, offer real value to firms, not just workers.
Starting in 2013, Udacity began to offer a fast way to educate highly skilled workers in the particular skills that firms demanded . Now, instead of waiting 2-3 years for the next graduating class of one of the few official degree-granting programs, a firm looking for highly technical labor could source talent directly from the graduating ranks of Udacity’s programs and reap the associated competitive advantages much quicker (conditional on Udacity’s education programs being similar in quality to those of official degree-granting programs). Udacity’s “Nanodegrees” – a form of certification that doesn’t meet official US degree standards but is increasingly recognized by employers as an indication of a quality education – takes only 6-12 months to complete. Udacity’s current AI Engineer Nanodegree takes 9 months to complete a total cost of $2,400.
Thinking Ahead: Udacity’s Longer-Term Strategy
As highly technical labor is increasingly demanded by firms because of digitalization (and as those firms increasingly apply the supply chain “lens” to their human resource needs), Udacity should focus on both innovating with its education programs to further cut down lead times and securing relationships with firms downstream the supply chain for highly technical labor.
Questions That Remain…
Does Udacity’s value proposition (as outlined above) only make sense for certain types of skilled labor? How should Udacity think about which skillsets or occupations to focus on moving forward?
 Goldin, Claudia and Katz, Lawrence. “The race between education and technology” Belknap Press of Harvard University Press. 2008.
 “The Quant Crunch” Published by Burning Glass Technologies. November 2017.
 Fuller, Joseph. “Bridge the Gap” Published by Accenture, Burning Glass Technologies, and Harvard Business School. November 2014.
 Gans, Joshua “The Disruption Dilemma” MIT Press. 2016.
 Farhad, Manjoo “Udacity Says It Can Teach Tech Skills to Millions, and Fast” The New York Times. September 16, 2015.