performance evaluation of supply chain management systems: a critical review of literature

Int. J. Procurement Management, Vol. 7, No. 2, 2014 201

Copyright © 2014 Inderscience Enterprises Ltd.

Performance evaluation of supply chain management systems: a critical review of literature

Rohit Kumar Singh* ABV-Indian Institute of Information Technology and Management, Room No. 05, BH-3, Gwalior (MP), PIN-474015, India E-mail: [email protected] E-mail: [email protected] *Corresponding author

Padmanav Acharya ABV-Indian Institute of Information Technology and Management, Room No. 109, Block D, Gwalior (MP), PIN-474015, India E-mail: [email protected] E-mail: [email protected]

Abstract: To make the supply chain operations more effective and for better customer satisfaction, organisations need to evaluate their process and measure the supply chain performance so that improvement in the process can be made on a continuous basis. Supply chain is a dynamic function of organisation that changes with time, there are several factors that influences its performance. Each organisation has its unique supply chain structure so the critical factors that influence its performance also vary from organisation to organisation. Till date many researchers have given their insights towards supply chain performance management. In this paper, we did a critical review of previously done researches and find out the critical factors having their significant impact on supply chain performance. The paper also made a summary discussion on the performance measurement tools popular among researchers such as AHP, DEA, BSC, SCOR, etc.

Keywords: supply chain management; SCM; critical factor; performance evaluation; balance score card; BSC; supply chain operations reference; SCOR; data envelopment analysis; DEA; AHP; fuzzy logic.

Reference to this paper should be made as follows: Singh, R.K. and Acharya, P. (2014) ‘Performance evaluation of supply chain management systems: a critical review of literature’, Int. J. Procurement Management, Vol. 7, No. 2, pp.201–218.

Biographical notes: Rohit Kumar Singh obtained his Bachelor degree in Mechanical Engineering from the Uttar Pradesh Technical University followed by his Master’s degree in Business Administration from the IIIT Gwalior. Currently, he is pursuing his PhD in Area of Supply Chain Management from the ABV – Indian Institute of Information Technology and Management Gwalior. His area of interest lies in operations and supply chain management and has published papers in national and international journals.

202 R.K. Singh and P. Acharya

Padmanav Acharya is an Associate Professor in ABV-IIITM, Gwalior. He has done his MTech and PhD from the IIT Kharagpur after his BTech in Mechanical Engineering from the Utkal University. He has 18 years of teaching experience. He has published several papers in journals of international and national repute and also presented papers and chaired sessions at international and national conferences. He has been a reviewer of prestigious international journals. His areas of interest include software engineering and management, busyness system simulation, and operations management.

This paper is a revised and expanded version of a paper entitled ‘Performance evaluation of supply chain management system: a critical review of literature’ presented at BPSCM-2012, Bhubaneswar, India, 22–23 November 2012.

1 Introduction

In the recent years, performance measurement of supply chain performance has become the hot topic for researchers, number of researchers has given their insights to measure and to improve the performance of supply chain, also develops various performance measurement systems. Performance measurement of supply chain management (SCM) is a rapidly growing multi-criteria decision-making problem owing to the large number of factors affecting decision-making (Bhagwat and Sharma, 2007). According to Christopher (1998), supply chain is the network of organisations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services in the hands of ultimate consumer. So, the performance of any supply chain depends on performance of all supply chain member or partner organisations. Companies operating in supply chain networks (SCN) need to synchronise existing business processes and data before the design of a new PMS (Papakiriakopoulos and Pramatari, 2010). For any supply chains, the general processes and structure can be integrated into six core processes that are linked; supplier, inbound logistics, manufacturing, outbound logistics, marketing and sales, and end customers (Thakkar et al., 2009). So, the supply chain performance typically depends on all those parameters. Performance measurement of SCM systems helps company to prioritise and formulate viable performance measurement strategies in the volatile and complex global decision environment. A number of researchers have developed the performance measurement systems by taking different attributes of supply chain and made performance measurement matrices. Performance measurement system of any supply chain primarily indicates the deviation from objectives and the probable reasons of deviation and aligns the communication strategies from top management to shop floor executives. The development of a collaborative PMS is a challenging task (Papakiriakopoulos and Pramatari, 2010), mainly because of identifying the key performance dimension according to supply chain structure as it varies organisation to organisation according to their business process. Cagnazzo et al. (2010) discussed that performance measurement system not only works towards enhancing the performance of organisation but also supports in quality improvement initiatives of organisation.

