1 Second International Symposium on Engineering Systems MIT Cambridge, Massachusetts, June 15-17- 2009 Models of Complex Enterprise Networks W. B. Rouse, L. F. McGinnis, R. C. Basole, D. A. Bodner, W. C. Kessler Tennenbaum Institute Georgia Institute of Technology Atlanta, GA 30332-0210 USA Copyright © 2009 by the Tennenbaum Institute. Published and used by MIT ESD and CESUN with permission ABSTRACT This paper reports on an ongoing comparative study of network models of complex enterprises. The focus is on enterprises composed of a large number of organizations, often represented as a hierarchy of networks that relate people to processes, organizations, and broader social and economic structures and forces. We consider the roles that information and incentives play in such complex hierarchical networks. These networks are elaborated in terms of four characteristics: transformations, flows, controls, and social/organizational relationships. A model hierarchy is presented that relates these four characteristics to phenomena, representations, micro-models, macro-models, and modeling tools. Examples of global manufacturing and health care delivery are woven through these discussions of alternative representations and models. We conclude by providing a structured comparison of these two domains. Key Words: Complex systems, network models, hierarchical models, engineering systems, global manufacturing, health care delivery. 1. Introduction Enterprises are typically composed of a large number of organizations that provide products and services, as well as other organizations that play important roles in the enterprise ecosystem. Such enterprises can be represented as hierarchical networks as shown In Figure 1. At the lowest foundational level, there are people working to create value, e.g., by assembling aircraft or automobiles, or providing medical care to patients. This work occurs in the context of the business processes of delivery operations. These processes may be formalized and visible -- perhaps also reengineered and optimized -- or they may be obscured by functional or departmental boundaries between, for example, engineering and manufacturing, or between orthopedics and radiology.