Supply chain performance measurement system using DEA modeling

– This paper aims to illustrate the use of data envelopment analysis (DEA) in measuring internal supply chain performance., – Two DEA models were developed – the technical efficiency model and the cost efficiency model. The models are further enhanced with scenario analysis to derive more meaningful business insights for managers in making resources planning decisions., – The information obtained from the DEA models helps managers to identify the inefficient operations and take the right remedial actions for continuous improvement. More importantly, the opportunity cost (forgone profit) calculated serves as a good reference to managers to make efficient decisions on resource allocations., – Results are based on the deterministic data set. Future enhancement of the study would be to look into the possibility of modeling DEA in a stochastic supply chain environment (non‐deterministic) due to the fact that supply chain operates in a dynamic environment., – The proposed DEA‐based approach provides useful managerial implications in the measurement of supply chain efficiency. The study proves the usefulness of DEA as a decision‐making tool in supply chain., – This paper provides useful insights into the use of DEA as a modeling tool to aid managerial decision making in measuring supply chain efficiency.

[1]  Tzu-Chuan Chou,et al.  Towards a framework of the performance evaluation of SMEs' industry portals , 2005, Ind. Manag. Data Syst..

[2]  Gordon Stewart,et al.  Supply‐chain operations reference model (SCOR): the first cross‐industry framework for integrated supply‐chain management , 1997 .

[3]  Kim Hua Tan,et al.  A process and tool for supply network analysis , 2004, Ind. Manag. Data Syst..

[4]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[5]  Emmanuel Thanassoulis,et al.  Data Envelopment Analysis:the mathematical programming approach to efficiency analysis , 2008 .

[6]  Josu Takala,et al.  A proposed white-collar workforce performance measurement framework , 2006, Ind. Manag. Data Syst..

[7]  Kuan Yew Wong,et al.  A review on benchmarking of supply chain performance measures , 2008 .

[8]  Petri T. Helo,et al.  Managing agility and productivity in the electronics industry , 2004, Ind. Manag. Data Syst..

[9]  Joseph Sarkis,et al.  A comparative analysis of DEA as a discrete alternative multiple criteria decision tool , 2000, Eur. J. Oper. Res..

[10]  William P. Wagner,et al.  Implementing corporate intranets: lessons learned from two high-tech firms , 2002, Ind. Manag. Data Syst..

[11]  Mohan P. Rao A performance measurement system using a profit-linked multi-factor measurement model , 2006, Ind. Manag. Data Syst..

[12]  H. Sherman,et al.  Managing Bank Productivity Using Data Envelopment Analysis DEA , 1995 .

[13]  Joe Zhu,et al.  Multi-factor performance measure model with an application to Fortune 500 companies , 2000, Eur. J. Oper. Res..

[14]  Stephen O. Ogunlana,et al.  Selection and application of risk management tools and techniques for build-operate-transfer projects , 2004, Ind. Manag. Data Syst..

[15]  Lawrence M. Seiford,et al.  Recent developments in dea : the mathematical programming approach to frontier analysis , 1990 .

[16]  Lawrence M. Seiford,et al.  Data envelopment analysis: The evolution of the state of the art (1978–1995) , 1996 .

[17]  David Frederick Ross,et al.  Competing Through Supply Chain Management , 1998 .

[18]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[19]  Michael Schefczyk,et al.  Industrial benchmarking: A case study of performance analysis techniques , 1993 .

[20]  G. Stevens Integrating the Supply Chain , 1989 .

[21]  Robert C. Rickards,et al.  Setting benchmarks and evaluating balanced scorecards with data envelopment analysis , 2003 .

[22]  A. Athanassopoulos,et al.  Ratio and Frontier Analysis for Assessing Corporate Performance: Evidence from the Grocery Industry in the UK , 1995 .

[23]  Paul Humphreys,et al.  A web-based supplier evaluation tool for the product development process , 2005, Ind. Manag. Data Syst..

[24]  Peter E. D. Love,et al.  Management of risks in information technology projects , 2004, Ind. Manag. Data Syst..

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

[26]  A. Charnes,et al.  Data Envelopment Analysis Theory, Methodology and Applications , 1995 .

[27]  Philip M. Kaminsky,et al.  Designing and managing the supply chain : concepts, strategies, and case studies , 2007 .

[28]  Richard C. Morey,et al.  Increasing the Efficiency of Corporate Travel Management through Macro Benchmarking , 1995 .

[29]  Gary D. Ferrier,et al.  Measuring cost efficiency in banking: Econometric and linear programming evidence , 1990 .

[30]  Vincent G. Duffy,et al.  Using AHP for determining priority in a safety management system , 2004, Ind. Manag. Data Syst..

[31]  John Seydel,et al.  Data envelopment analysis for decision support , 2006, Ind. Manag. Data Syst..