Supply chain performance measurement is a context-dependent process, tailored to specific supply chain requirements. To understand how a performance measurement system in a supply chain has developed and is used there is a need to capture its context,

Performance evaluation of supply chain management systems 203

process and content (Cuthbertson and Piotrowicz, 2011). Nowadays, business environment is highly volatile in nature, lots of uncertainties and risks are present, and influences working of supply chain. According to Palaniswami et al. (2010), the management of an extended SCN in terms of risk and security has become very complex. The performance of supply chain in this kind of environment depends upon organisation capability to cope up with uncertainties and the extent of flexibility it has. For, e.g., Sourcing of material is done with multiple suppliers but risk is always present in terms of supplier availability or material availability. Identified perceived risks are classified as performance and relational risks managed by trust and control mechanisms (Kumar et al., 2011). To cater with these kinds of risks and maintain the level of supply chain performance a company should have multiple suppliers of single products so that availability of material can be ensured.

1.1 Objective/purpose

The purpose of this paper is to analyse the existing literature to find out the critical factor of supply chain that have significant role in measuring its performance.

2 Why performance measurement?

Performance measurement is critical to assess the way a particular supply chain is operating. It is key to know whether a supply chain is efficient or not, and whether a supply chain is responsive enough to satisfy customer demand or not. Performance measures provide data and information necessary to take corrective measures. Performance measurement enables officials to hold organisations accountable and to introduce consequences for performance. Performance measurement may be done annually to improve customer accountability and policy decision making (Wholey and Newcomer, 1997). Each and every attribute of supply chain participate in its performance, for, e.g., buyer supplier relationship, delivery time, logistics process, information sharing, etc. Fantazy et al. (2011) look at the role of information sharing on supply chain performance that environmental uncertainty, internal integration, and external integration positively impact information sharing. Information sharing has a positive and direct impact on operational and financial performance, and it enhances the supply chain performance. Barros et al. (2011) presented the results of a case study about the use of a common scorecard to share performance measurements between buyers and suppliers. Banomyong and Supatn (2011) developed a supply chain performance assessment tool to measure the performance of firm’s key supply chain activities under different performance dimensions.

Gunasekaran and Kobu (2007) talks about the essentiality of performance measurement of supply chain and gave the reasons why it is important in today’s scenario:

1 identifying success weather the firm and its supply chain is performing as per expectation or not

2 to identify weather the supply chain are capable enough to meet customer needs

3 to have better understanding of processes


4 to identify where the actual problem exist and improvement opportunities

5 helpful in providing factual decisions

6 enabling progress

7 tracking progress

8 to facilitate a more open and transparent communication and cooperation.

Supply chain is a direct linkage between customer and organisation, so to attain better customer satisfaction and to enhance the service delivery standard, it is essential to evaluate and measure the performance, so that corrective measure can be placed at right time. For any business activity, such as SCM, which has strategic implications for any company, identifying the required performance measures on most of the criteria is essential and it should be an integral part of any business strategy (Bhagwat and Sharma, 2007). Performance can be measured in terms of certain performance measures that may vary from organisation to organisation as per their supply chain system. SCM is a strategic key to improve operational performance, and facilitates achieving its organisational goals. Performance measurement reflects the need for improvement in areas with unsatisfactory performance (Chan and Qi, 2003), so it is clear that to make the supply chain operations more effective and for better customer satisfaction, organisations need to evaluate their process and measure the supply chain performance so that improvement in the process can be made on continuous basis.

3 Methods of performance measurement

Various authors have adopted different techniques to measure the performance of supply chain.

