Selecting the Six Sigma Project: A Multi Data Envelopment Analysis Unified Scoring Framework

Abstract

The importance of the project selection phase in any six sigma initiative cannot be emphasized enough. The successfulness of the six sigma initiative is affected by successful project selection. Recently, Data Envelopment Analysis (DEA) has been proposed as a six sigma project selection tool. However, there exist a number of different DEA formulations which may affect the selection process and the wining project being selected. This work initially applies nine different DEA formulations to several case studies and concludes that different DEA formulations select different wining projects. Also in this work, a Multi-DEA Unified Scoring Framework is proposed to overcome this problem. This framework is applied to several case studies and proved to successfully select the six sigma project with the best performance. The framework is also successful in filtering out some of the projects that have "selective" excellent performance, i.e. projects with excellent performance in some of the DEA formulations and worse performance in others. It is also successful in selecting stable projects; these are projects that perform well in the majority of the DEA formulations, even if it has not been selected as a wining project by any of the DEA formulations.

Selection of Six Sigma project with interval data: common weight DEA model

“…Substantial researchers have accentuated the significance of the Six Sigma project selection, and numerous methods have been presented in the literature. Arafah (2015), Banuelas et al (2006), Padhy (2017) and Yousefi and Aqamohammadi (2014) summarized the common methods used for the Six Sigma project selection. Table II summarizes some popular methods.…”

“…Table II summarizes some popular methods. Among these papers above, many researchers suggested that the Six Sigma project selection is an MCDM problem (Kumar et al, 2007;Arafah, 2015). As mentioned earlier, DEA can effectively solve the MCDM problems and offer many advantages, especially objectivity.…”

“…Yüksel (2012) used input-oriented CCR model to evaluate the efficiencies of five Six Sigma projects and pointed that DEA can be used not only to evaluate the performance of the firm's Six Sigma projects but also to analyze the reasons for inefficiency and find the ways to improve the inefficient projects. Arafah (2015) developed a Multi-DEA Unified Scoring Framework to overcome the problem that different DEA formulations may affect the Six Sigma project selection result. DEA is an applicable method for selecting the optimal Six Sigma project, but the conventional DEA models have two main drawbacks, namely, weight flexibility and poor discriminating power.…”

“…It means that when the efficiencies of DMUs are measured, the constraints are different from one DMU to another, and even in the lower limit efficiency and the upper limit efficiency of the same DMU, the constraints in models are also different. Thus, the evaluation efficiency values are not Alinezhad et al (2013), Arafah (2015), Yousefi and Aqamohammadi (2014) and Yüksel (2012) comparable because the different constraint sets result in the use of different production frontiers during the measure process. IDEA is frequently used for selecting and ranking DMUs based on their efficiencies in the presence of imprecise data.…”

“…In previous papers, researchers indicated that Six Sigma projects require multiple inputs to produce outputs, hence the project's selection process is essentially an issue of multiple criteria decision-making (MCDM) (Arafah, 2015;Bilgen and S en, 2012). Many researchers used analytic hierarchy process (AHP) or technique for order preference by similarity to ideal solution (TOPSIS) method to evaluate Six Sigma projects (Kumar et al, 2009;Bilgen and S en, 2012).…”