Value of Social Network -- A Large-Scale Analysis on Network Structure Impact to Financial Revenue of Information Technology Consultants 1 Lynn Wu MIT Sloan School of Management IBM Research Ching-Yung Lin IBM Research Sinan Aral NYU Stern MIT Sloan School of Management Erik Brynjolfsson MIT Sloan School of Management Working Paper Abstract A large body of literature on social networks in organizations demonstrates that certain types of network topology are optimal. However, little research leverages the ample data created by people‘s electronic communications to refine and verify theories. This gap is problematic, because the literature on organizational networks suffers from the same deficits as much of the social network literature: both tend to be focused on small, static networks. In this study, we mitigate this gap by collecting and mining the largest organizational social network ever collected. We find that not only does the population level topology of social network correlate with performance, attributes of the nodes in a social network such as human capital and status that can be beneficial to work performance. In addition to an individual‘s own human capital and network position, the human capital and status in one‘s network can be instrumental to one‘s success. 1 This work was presented at Winter Information Systems Conference, Salt Lake City, UT, Feb. 2009. Presentation slides can be accessed at http://smallblue.research.ibm.com/