This study investigates the use of using complexity theory--the study of nonlinear dynamical systems of which chaos and catastrophe theory are subsets--in the analysis of a non temporal data set to derive valuable insights into the functioning of university schools of business. The approach is unusual in that studies of nonlinearity in complex dynamical systems typically involve longitudinal data. Challenges associated with such studies usually involve establishing nonlinearity, obtaining a data set with a sufficient number of entries, and robust mathematical and computational requirements for effective analysis. The format of the paper is as follows: 1) a general description of complex systems is presented which identifies a number of generally accepted characteristics of complex systems, 2) a description of the data set and the research technique utilized, 3) a presentation of the data set as an "attractor" landscape as typically defined in complex systems analysis, 4) potential insights that may be derived from the analysis; and 5) conclusions and recommendations for further study. The value of the study is to demonstrate that within the framework of complexity theory, non longitudinal data may be used to derive valuable managerial insights into the functioning of organizations such as university schools of business.