3.1 Balance score card

Kaplan and Norton (1992) proposed the balanced score card framework to evaluate the performance of a system, they proposed the four major perspective of balance score card: financial, internal business process customer, learning and growth, Bhagwat and Sharma (2007), and Thakkar et al. (2009) used balance score card approach to measure the performance of supply chain. According to Bhagwat and Sharma (2007) implementing the balance score card (BSC) has meant adopting new measures that were not used earlier in all case companies. In the research they conducted on performance measurement of supply chain, they observed that most interviewees stated that BSC has forced them to select the most important measures from the existing ones and helped them to focus their attention. According to Valmohammadi and Servati (2011), statistical method in combination with BSC could help organisations to design and implement a sound performance measurement system. According to Chavan (2009), the process of BSCs are: • clarify and translate vision into strategy • communicate and link strategic objectives and measures • plan, set targets and aligns strategic initiatives • enhance strategic feedback and learning.


The BSC approach provides a comprehensive picture of the enterprise performance at a glance. The balanced scorecard approach provides a clear prescription as to what companies should measure in order to ‘balance’ the financial perspective.

Figure 1 Balance score card

Source: Kaplan and Norton (1996)

3.2 Supply chain operations reference

The supply chain operations reference (SCOR) model, developed by the supply-chain council (SCC), is widely accepted as the only cross-industry standard for SCM, which not only provides a standard description of supply chain processes, but standard metrics to measure supply chain performance. According to Cirtita and Segura (2012), the scope of the SCOR model includes all elements of demand satisfaction starting with the initial demand signal (order or forecast) and finishing with the signal of satisfying the demand (final invoice and payment). SCOR provides an opportunity to include the measures which can capture the performance of many overlapping activities of the various entities in supply chain (Thakkar et al., 2009). The SCOR model provides a framework for characterising supply-chain management practices and processes that result in best-in-class performance (Lockamy and McCormack, 2004). According to SCC SCOR is based on five core management process: plan, source, make, deliver, and return.

• Plan: Processes that balance aggregate demand and supply to develop a course of action which best meets sourcing, production and delivery requirements.

• Source: Processes that procure goods and services to meet planned or actual demand.

• Make: Processes that transform product to a finished state to meet planned or actual demand.


• Deliver: Processes that provide finished goods and services to meet planned or actual demand, typically including order management, transportation management, and distribution management.

• Return: Processes associated with returning or receiving returned products for any reason.

These processes extend into post-delivery customer support

Figure 2 SCOR model

3.3 Data envelopment analysis

Data envelopment analysis (DEA) has been recognised as a valuable analytical research instrument and a practical decision support tool. In the DEA methodology, formally developed by Charnes et al. (1978), efficiency is defined as a ratio of weighted sum of outputs to a weighted sum of inputs, where the weights structure is calculated by means


of mathematical programming and constant returns to scale (CRS) are assumed. DEA provides a comparative measure of efficiency, which is good for evaluating companies’ performance and for benchmarking (Joo et al., 2012). Zhu (2002) provides a number of DEA spreadsheet models that can be used in performance evaluation and benchmarking. Saen (2009) proposed method for ranking suppliers in the presence of non-discretionary factors using DEA.

DEA is a relatively new ‘data oriented’ approach for evaluating the performance of a set of peer entities called decision making units (DMUs) which convert multiple inputs into multiple outputs. DEA originated from the work by Charnes et al. (1978), have proven to be an effective approach in measuring the relative efficiency of peer units when multiple performance measures are present (Wu, 2008). DEA model is created to appraise the overall technical efficiency of supply chains.

