Optimal Organizations Across Many Faces of Complexity: Synchronized Networks With Load-Balance and Minimum Complexity

We present a framework for the optimization of networks across three perspectives of complexity. Two of these refer to structural properties of a system, termed objective and subjective complexity: the former sees an advantage in connectivity; the latter views complexity as creating opaqueness from within a subjective perspective. Here, the distance from a reference for simplicity network—, a tree, the quintessential management structure—models subjective complexity. The third property relates to the dynamics of a network for which we utilize the proxy of Kuramoto synchronization. Within this we propose a two-stage optimization process for effective synchronization within a constraint of load balance and minimum subjective and objective complexities. Separate objective functions for each of these views of complexity are presented. This builds on previous work on the optimization of Kuramoto synchronization. We demonstrate the computational approach within an illustrative framework for stakeholder engagement in the management of complexity in organizational decision making. We show how the different perspectives may be balanced to arrive at choices of an optimal network design.