Assessing performance tradeoffs in hierarchical organizations using a diffusive coupling model
This work addresses performance tradeoffs for organizations, teams, and command and control units, but it is incremental as it applies existing modeling techniques to hierarchical structures.
The study tackled the problem of efficiency and performance tradeoffs in hierarchical organizations by analyzing a diffusive coupling model on hierarchical networks, revealing a fundamental tradeoff where networks favoring fast coordination reduce the ability to share information from lower layers up the hierarchy, with numerical results validating these theoretical insights.
We study a continuous-time dynamical system of nodes diffusively coupled over a hierarchical network to examine the efficiency and performance tradeoffs that organizations, teams, and command and control units face while achieving coordination and sharing information across layers. Specifically, after defining a network structure that captures real-world features of hierarchical organizations, we use linear systems theory and perturbation theory to characterize the rate of convergence to a consensus state, and how effectively information can propagate through the network, depending on the breadth of the organization and the strength of inter-layer communication. Interestingly, our analytical insights highlight a fundamental performance tradeoff. Namely, networks that favor fast coordination will have decreased ability to share information that is generated in the lower layers of the organization and is to be passed up the hierarchy. Numerical results validate and extend our theoretical results.