Organizational Models for Big Data and Analytics


  • Robert L. Grossman University of Chicago
  • Kevin P. Siegel Visa U.S.A.



Organizational structures for analytics, big data, analytic governance, organizing data scientists


In this article, we introduce a framework for determining how analytics capability should be distributed within an organization. Our framework stresses the importance of building a critical mass of analytics staff, centralizing or decentralizing the analytics staff to support business processes, and establishing an analytics governance structure to ensure that analytics processes are supported by the organization as a whole.

Author Biography

Robert L. Grossman, University of Chicago

Robert Grossman is a faculty member at the University of Chicago, where he is the Chief Research Informatics Officer (CRIO) of the Biological Sciences Division; a Senior Fellow and Core Faculty in the Institute for Genomics and Systems Biology and the Computation Institute; and a Professor in the Department of Medicine in the Section of Genetic Medicine. He is also the Founder and a Partner of Open Data Group,




How to Cite

Grossman, R. L., & Siegel, K. P. (2014). Organizational Models for Big Data and Analytics. Journal of Organization Design, 3(1), 20–25.