Six sigma project selection using data envelopment analysis

Purpose – The evolution of six sigma has morphed from a method or set of techniques to a movement focused on business‐process improvement. Business processes are transformed through the successful selection and implementation of competing six sigma projects. However, the efforts to implement a six sigma process improvement initiative alone do not guarantee success. To meet aggressive schedules and tight budget constraints, a successful six sigma project needs to follow the proven define, measure, analyze, improve, and control methodology. Any slip in schedule or cost overrun is likely to offset the potential benefits achieved by implementing six sigma projects. The purpose of this paper is to focus on six sigma projects targeted at improving the overall customer satisfaction called Big Q projects. The aim is to develop a mathematical model to select one or more six sigma projects that result in the maximum benefit to the organization.Design/methodology/approach – This research provides the identification ...

[1]  A. Charnes,et al.  Sensitivity and stability of efficiency classifications in Data Envelopment Analysis , 1996 .

[2]  Johannes Freiesleben,et al.  Six Sigma and the Bottom Line , 2004 .

[3]  W. J. Hill,et al.  The Impact of Six Sigma Improvement—A Glimpse into the Future of Statistics , 1999 .

[4]  A. Fundin,et al.  Use Customer Feedback To Choose Six Sigma Projects , 2003 .

[5]  William F. Rodebaugh,et al.  The Project Selection Process , 2002 .

[6]  Robert M. Thrall,et al.  Chapter 5 Duality, classification and slacks in DEA , 1996, Ann. Oper. Res..

[7]  M. J. Harry,et al.  SIX SIGMA : A BREAKTHROUGH STRATEGY FOR PROFITABILITY , 1998 .

[8]  D. Moorman On the quest for Six Sigma. , 2005, American journal of surgery.

[9]  Joseph Moses Juran Juran on leadership for quality : an executive handbook , 1989 .

[10]  Praveen Gupta,et al.  Six Sigma Deployment , 2003 .

[11]  J. Antony Six Sigma in the UK service organisations: results from a pilot survey , 2004 .

[12]  Charles R. Gowen,et al.  Effect of technological intensity on the relationships among Six Sigma design, electronic-business, and competitive advantage: A dynamic capabilities model study , 2005 .

[13]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[14]  Jichao Xu,et al.  Selecting Six Sigma Projects , 2002 .

[15]  C. Tennant,et al.  Selection of six sigma projects in the UK , 2006 .

[16]  Sally Lanyon At Raytheon Six Sigma works, too, to improve HR management processes , 2003 .

[17]  Thomas Bertels,et al.  Rath & Strong's Six Sigma Leadership Handbook , 2003 .

[18]  William Michael Kelly,et al.  Three Steps To Project Selection , 2002 .

[19]  Mark Goldstein,et al.  Six Sigma Program Success Factors , 2001 .

[20]  P. Andersen,et al.  A procedure for ranking efficient units in data envelopment analysis , 1993 .

[21]  John J. Rousseau,et al.  Two-person ratio efficiency games , 1995 .

[22]  Haritha Saranga,et al.  Reliability and Six Sigma , 2006 .

[23]  Joe Zhu Robustness of the efficient DMUs in data envelopment analysis , 1996 .

[24]  Peter S. Pande,et al.  The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance , 2000 .

[25]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[26]  Joe Zhu,et al.  Quantitative models for performance evaluation and benchmarking , 2003 .

[27]  Joseph Moses Juran,et al.  Juran Institute's Six Sigma Breakthrough and Beyond , 2004 .

[28]  A. Charnes,et al.  SENSITIVITY OF EFFICIENCY CLASSIFICATIONS IN THE ADDITIVE MODEL OF DATA ENVELOPMENT ANALYSIS , 1992 .

[29]  Lawrence M. Seiford,et al.  Stability regions for maintaining efficiency in data envelopment analysis , 1998, Eur. J. Oper. Res..

[30]  L. Seiford,et al.  An investigation of returns to scale in data envelopment analysis , 1999 .

[31]  Jiju Antony,et al.  Six Sigma in the software industry: results from a pilot study , 2004 .

[32]  U. D. Kumar,et al.  On the optimal selection of process alternatives in a Six Sigma implementation , 2008 .

[33]  Lawrence M. Seiford,et al.  On alternative optimal solutions in the estimation of returns to scale in DEA , 1998, Eur. J. Oper. Res..

[34]  Bill Robinson,et al.  Build a Management System Based on Six Sigma , 2005 .