Project Management Efficiency of a Portuguese Electricity Distribution Utility Using Data Envelopment Analysis

Abstract In this paper a model to assess the efficiency of project management by a Portuguese company responsible for the electricity distributionis proposed. The main objectives of the model is to assist the company in three areas: Assess the efficiency of twenty five Operational Areas developing remote control projects of the distribution network, making more transparent the benefits of an integrated project management methodology; identify possible actions to improve the efficiency of those Operational Areas; and prepare the company to use the model for evaluating the efficiency of other projects. Data envelopment analysis is used to assess the ability of this utility in converting inputs into outputs upon remote control projects in the distribution network during a period of time. The most important findings of this study regard the identification of inefficient Operational Areas, further showing how much the Operational Areas should reduce their resources usage and which Operational Areas are performing at best level, setting the best practices to be benchmarked.

[1]  Joe Zhu,et al.  Service Productivity Management: Improving Service Performance Using Data Envelopment Analysis (Dea) , 2006 .

[2]  Do Ba Khang,et al.  Time, cost and quality trade-off in project management: a case study , 1999 .

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

[4]  Jure Kovač,et al.  Project management in strategy implementation—experiences in Slovenia , 2000 .

[5]  Yvan Petit,et al.  Project Portfolios in Dynamic Environments: Organizing for Uncertainty , 2012 .

[6]  Mehdi Toloo,et al.  A NEW INTEGRATED DEA MODEL FOR FINDING MOST BCC-EFFICIENT DMU , 2009 .

[7]  Raffaella L. Mota Comparing Brazil and USA electricity performance; what was the impact of privatisation? , 2004 .

[8]  Sid Ghosh,et al.  Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach , 2004 .

[9]  Michael Norman,et al.  Data Envelopment Analysis: The Assessment of Performance , 1991 .

[10]  Tooraj Jamasb,et al.  Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks , 2005 .

[11]  Sofia Pemsel,et al.  Project management office a knowledge broker in project-based organisations , 2013 .

[12]  Jack R. Meredith,et al.  Project Management: A Managerial Approach , 1989 .

[13]  William W. Cooper,et al.  Introduction to Data Envelopment Analysis and Its Uses: With Dea-Solver Software and References , 2005 .

[14]  Kaoru Tone,et al.  Data Envelopment Analysis , 1996 .

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

[16]  Eric G. Too,et al.  The management of project management: a conceptual framework for project governance , 2014 .

[17]  H. Maylor Beyond the Gantt chart:: Project management moving on , 2001 .

[18]  Luis Copertari,et al.  Selecting projects in a portfolio using risk and ranking , 2011 .

[19]  Khalied Hyari,et al.  Utilizing data envelopment analysis to benchmark safety performance of construction contractors , 2010 .

[20]  Andreas Kappeler,et al.  Efficiency analysis of German electricity distribution utilities – non-parametric and parametric tests , 2006 .

[21]  Alexander Kock,et al.  An empirical investigation on how portfolio risk management influences project portfolio success , 2013 .

[22]  Timothy Coelli,et al.  An Introduction to Efficiency and Productivity Analysis , 1997 .

[23]  P. Leung,et al.  Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis , 1996 .

[24]  A. K. Munns,et al.  The role of project management in achieving project success , 1996 .