Computational Modeling of Complex Enterprise Systems: A Multi-Level Approach

Abstract

Enterprises are complex adaptive socio-technical systems. They exhibit nonlinear, dynamic characteristics, resulting in unpredictable system behavior. Enterprises tend to consist of many independent agents. The needs and desires of these agents are not homogenous; their goals and behaviors often conflict, requiring agents to dynamically adapt to external events. At the same time, agents are intelligent and learn. The overall enterprise system thus changes over time. Given that no single agent is in control, complex enterprise system behaviors are typically not directly controllable, but can be influenced and managed. Successful transformation of such systems is consequently quite challenging. Traditional modeling and analyses approaches fail to consider these complex issues and are therefore inadequate for supporting enterprise transformation efforts. New methods and tools are therefore needed. This chapter argues for the use of multi-level computational methods in pursuit of this endeavor. Enterprise components and behaviors can be conceptualized as consisting of multiple levels. We find using the levels of people, processes, organizations and eco-systems to be a useful framework. Within this framework, computational modeling augments and amplifies human decision-making and facilitates exploration of a wide range of possibilities, thereby enabling the early discarding of bad ideas and refinement of good ones. Also, decomposition of an enterprise into multiple levels allows stakeholders to interact with those phenomena of interest to them. The goal of this work is to enable decision makers to “drive the future” before “writing the check”.