Big data tips from business school experts

Business schools around the world are integrating big data and analytics training into curriculums to meet growing demand in the enterprise for data-driven decisions and business strategies.

Over at BusinessBecause, a website for MBA students and graduates, writer Seb Murray gets B-school leaders and educators to share some of their top data analytics tips. Many of these insights also should help current members of the enterprise C-suite execute their big data analytics initiatives.

Roy Lee, assistant dean of global programs at NYU Stern School of Business, argues that “unlocking the potential of analytics takes more than just hiring data scientists or building assets.” Rather, he says, enterprises should “initiate a shift toward building a data-driven culture.”

But it’s hard to foster a data culture if your data scientists are locked in a room. Instead they should work in collaboration with other enterprise employees, suggests Arne Strauss, associate professor on the MSc Business Analytics at Warwick Business School.

“Successful projects in business analytics are often run by interdisciplinary teams, with experts on analytics, information technology, methodology, and on the business implication of the problem,” he tells BusinessBecause.

This type of integrated, team-based approach to analytics can help keep the focus on the specific business challenges that must be addressed. Without the ongoing perspective and context of relevant enterprise stakeholders, analytics programs can lose direction and momentum.

Finally, enterprises should realize that big data and analytics are tools that can be leveraged by themselves and their competitors. “If you aren’t using data to anticipate customer interests, your company is going to be at a disadvantage, especially when competing against the most advanced digital companies,” David Kiron, executive editor of MIT Sloan Management Review and former senior researcher at Harvard Business School, tells BusinessBecause.

What are your enterprise’s data analytics strategies and goals for 2016?


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