3.4 Fuzzy logic

According to Ordoobadi (2009), fuzzy logic allows the decision makers to express their preferences/opinions in linguistic terms. Fuzzy set theory has diverse applications and has been used in the managerial decision making for handling uncertainties and imprecise information involved in the process. With fuzzy logic, propositions can be represented with degrees of truthfulness and falsehood. In many real-world applications, fuzzy systems that make use of linguistic rules are aptly suited to describe the behaviour of the real-world problem, which is difficult to model mathematically (Zadeh, 1978). For, e.g., supplier selection is one of the most important and complex functions to be performed by the purchasing department, Gnanasekaran et al. (2010) used fuzzy AHP approach and developed a method for supplier selection. Fuzzy logic is a problem solving methodology that provides a simple way of definite conclusions from vague and imprecise information. Fuzzy sets provide a conceptual framework, as well as an analytical tool to solve real world problems where there is a lack of specific facts and precision (Klir and Yuan, 1995).

3.5 Analytical hierarchy process

AHP is a multi-criteria decision-making tool developed by Saaty (1980). The AHP is a systematic procedure for representing the elements of any problem, hierarchically. AHP is a tool to find the optimal outcome from a multiple criteria scenario by employing a hierarchal approach to arrive at best solution. The belief is that a complex decision-making problem is decomposed into smaller and simpler decision-making problems that contribute to achieve the initial goal (Lee and Ross, 2012). Some researchers have used AHP technique in combination with BSC to measure the performance of supply chain (Bhagwat and Sharma, 2007). Rajkumar et al. (2009) established a vendor selection system using AHP from the customer satisfaction orientation and showed how the customer-focused AHP is able to select the most efficient vendor. The AHP method can support managers in a broad range of decisions and complex problems – including supplier-selection decisions, facility-location decisions, forecasting, risks and opportunities modelling, choice of technology, plan and product design, and so on (Fariborz et al., 1989). The AHP approach is able to use criteria, which are not easy to quantify and this model can help in


determining relative importance of criteria in the shape of weights taking into account the views of different experts (Varma et al., 2008).

Figure 3 Typical structure of AHP

4 Performance measurement

In line with the literature, we have discussed regarding effectiveness of performance management, here is some key research work done by the authors from the period of 1995–2010 where we have highlighted the important measures of supply chain as carried out in industry.

Supply chain basically works towards fulfilling the customer’s requirement. Various processes and parties involved in the supply chain directly or indirectly should be evaluated in terms of parameters such as: cost, delivery time, responsiveness, etc., to make the process better and enhance the level of customer satisfaction that would be a direct benefit for the organisation. Table 1 Selective author’s views on performance management

Author(s) Views on performance management

Neely et al. (1995) Performance measurement is the process of quantifying the effectiveness and efficiency of action.

Bititci et al. (1997) The performance management process should be seen as a closed loop control system which deploys policy and strategy, and obtains feedback from various levels in order to manage the performance of the business.

Pires and Aravechia (2001) Performance measurement can be defined as the information regarding the processes and products results that allows the evaluation and the comparison in relation to goals, patterns, past results and with other processes and products.


Table 1 Selective author’s views on performance management (continued)

Author(s) Views on performance management

Chan and Qi (2003) Performance management provides the necessary assistance for performance improvement in pursuit of supply chain excellence.

Taylor (2004) Supply chain performance measurement could be initiated by examining characteristics of customer demand, internal implementation, manufacturer supply, and the information environment.

Kongar (2004) An efficiently managed supply chain can lead to reduced response time for customers. To achieve this, continuous observation of supply chain efficiency, i.e., a constant performance evaluation of the current SCM is required.

Park and Chang (2010) The companies whose own capability matches their supplier selection criteria can expect better supply chain performance from SCM practice than non-matching companies.

Neely and Bourne (2000) and Meekings et al. (2009)

To effectively use a performance measurement system, organisations need to have systematic mechanisms for extracting maximum value from the measurement data

5 Performance measurement of supply chain: a critical review

5.1 Performance measurement through modularisation and postponement

According to Ernst and Kamrad (1999), in their paper on evaluation of supply chain structures through modularisation and postponement “Concepts of outsourcing and postponement allow companies to combine economies of scale and scope through the integration of product and process design”. They have introduced a conceptual framework to evaluate the best appropriate supply chain structure is the most appropriate choice. Based on the degree of outsourcing and postponement organisations can compare and contrast varying supply chain structures. This paper introduces a conceptual framework for evaluating different supply chain structures in the context of modularisation and postponement. In their analysis modularisation is directly linked with inbound logistics and postponement is related to outbound logistics. They have done their analysis on four kinds of supply chain structures according to the combined levels of modularisation and postponement namely, Rigid, postponed, Modularized and Flexible. Also, they have made comparison among these supply chain structure by doing cost analysis. In this paper, they proposed a conceptual framework that which supply chain is the most appropriate choice. According to them companies should go for combination of modularisation and postponement and they set aside the concept of vertical integration as it is not desirable and many companies are replacing it with vertical coordination.

