Phillip J. Lederer and Xiaobo Zheng
A management system exists to coordinate, control, and make decisions about activities within an organization. These functions are information intensive, and therefore the design of management hierarchy has much to do with information-processing economics. Most economic entities’ management structures are described by “an organization chart” which is a network of departments. The goal of this paper is to take an analytical look at management hierarchy modeled as a tree with information-processing departments at nodes. Two key assumptions about information processing are made: first, data’s arrival patterns are uncertain as are processing times and that creates queuing delays, and second, data processing rates fall when data come from a variety of sources. Forthcoming results seem to accord more closely to empirical data than past work. Large increases in cost parameters or data flow rates do not change the hierarchy’s structure very much. At higher tiers departments have more capacity and operate at lower utilizations, and managers have more subordinates, thus their work is less specialized and more complex. Included case studies support the latter assertion. We find that a large drop in information technology cost, or increased importance of quick customer response due to competition does not reduce the hierarchy height as effectively as decentralization. This implies that the historically recognized delayering of firms is principally due to reorganization to decentralize information processing.