A Framework for Performance Measurement System of Supply Chain Management

Supply Chain Management (SCM) has gained significance as one of the 21st century manufacturing paradigms for improving organizational competitiveness. Supply chain ensures improved efficiency and effectiveness of not only product transfer, but also information sharing between the complex hierarchies of all the tiers. The literature on SCM that deals with strategies and technologies for effectively managing a supply chain is quite vast. In recent years, organizational performance measurement (PM) and metrics have received much attention from researchers and practitioners. In this paper the performance is evaluated on five important links of the supply chain management system like inbound logistics, manufacturing, outbound logistics, marketing and after sales service. This paper describes a framework for performance measurements in supply chains. In addition, a multi-attribute decision-making technique, an analytic hierarchy process (AHP), is used to make decision about weak link based on the priority of performance measures. On the basis of questionnaire collected for each level from Indian industries. The mean rating (both level) is utilized, as the input data to compute the pairwise comparisons of criteria. KEYWORD Supply chain; Supply chain management; Performance measurement; AHP INTRODUCTION The development of economy of any country is supported by growth of its manufacturing industries. Currently, the manufacturing industries are passing through a phase of very tough competition. The economic environment is becoming harsh. In order to survive, every industry has to strive to improve productivity in all spheres of activity. What is required is to devise new ways of improving manufacturing performance by optimally utilizing the resources. In this context, effective supply chain management is vital to the competitiveness of manufacturing enterprises, as it directly impacts their ability to meet changing market demands in a timely and cost effective manner. Figure1 shows the typical supply chain consisting of different levels e.g. supplier, manufacturer, distributor and consumer, who work together in an effort to acquire raw materials, convert these raw materials into specified final products and deliver these final products to retailers Beamon (1998). Supply chain consists of all stages involved directly or indirectly in fulfilling a customer request. It includes the manufacturer, supplier, transporter warehouses, retailers and customer themselves. It is a multistage system involving a constant flow of information, material and product between different stages. Each stage of the supply chain performs different processes. A supply chain is also a worldwide network of facilities and distribution options that functions to procure materials, transform these materials into intermediate and finished products, and distribute these finished products to customer. The complexity of the chain may vary greatly from industry to industry and firm to firm in the context of intense global competition, so supply chain performance has become a critical issue in many industries. The aim of supply chain management is to gain an advantage in terms of customer service and cost over competitors. Therefore it is desirable to assess the company’s performance by benchmarking. Given the inherent complexity of the typical supply chain, selecting appropriate performance measures for supply chain analysis is particularly critical, since the system of interest is generally large and complex. The purpose of this research paper is to develop a basis for establishing a framework for performance measurement system of supply chains management. The performance is evaluated on five important links of the supply chain management system like inbound logistics, manufacturing, outbound logistics, marketing and after sales service. In this paper analytical hierarchy process (AHP) is used to make the decision about weak link of supply chain and mean rating is utilized, as the input data to compute the pairwise comparisons of criteria. Supplier Manufacture r Distributor Retailer Customer Fig.1 A typical Supply Chain International Journal of Advanced Engineering Technology E-ISSN 0976-3945 IJAET/Vol.II/ Issue IV/October-December, 2011/182-190 LITERATURE REVIEW With annual worldwide supply chain transactions leading to trillions of dollars, the potential impact of performance improvements is tremendous. In this context, adopting or implementing an appropriate performance measurement system with proper performance measures is imperative. According to Beamon (1999), one of the most difficult areas of performance measure selection is the development of performance measurement systems. This involves the methods by which an organization creates its measurement system. Important questions must be addressed here: What to measure? How are multiple individual measures integrated into a measurement system? How often to measure? How and when are measures re-evaluated? Although all of the ideas important to examining measurement systems are already in place, the problem is more difficult since the ‘slate is blank’ and the goal is to create the best possible measurement system for the supply chain or chains of interest. Traditionally, performance measurement is defined as the process of quantifying the effectiveness and efficiency of action (Neely et al. 1995). Sink and Tuttle (1989) claim that you cannot manage what you cannot measure. From the management perspective, performance measurement provides the necessary information for management feedback for decision makers and process managers. It plays a critical role in monitoring performance, enhancing motivation and communication and diagnosing problems Waggoner et al. (1999) and Rolstands (1995). Furthermore, performance measurement provides an approach to identifying the success and potential management strategies, and facilitating the understanding of the situation. It assists in directing management attention, revising company goals, and re-engineering business processes (Van Hoek 1998, Bourne et al. 2000. and Kuwaiti and Kay 2000). Henceforth, accurate performance measurement is helpful in the improvement of SCM. Many firms look to continuous improvement as a tool to enhance their core competitiveness using SCM. Many companies have not succeeded in maximizing their supply chains potential, because they have often failed to develop the performance measures and metrics needed to fully integrate their supply chain to maximize effectiveness and efficiency. Lee and Billington (1992) observed that the discrete sites in a supply chain do not maximize efficiency, if each pursues goals independently. They point to incomplete performance measures existing among industries for assessment of the entire supply chain. Measurements should be understandable by all supply chain