Valmohammadi and Servati (2011) designed an implementation model for a performance measurement system based on a combined approach of BSC and statistical methods. The authors did a SWOT analysis to identify the firm’s objective. The authors also found out the strategic measures of organisation based on all four perspective of BSC and then compared those strategic measures against other leading companies of same industry. At initial level authors took 77 strategic measure of performance and after statistical analysis they have eliminated less important measures and then developed a


BSC framework to measure the supply chain performance. The authors also made a strategic map of company and strategy linkage model those have influence over each other. The strategic linkage model of the company shows precisely the inputs and outputs of the objectives and is a good guide for everyone in the company starting from top management to shop floor employee. Then a comparison among case firm and other leading firms of same industry is done to find out where the case firm is lagging behind, so this approach is beneficial to find out the gaps and identify the way to fulfil those gaps in order to enhance the supply chain performance.

5.2 Performance measurement through balanced approach (financial and non-financial)

Gunasekaran et al. (2001) in the paper on ‘Performance measures and metrics in a supply chain environment’ made an attempt to develop a framework for measuring the strategic, tactical and operational level performance in a supply chain. In this paper, they worked on the need for performance measurement and metrics in a supply chain and the identification of measures and metrics in the areas of planning, sourcing, make/assembly decisions, delivery, and customer service level and finally they have developed a framework in order to measure the performance in supply chain environment. According to them there are two basic reasons for the need of performance measurement and metrics in a supply chain. The first one is ‘lack of balanced approach’. Balanced approach in terms of financial and non-financial measures of supply chain. Many companies failed to make balance between financial and non-financial measures while according to Maskell (1991), for a balanced approach, companies should bear in mind that, while financial performance measurements are important for strategic decisions and external reporting, day-to-day control of manufacturing and distribution of operations is better handled with non-financial measures. The second reason is “Lack of a clear distinction between metrics at strategic, tactical, and operational levels”. According to them metrics should be used while taking decisions at all three levels. In the same paper, the authors have also discussed about performance measures of supply chain on basis of six parameters. The first one is performance evaluation of planned order procedures in which they have discussed about how order related activities are carried out. According to them order entry method should be proper enough so that information feed can be used down the supply chain appropriately. Also, to achieve the better satisfaction level of customers organisation should try to become fast responsive hence to shorten the lead time. Next, parameter is supply chain partnership metrics in which they discussed the importance of good partners in supply chain. A strong partnership emphasises direct, long-term association, encouraging mutual planning and problem solving efforts. The third performance evaluation criteria are production level measures, in which they have discussed the range of products and services acts as an important strategic metric, and hence, it should be considered in performance evaluation. Capacity utilisation should be measured in order to gain in flexibility, lead-time and deliverability. Effectiveness of scheduling techniques should be measured because it refers to the time or date at which activities are to be undertaken. Measuring and improving effectiveness of scheduling techniques will improve the performance of a supply chain. The fourth measure is performance evaluation of delivery link; this is directly connected to the customer. Delivery link can be evaluated on the basis of ‘on time delivery, delivery cost and


response time’. The other performance measure is ‘measuring customer service and satisfaction’ customer satisfaction can be measured in terms of flexibility, i.e., making available products/service to meet the demand of customers., customer query time, i.e., how quick company officials are to respond to the customer’s query, post transaction measures of customer query, i.e., to help customer after the product/service has been sold out to him. The last measure is ‘supply chain finance and logistic cost’. According to the authors “The financial performance of a supply chain can be assessed by determining the total logistics cost”. The performance can be measured by measuring the cost associated with assets and return on investment and total inventory cost.

