Social network analyses in organizations: challenges and approaches for studying work networks

Abstract

In the past years, social network analysis (SNA) techniques got disseminated to a large number of fields, such as, disease spread, animal group behaviour, organization dynamics, and the like. A particular use for SNA is to help in understanding how organizations work. It focuses not only on issues relative to how to manage organizations, but how people accomplish their work and share their knowledge by means of their work networks. Understanding how people actually work in an organization helps managers to diagnose gaps in communication and collaboration, and consequently improve work efficiencies and effectiveness. In this paper we present some challenges in using SNA techniques to understand how work is done in a large IT service delivery organization. Using SNA it is possible to attain a better understanding of the working environment as well as diagnose some of the issues workers face everyday. Some major technical and methodological challenges are: to define the importance of each media and that there are a few SNA algorithms that can work with multi-edges or weighted graphs. Thus, a computational challenge in organization data rests on how to merge the different media available and how to measure the importance and consequently give value for e-mail, instant messenger, traces of work, hierarchical structure, collaborative documents, intern communities, and face-to- face communications, for example. In sum, this paper discusses some of these challenges that emerged in our exploration of work networks, and suggests a few techniques and approaches to tackle them.