Manufacturing Performance Evaluation Tool for Malaysian Automotive Small and Medium-sized Enterprises

INTRODUCTION The globalization of markets, growing inter-diffusion of economies, and increased inter-dependence of economic agents are reshaping national and international competitive environment and economic performance (Ghobadian and Gallear, 1996). To be competitive, all companies have to re-examine and modify their competitive strategies. Small and medium sized enterprises (SMEs) can not be separated from these pressures. They have to pay more attention to the changes in manufacturing performance system including the measures used. They need to have a set of manufacturing performance measure to gauge their level of achievement. Hudson, Smart and Bourne (2001) suggested that there are numerous barriers to strategic performance measurement system implementation in SMEs. The failure of the implementation was attributed primarily to the development process being: too resource intensive and too strategically oriented. This is due to limited resources and a dynamic style strategy of SMEs. These issues are acutely problematic because developing a strategic performance measurement system is necessarily long term and it explicitly requires the resulting measures to be strategically focused. These differences of SME's characteristics indicate a need to asses their performance measurement differently. The manufacturing performance measurement literatures have shown the financial measures such as profits and return on investment were criticized by many authors because of their many shortcomings. They are short-term rather than long-term focus, measuring the past rather than future (McNair, Lynch and Cross, 1990). Financial measures tend to be obsolete and easily manipulated by managers (Jusoh and Parnell, 2008). To deal with those criticisms then non financial measures such as quality, delivery, time, and flexibility have been suggested as better performance measures. Non-financial measures are timelier than financial ones, very measurable and precise, meaningful to the workforce so aiding continual improvement, consistent with company goals and strategies, they change and vary over time as market needs change, and so tend to be flexible (Medori and Steeple, 2000). This study focused only on the non-financial manufacturing performance measures. In performance measurement, numerous non-financial measures can be used by organizations. The problem is which of the measures from the ones that are available in an organization should be used (Medori and Steeple, 2000). It usually depends on the characteristics of the organization and the nature of its business industry and environment. In the performance measurement literature, there are also different models or approaches on analytical techniques and quantification of performance. Oztaysi and Ucal (2009) summarized the most frequently used analytical models in the literature. They are Cognitive Maps, Regression Analysis, Artificial Neural Networks (ANNs), Analytical Hierarchy Process (AHP), Multi Attribute Utility Theory (MAUT), and Simple Multi Attribute Rating Technique (SMART) and Data Envelopment Analysis (DEA). These techniques usually used to determine the importance of indicators or define tradeoffs between indicators and definition of relationship between the indicators (Abu-Suleiman, 2006). Of those techniques, the AHP is the most popular tool for multiple criteria decision-making. AHP has been extensively used for selection process such as comparing the overall performance of manufacturing departments (Rangone, 1996), determining measures for business performance (Cheng and Li, 2001), manufacturing supply chain (Wang, Huang and Dismukes, 2005), benchmarking logistics performance (Chan, Chan, Lau and Ip, 2006), and vendor evaluation and selection (Haq and Kannan, 2006). As cited in Muralidharan, Anantharaman and Desmukh (2001), in addition to simplicity, ease of use, and flexibility, its ability to handle complex and ill-structured problems has led to AHP's power and popularity as a decision-making tool (Vargas, 1990; Wedley, 1990). …