by Angela Guess
Martin Hooper recently wrote in Enterprise Innovation, “As companies push to find the limit of innovation and move to set themselves apart from the crowd, more and more are also recognizing the importance of building a robust data analytics team to support their initiatives. Business leaders are aware that missing digital skills and shortage of IT talent is a challenge that hinders them from achieving digital transformation within their organizations. The race is on to putting digital transformation at the center of an enterprise’s corporate plan– in fact, it is predicted that by the end of 2017, two thirds of the CEOs of the G2000 enterprises will have this strategy in place. Seeing as such, here are some questions to ask when developing a Data Science team:”
Hooper goes on, “Before outsourcing for IT talent to manage data projects, organizations should first identify potential candidates within their team – chances are, they may already have internal staff working on projects scratching the surface of data analytics without noticing it. This can be done by accessing how data science is currently being used in the organization, no matter how little or widely. In most cases, the reason for not recognizing that existing employees have the capabilities and know-how already in place might be attributed to the fact that they have been working individually across different areas, instead of together in a cohesive unit, as they should be. In addition, it pays to identify employees with aptitude and curiosity for data science work – while they may already display skills of business acumen, data access, data modeling, decision science and data visualization, a lot more training can be done to develop them into full-fledged data scientists.”
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