Data Envelopment Analysis: A Linear Programming Application to Measure the Relative Efficiencies of Internal Business Divisions
Abstract
Data Envelopment Analysis (DEA) is a non-parametric linear programming model used to determine relative efficiencies of similar decision making units based on identical categories of input and output variables. This research applied DEA to the Internal Business Divisions (IBDs) of a fictitious Architecture / Engineering / Construction firm to illustrate how business managers can identify internal inefficiencies. An overview of the mathematical theory behind DEA and its model variations are presented, as well as the methods used to apply DEA to the company’s IBDs. The fictitious company and its IBDs were defined based on industry standards. Then, financial and non-financial key performance indicators were identified and used as the input and output variables. The variable data was developed based on averages of top performing design firms in the industry, and the results were analyzed to determine which IBDs were underperforming and how. The specific results of the analysis were irrelevant due to the fact that the company and data were fictitious; however, the results were examined and interpreted to illustrate how DEA can be used as a tool to realize potential efficiency optimization within an existent company.
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