Mobile Analytics designed by Iris Li from The Noun Project
The value of data science skills, and resulting demand for skilled practitioners, is a well-known challenge within the emerging big data analytics industry. This trend receives additional support in “Game changers: Five opportunities for US growth and renewal”, a new report from McKinsey Global Institute (MGI) which estimates that big data analytics could increase annual GDP in retail and manufacturing by up to $325 billion by 2020.
According to MGI’s research, by 2018 the United States will experience a shortage of 190,000 skilled data scientists, and 1.5 million managers and analysts capable of reaping actionable insights from the big data deluge. With an estimated 40,000 exabytes of data being collected by 2020 — up from 2700 exabytes in 2012 — the implications of this shortage become apparent. Further driving this explosion in data collection, and the demand for skilled practitioners, is the wide range of economic sectors that will leverage big data analytics in the next decade, including retail, manufacturing, health care, and government services.
As a result, the opportunity for data scientists and organizations that move early in the space is apparent. MGI projects macroeconomic impact coming through three major routes — cost efficiencies and productivity gains, shifts in market share, and consumer surplus. To remain competitive and maximize efficiencies in the coming decade, companies will need to invest in big data technologies, but equally important will be the investment in data scientists proficient in advanced statistics and machine learning.
Achieving this goes beyond offering attractive compensation packages and an appealing internal culture. As Pivotal’s Annika Jimenez writes in her paper, Disruptive Data Science: Transforming Your Business into a Data-Driven Enterprise, “Your ability to lure strong data science talent in this white-hot market for data scientists depends entirely on your ability to build the most attractive analytics playground for your candidates.”
In the long term, however, there will need to be a concerted effort to build out this emerging workforce. While existing managers and analysts can expand their analytics skills through a data science certification curriculum, this alone will not address the entirety of the shortage. In their report, MGI states:
The United States is already ahead of other countries in deploying big data and developing the expertise needed to harness this information and create value. But to maintain its lead, it will need to focus on building a pipeline of talent… A significant amount of retraining may be necessary to develop the skills of those already in the workforce. Many industries are engaged in a war for top analytical talent; this shortage is likely to be one of the central challenges to wider public-sector adoption, since government limits on compensation make it difficult to lure highly sought-after candidates away from the private sector.
MGI cites the Obama administration’s Big Data Research and Development Initiative as one promising response to this economic challenge, and predicts that “The adoption of big data tools in the federal government may provide additional momentum in academia, the biomedical research community, and the private sector.” As Pivotal’s Jimenez notes, a number of academic institutions are already building out data science programs, including the University of Washington, Stanford, Syracuse, Northwestern, North Carolina State, and Columbia University.
