Article Preview
TopData Envelopment Analysis
Data Envelopment Analysis (DEA) was developed by Charnes, Cooper and Rhodes in the year 1978. It is a non-parametric, multi-factor productivity analysis model that evaluates linear programming based technique used to determine the relative efficiencies of a set of homogenous organizational units called Decision Making Units (DMUs). These DMUs utilize multiple inputs to produce multiple outputs and their efficiency is measured by the ratio of multiple outputs to multiple inputs.
DEA is a procedure designed to measure performance of any organization and comparing the relative efficiency of organizations. This method can successfully be applied to profit and nonprofit making organizations as well as data envelopment analysis can handle multiple inputs and multiple outputs as opposed to other techniques such as ratio analysis or regression. The measure of performance is expressed in the form of efficiency score. The efficiency score is measured as a ratio between weighted outputs and weighted inputs. The weights are chosen so as to find the best advantage for each unit to maximize its relative efficiency, under the restriction that this score is bound by 100% efficiency. If a unit with its optimal weights receives the efficiency score of 100%, it is efficient, while a score of less than 100% is considered inefficient.
DEA is a very flexible method of comparing the efficiency performance of various DMUs. DMUs can be individuals, branches of an organization, or entire organizations. DEA is concerned with measuring the relative efficiency of the various DMUs as they convert their inputs into outputs. As a non-parametric method, DEA does not require or assume any functional relationship between the inputs and outputs.