Noshir Contractor, Northwestern University

People Analytics: Using Digital Exhaust from the Web to Leverage Network Insights in the Algorithmically Infused Workplace
Noshir Contractor

Description

Semester: 
Fall 2022
Lecture Time: 
Friday, September 2, 2022 - 1:30pm to 3:00pm
Lecture Location: 

R0240, Ross School of Business, Lower Level

Introduced By: 
Cassie Turner

Abstract

In order to bring the performance of people analytics in the algorithmically infused workplace up — and in line with the hype — organizations need to do more than analyze data on demographic attributes. We need to focus not only on who people are but also who they know. The potential for social network analysis to identify “high potentials,” who has good ideas, who is influential, what teams will get work done efficiently and effectively is well established based on decades of research. The challenge has been the collection of network data via surveys that are time consuming, elicit low response rates and have a high obsolescence. This talk presents empirical examples ranging from corporate enterprises to simulated long duration space exploration to demonstrate how we can leverage people analytics – and in particular relational analytics - to mine “digital exhaust”— data created by individuals every day in their digital transactions, such as e‐mails, chats, “likes,” “follows,” @mentions, and file collaboration— to address challenges they face with issues such as team conflict, team assembly, diversity and inclusion, succession planning, and post-merger integration.

Recording & Additional Notes

Noshir Contractor is the Jane S. & William J. White Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, the School of Communication and the Kellogg School of Management and Director of the Science of Networks in Communities (SONIC) Research Group at Northwestern University. He is also the President-Elect-Select of the International Communication Association (ICA).

Professor Contractor has been at the forefront of three emerging interdisciplines: network science, computational social science and web science. He is investigating how social and knowledge networks form – and perform – in contexts including business, scientific communities, healthcare and space travel. His research has been funded continuously for 25 years by the U.S. National Science Foundation with additional funding from the U.S. National Institutes of Health, NASA, DARPA, Army Research Laboratory and the Bill & Melinda Gates Foundation.

His book Theories of Communication Networks (co-authored with Peter Monge) received the 2003 Book of the Year award from the Organizational Communication Division of the National Communication Association. He is a Fellow of the American Association for the Advancement of Science (AAAS) and the Association for Computing Machinery (ACM). He also received the Distinguished Scholar Award from the National Communication Association and the Lifetime Service Award from the Organizational Communication & Information Systems Division of the Academy of Management. In 2018 he received the Distinguished Alumnus Award from the Indian Institute of Technology, Madras where he received a Bachelor’s in Electrical Engineering. He received his Ph.D. from the Annenberg School of Communication at the University of Southern California.

Reading List

Leonardi, P., & Contractor, N. S. (2018, December). Better People Analytics: Measure who they know, not just who they are. Harvard Business Review, 96, 70–81. https://paperpile.com/shared/RIES96

Wagner, C., Strohmaier, M., Olteanu, A., Kıcıman, E., Contractor, N., & Eliassi-Rad, T. (2021). Measuring algorithmically infused societies. Nature, 595(7866), 197–204. https://paperpile.com/shared/n1vP6K

Contractor, N. (2020). How can computational social science motivate the development of theories, data, and methods to advance our understanding of communication and organizational dynamics. In Welles, B. F., & González-Bailón, S. (Eds.). The Oxford handbook of networked communication. Oxford University Press, USA. Published online https://doi. org/10.1093/oxfor dhb/97801, 90460(518.013), 7. https://paperpile.com/shared/EAuhYG