The authors have also proposed a framework in order to measure the performance of supply chain. Performance metrics on all three levels (strategic, tactical, and operational) was proposed. All the factors in the metrics were segregated into financial and non-financial in order to make the balance between them. Finally, each organisation needs to capitalise on supply chain capabilities and resources to bring products and services to the market faster, at the lowest possible cost.

5.3 Performance measurement through radar chart methodology

A research was carried out by Pires and Aravechia (2001) on measuring supply chain performance. In the paper, the authors have proposed a model comprising of the structure, design, implementation and management of a supply chain performance measurement system. The authors’ emphasis that performance evaluation should be on basis of different indicators but most commonly, companies do it on basis of cost incurred because it is relatively simple to measure on basis of single indicator. The better alternative would be to combine the cost with time, flexibility and quantity. The authors have also explained model developed by Pinto (1998) for evaluating the performance of supply chain. According to the model (for a sole business unit) once organisation determine the indicator of performance management, it can be segregated into three parts:

1 resources

2 exits

3 flexibility.

All the indicators can be placed on circular shape by dividing the circle into three equal parts. Now, against each indicator two points can be made, one is for desired performance and second one is for effective performance. One polygon can be made after connecting each point of desired performance and second polygon can be made by connecting points of desired performance. The area between both the polygons is improvement area where a company need to work (Radar Diagram Methodology).

The advantage of this kind of radar chart lies in the construction flexibility and in the easy visualisation of the performance indicators. By use of this diagram it would be easier to evaluate the performance of each business unit participating in a company’s supply chain. The paper also discuss the necessity that supply chains have to achieve, simultaneously, a high efficiency level and the ability to react, in an efficient way, to frequent changes in the competitive environment. It also deals with the performance indicators determination for the evaluation of the whole productive chain.


5.4 Performance measurement through BSC

Chang (2009) has done an empirical study on evaluating the performance of supply chain integration. The author has taken a select case-based approach and utilised the case studies, and based on findings he modified a research model. The author attempted to evaluate SCM integration by using Kaplan and Norton’s BSC metrics. Initial research model using BSC to evaluate SCM performance divides SCM integration into six dimensions: customer integration, internal process integration, supplier services and material integration, technology and planning integration, measurement integration, and relationship integration. And performance evaluation was judged on four parameters: financial perspective, customer perspective, business process perspective, innovation and learning perspective. Data collection was done by sending online questionnaire to 1,000 companies. In statistical analysis (regression) it was found that SCM integration is significant predictor of performance evaluation.

5.5 Performance measurement based on different dimensions

Beamon (1999) reviewed the literature on measuring supply chain performance and found out that supply chain models have predominantly utilised two different performance measures, the first one is cost and the other one is combination of cost and customer responsiveness. Cost in terms of operation cost and inventory cost, etc., while customer responsiveness in terms of lead time, delivery time, fill rate, etc. Cost, activity time, customer responsiveness, and flexibility have all been used as supply chain performance measures either singly or jointly. The author has bifurcated the measure of supply chain in three ways. First one, is single supply chain performance measures-organisations use single factor to measure the performance because of its least complexity but single measure is useful when it itself describe the overall system performance. The second one is cost as a single supply chain performance measure: in this cost is considered as the sole measure of performance, but lack of relevance of the cost categories, cost distortions (especially overheads), and inflexibility, such as reports that are too late to be valuable. Third and the last one are strategic goals and supply chain performance measures: in this organisations need to find out their strategic goals, and on basis of these goals, performance measure is decided. For, e.g., XYZ Company’s strategic goal is to produce high quality products in variety of ranges, quality would be the performance measure. The authors have also designed a new framework for supply chain performance measure. According to the proposed framework SCM system must give emphasis on three kinds of performance measurement: resource measures (R), output measures (O), and flexibility measures (F). The authors also have proposed the interrelation ship among three types of performance measurement.

