22nd Annual HSATM Conference

Competitive Advantage in the Era of Big Data

Big Data has come to be the shorthand term for a rapidly advancing trend in the combination of computer science and statistics / econometrics, allowing the discovery of new insights from analysis of massive amounts of data. This phenomenon is opening the door to a new approach to understanding the world and making decisions.

  • Wednesday, June 19, 2013
  • 8:45 AM - 4:45 PM
  • Continental Breakfast, 8:00-8:45 AM

Stevens, Babbio Center, 525 River St., Hoboken, NJ 07030
Corner of 6th & River Streets

The quest to draw useful insights from business measurements is nothing new. In a recent New York Times article, Big Data is described as a descendant of Frederick Winslow Taylor’s (Stevens class of 1883) “scientific management,” which used time-and-motion studies to redesign work for maximum efficiency. Today, vastly larger datasets are being used in applications ranging from targeted and viral marketing, to automatic language translation, to city planning and medical data analysis. Data is now characterized as the basis of competition in the 'smarter' era, and Big Data as “the next natural resource.”

The 2013 HSATM conference will examine how this revolution may well transform how organizations are managed, how they innovate, and how they achieve competitive advantage, as well as the potential societal impacts. It will also explore possible pitfalls in the application of Big Data and how to avoid them.

The Conference will appeal to people working in R&D, marketing, business development, operations, project management, technology, HR — in short, to everyone concerned with innovation, competitive advantage, and the practical application of knowledge.

Presentation Abstracts & Speaker's Bios


A panel discussion will follow the presentations, featuring the four presenters joined by two other authoritative speakers, Joe McKendrick and Mahesh Harvu. The latter will begin the panel discussion by offering brief “devil’s advocate” views that raise potential pitfalls in the application of Big Data, which will be addressed by the panel.