Organizational Engineering Using Sociometric Badges

Benjamin N. Waber, Daniel Olguin Olguin, Taemie Kim, Alex (Sandy) Pentland


We show how a wearable computing research platform for measuring and analyzing human behavior can be used to understand social systems. Using a wearable sociometric badge capable of automatically measuring the amount of face-to-face interaction, physical proximity to other people, and relative location, we are able to construct a dynamic view of an organization’s social network by viewing interactions as links between actors. Combining this with email data, where e-mail exchanges indicate a social tie, we are able to form a robust view of the social network, using proximity information to remove spurious e-mail exchanges. We attempt to use on-body sensors in large groups of people for extended periods of time in naturalistic settings for the purpose of identifying, measuring, and quantifying social interactions, information flow, and organizational dynamics. We discuss how this system can lead to an automatic intervention system that could optimize the social network in real time by facilitating the addition and removal of links based on objective metrics in a socially natural way. We deployed this research platform in a group of 22 employees working in a real organization over a period of one month, and we found that betweenness in the combined social network had a high negative correlation of r = −0.49 (p < 0.05) with perceived group interaction quality.

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