members and should offer minimum opportunity for manipulation (Schroeder et al. 1986). Performance studies and models should be created, so that, organizational goals and achievement of those goals can be measured, thus allowing the effectiveness of the strategy or techniques employed to be accessed. The metrics that are used in performance measurement and improvement should be those that truly capture the essence of organizational performance. A measurement system should facilitate the assignment of metrics to where they would be most appropriate. For effective performance measurement and improvement, measurement goals must represent organizational goals and metrics selected should reflect a balance between financial and non-financial measures. According to Beamon (1999), very little literature on performance measurement systems (PMSs) design and performance measures was available. Three types of performance measures that are necessary components in any supply chain performance measurement system i.e. resource, output and flexibility have been identified. Beamon (1998) categorised the existing performance measures into two groups: qualitative and quantitative, involving customer satisfaction, and customer responsiveness, flexibility, supplier performance, costs and those used in supply chain modeling. Gunasekaran et al. (2004) developed a framework for measuring the strategic, tactical, and operational level of performance in a supply chain, which deals mainly with supplier, delivery, customer service and inventory and logistics costs. Chan (2003) mentioned that there was no systematic grouping of the different performance measures in the literature. Some common criteria such as cost, quality, resource utilization, flexibility, visibility, trust and innovativeness have been categorized in Chan’s (2003) work. Bhatnagar and Sohal (2005) proposed a framework which included qualitative factors concerning plant location decisions, supply chain uncertainty, and manufacturing practices. They argued that a joint consideration of such factors helps in explaining supply chain competitiveness. They discussed about 06 criteria and 30 sub criteria, divided into three parts like plant location factor, supply chain uncertainty and manufacturing practices. Gaiardelli et al. (2007) observed that since many actors are involved along the service chain, an integrated, multi-attribute and consistent set of measures needs to be properly designed at every level of the after-sales supply chain. Li et al. (2006) conceptualized and developed five dimensions of SCM practice (strategic supplier partnership, customer relationship, level of information sharing, quality of information sharing, and postponement) and tested the relationships between SCM practices, competitive advantage, and organizational performance. Their research indicated that higher levels of SCM practice can lead to enhanced International Journal of Advanced Engineering Technology E-ISSN 0976-3945 IJAET/Vol.II/ Issue IV/October-December, 2011/182-190 competitive advantage and improved organizational performance. Jammernegga and Reiner (2007) discussed the opportunities and challenges for improving the performance of supply chain processes by coordinated application of inventory management and capacity management. Gruat La Forme et al. (2007) proposed a general framework characterizing the performance of the collaboration in supply chains based on two models: collaboration characterization model and a collaboration-oriented performance model, both based on main supply chain business processes. Zhou and Benton Jr. (2007) investigated the integration of information sharing and supply chain practice in supply chain management. Their findings reflected that both effective information sharing and effective supply chain practice were critical in achieving good supply chain performance. Bhagwat and Sharma (2007) developed a balanced scorecard for supply chain management for measuring and evaluating day-to-day business operations in the context of four perspectives: finance, customer, internal business process, and learning and growth. The Supply Chain Council’s SCOR-model (2008) is an international standard for process description and reorganization, and considers five main supply chain processes: planning, sourcing, production, delivering, and return activities. Through a common set of definitions, performance indicators and best practices, the SCOR-model is a framework for a common language between supply chain partners concerning its five management processes (Gruat La et al.2007, Zhou and Benton 2007). DEVELOPMENT OF FRAMEWORK FOR PERFORMANCE MEASUREMENT OF SUPPLY CHAIN SYSTEMS The framework, within which the performance indicators in the supply chain are described, is based on a hierarchical structure. The schematic of AHP for selection of alternatives in supply chain is shown in Fig 2. The performance is evaluated on five important links of the supply chain management system like inbound logistics, manufacturing, outbound logistics, and marketing and after sales service. These links are explained in Table 1. These links are to be evaluated on the metrics. An in-depth literature review of performance measures metrics is given in Sarode et al 2008. After deciding criteria for all links in supply chain, questionnaires were designed and ask the weightages to stakeholders of all links in supply chain. The mean rating of all criteria is used to compute a pair-wise comparison matrix and compute the relative weightages for each using AHP this can be shown in Table 2. Compare each of the links (inbound logistics, manufacturing, etc) on each metric and compare the relative weightage. Since there are ten elements on level two, and five links to be pairwise compared for each element, there will be ten matrices of judgements. The Pairwise comparison for each criteria (after normalization of weightages, given in table 3) is shown in table 4. Development of analytical process Analytical hierarchy process (AHP) was developed in 1972 as a practical approach in solving relatively complex problems (Saaty 1980). It is used for multicriteria problems in a number of application domains (Roger 1987, Saaty 2000 and Kodali and Chandra 2001, Kodali and Routroy 2006, Sarode and Khodke 2009). The general approach of the AHP is to decompose the problem and make pair-wise comparison of all elements on a given level with related elements in the level just above it belong. A highly user friendly computer model is developed which assists the user in evaluating his/her choices. The schematic of AHP for selection of supplier in supply chain is shown in Fig 1. Table 1 Explanation of the links A 1 : Inbound Logistics The link between the supplier and operations is provided by the inbound logistics A 2: Operations The operations functions will include evaluation of facilities, WIP inventory policies and communication within the