InnovationLit: Big Data, Updating C-Suite, Global 1000, Innovation Strategy, Open Data, Entrepreneurship, Coke’s Innovation Program

big data @ work: Dispelling the Myths, Uncovering the Opportunities; Thomas H. Davenport, Harvard Business Review Press, Boston, MA; 2014, 225 pp.

Admittedly skeptical about big data and its surrounding hype until he began researching it in 201l, Prof. Davenport now calls its importance “substantial.” Consequently, he explains the goal of his book, due out in February, is not to sell executives on big data but to help them make effective decisions about it because “there is little doubt that analytics can transform organizations, and the firms that lead the charge will seize the most value.”

Davenport is professor of IT and management at Babson College, a research fellow at the MIT Center for Digital Business, a senior advisor to Deloitte Analytics, and the cofounder and research director of the International Institute for Analytics. He begins his 18th book by explaining why big data is important to business organizations. He continues with seven chapters on the following topics:

• What people and companies are begin­ning to do with big data in key industries and functions.

• How organizations can decide what business objectives to achieve with big data, whether to pursue data discovery versus production applications, and how rapidly to move on big data oppor­tunities.

• The skills a data scien­tist needs and how big data will change management behaviors.

• Infrastructural technologies for managing big data, like Hadoop and MapReduce, plus useful analytical approaches such as machine learning and visual analytics.

• What organiza­tions need—beyond smart people and new technology—to succeed with big data.

• The learning one can extract from start-ups and online firms like LinkedIn, Kyruus and Operating Analytics.

• What large, established companies like UPS, United Healthcare and are doing with big data. This chapter also advances an idea Davenport calls “Analytics 3.0,” which describes how companies can combine the best of small data and traditional analytics with the big data approach.

Each chapter, concludes with action-oriented questions he feels management teams should be asking and answering in order to harness the power of big data.

“Mobilizing your C-suite for big-data analytics;” Brad Brown, David Court and Paul Willmott; McKinsey Quarterly Nov. 2013;

 “Today, the power of data and analytics is profoundly altering the business landscape, and once again companies may need more top-management muscle,” write these McKinsey executives. They outline the most important tasks facing corporate leaders wishing to profit from data analytics and the “critical” questions they need to answer. The tasks fall into six areas: acquiring adequate knowledge of data analytics; defining a strategy; determining what to build, purchase, borrow, or rent; securing the necessary expertise; undertaking the surprisingly “arduous” effort to mobilize human and capital resources; using frontline tools; adding new executive roles and lines of authority.

The article conclude with examples of companies that have implemented their own answers to “three key questions” the authors’ experience suggests will bring “strategic clarity to the needed organizational changes.”

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