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Today’s data scientist shortage won’t go away soon, yet companies need them more than ever to leverage the value of big data. The solution is to build teams of data scientists instead of seeking soloists.
It is very difficult to find individuals with the scarce combination of skills that data scientists possess. For many companies, the more realistic approach is to create teams of people who individually lack the full skill set of a data scientist, but as a group, possess them all. Members of a data scientist team might include a systems architect, a quantitative analyst, a business analyst, a visualization designer and a software engineer.
Data scientists are in high demand, but research by the Accenture Institute for High Performance has found the world is facing a severe shortage. The shortage is especially severe in the US where 80 percent of new data scientist jobs created between 2010 and 2011 have not been filled.
Meanwhile, the US is expected to create around 400,000 new data science jobs between 2010 and 2015, but is likely to produce only about 140,000 qualified graduates to fill them. While emerging economies are continuing to produce science, technology, engineering and mathematics (STEM) talent, the shortage in the US alone will still exceed the combined surpluses in China and India.
Executives should keep the following points in mind for creating effective data engineer-scientist teams:
Widen the recruiting pool. Search outside your industry and even outside the business world. For example, consider academics, physics majors and graphic designers for the unique contributions they could make to the team.
Communicate, collaborate, but don’t necessarily co-locate. In an ideal world, all members work together in the same location. But companies should not give up on teams if they cannot co-locate them.
Boost effectiveness and retention through team learning. Encourage members to pick up skills from other members to create flexibility and to decrease attrition.
Jeanne G. Harris is the managing director for IT and analytics research at the Accenture Institute for High Performance, and the co-author of Competing on Analytics (Harvard Business Review Press, 2007). She is based in Chicago. Her e-mail is email@example.com.
Nathan Shetterley is a senior R&D manager with the Accenture Technology Labs. He is based in San Francisco. His e-mail is firstname.lastname@example.org.
Allan E. Alter is a research fellow with the Accenture Institute for High Performance. He is based in Boston. His e-mail is email@example.com.
Krista Schnell is an R&D developer with Accenture Technology Labs. She is based in San Jose. Her e-mail address is firstname.lastname@example.org.
February 12, 2014
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