Selecting Six Sigma project: a comparative study of DEA and LDA techniques

Abstract

Purpose Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach First, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model. Findings The results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA. Originality/value The paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.