Performance Modelling of Indian SMEs: A DEA Approach

Abstract

The purpose of the present study is to develop a model through Data Envelopment Analysis (DEA) for assessment and prediction of performance of Small & Medium Enterprises (SMEs) for effective decision making. DEA is a robust mathematical tool for evaluation of efficiency of SMEs. DEA basically, takes into account the input and output components of a decision making unit (DMU) to calculate technical efficiency (TE). TE is treated as an indicator for performance of DMUs and comparison has been made among them. A sensitivity analysis has been carried out to study the robustness of the ranking of SMEs obtained through DEA. A total of 41 Indian companies who are producing auto components are chosen for benchmarking purpose. The average score of efficiency is 0.565with a standard deviation of 0.315 when Charnes, Cooper and Rhodes (CCR) model is used. Similarly, when the Banker, Charnes and Cooper (BCC) model is used the average score is 0.751 with a standard deviation of 0.246. The rank order correlation coefficient between the efficiency ranking obtained through CCR and BCC model is 0.763 (p =0.000) which is significant. The peer group and peer weights for the inefficient SMEs have been identified. This is useful for benchmarking for the inefficient DMUs. The SMEs can identify the parameters in which they lack and take necessary steps for improvement. The peer group for the inefficient SMEs indicates the efficient SMEs to which the inefficient SMEs are closer in its combination of inputs and outputs. This work the managers to predict the performance of individual DMU based on input consumed and generate various “what-if” scenarios. The study provides a simple but comprehensive methodology for improving the performance of SMEs in India