Measuring performance & interrelatedness in social networks of knowledge workers

Complexity is usually referred to as the degree of interrelatedness of components within a system. This paper explores the interrelatedness of components within complex social networks by using social network concepts adapted from `structural holes´ theory. Analogous to Shannon´s Entropy, the study operationalises `interrelatedness´ in terms of the extent to which network ties transmit information that is unique and non-redundant based on structural positions of components within a complex social network. We term this index the `Information Redundancy Index´ (IRI), developed by combining structural holes measures of `efficiency´ and `constraint´ to determine the extent of redundant information exchange between components. The study then demonstrates how `Information Redundancy´, as a proxy for complexity, can be used to associate with project worker performance in terms of interrelatedness. It is hypothesized that higher levels of `Information Redundancy´ within an individual´s social network have a detrimental effect on individual performance. Empirical results, from a pilot study of 17 real estate agents show a significant negative correlation between `efficiency´ and performance providing partial support for the hypothesis. These results are promising by paving the way for future studies to use social network metrics to capture system-level interactions that emerge in complex social systems. This has significant implications for future development of a practical managerial toolkit for project professionals in an increasingly complex world.