This research discusses the importance of a supply chain system to achieve simultaneously a high level of efficiency, a high level of customer service and the ability to respond effectively to a changing environment The categorisation of supply chain performance measures resulted in the identification of three types of performance measures that are necessary components in any supply chain performance measurement system: resource, output and flexibility.


5.6 Performance measurement through integrated SCOR-BSC approach

Thakkar et al. (2009) in their paper proposed an integrated SCOR-BSC-based framework for measuring the performance of supply chain in order to enhance the effectiveness of supply chain functions of small and medium enterprise. SCOR enables users to address, improve, and communicate SCM practices within and between all interested parties in the extended enterprise. The authors have worked on finding performance indicators of supply chain process ‘Source, make, deliver’ they have also generated the guidelines for implementing the framework in small and medium enterprises.

Based on the above literature discussed, following measures of supply chain can be put in a model to evaluate the performance of supply chain. Table 2 Summary table

Author(s) Proposed framework Factors of performance measurement

Ernst and Kamrad (1999) Modularisation postponement

Inbound logistics outbound logistics

Balanced approach Planned order procedures a Financial Supply chain partnership b Non-financial Production level Metrics Delivery link a Strategic Customer service and satisfaction b Tactical

Gunasekaran et al, (2001)

c Operational Supply chain finance and logistic cost

Manufacturing cost Inventory cost Distribution cost Delivery time

Resource measures

Customer response time Customer complaints Volume flexibility

Exit measures

Delivery flexibility Product mix flexibility

Pires and Aravechia (2001)

Flexibility measures

Financial perspective (SCM integration) Customer perspective Customer

Internal process Supplier/service Technology and planning Measurement

Chang (2008)

Business process perspective innovation and learning perspective

Relationship


Table 2 Summary table (continued)

Author(s) Proposed framework Factors of performance measurement

Inventory levels

Personnel requirements equipment utilisation

Energy usage

Resource

Cost

Customer responsiveness

Quality

Output

Product quantity

Volume fluctuation

Beamon (1999)

Flexibility

Schedule fluctuation

Combination of Customer service

a SCOR Finance and marketing

Internal business

Thakkar et al. (2009)

b BSC

Innovation and learning

Increased income and profit

Cost reduction

Utilisation of financial resource

Financial perspective

Stock market participation

Customer satisfaction Customer perspective

Internal market share

Materials and energy efficiency

Production technology

Business process perspective

Supply chain of raw material

Employee satisfaction

Successors for key positions

Internalisation of objectives

Thriftiness culture

Valmohammadi and Servati (2011)

Innovation and learning perspective

Involvement of employees

6 Discussion

Supply chain is integration of different business entities works together, interact with each other in order to provide service to end customer. So, the ultimate objective of any supply chain is to attain customer satisfaction at maximum extent. In an extreme


turbulent and highly competitive market, firms are working to make the supply chain as robust as possible, and are working in collaborate with all its supply chain partners to improve the performance of entire supply chain. Supply chain integration enhances its performance. According to Bagchi et al. (2005) “The conventional wisdom in most SCM literature is that the more integration – the better the performance of the supply chain”. Here, in this paper authors have talked about various frameworks proposed by eminent authors in order to improve and enhance the supply chain performance. The most widely used and accepted framework to measure the performance of supply chain is BSC, the unique attribute of BSC is, it takes both financial and non-financial measures which have direct impact on supply chain performance. The most common measure what almost all authors have identified is supply chain cost that includes delivery cost, inventory cost, distribution cost, logistics cost, etc. Cost directly influence the return on investment of company, and it is obvious that higher the cost would cause either higher in price of product or lower down the profit of organisation. The other important measure that comes out is customer service and satisfaction. Customer satisfaction is directly link with the on time deliver, organisation responsiveness to customer complaints, customised service, quality of service/products, etc. Organisations need to make changes in product and its business process as per the requirement of customer. Higher the customer satisfaction would reflect the higher success rate of any supply chain.

7 Conclusions

In this paper the important aspects of performance evaluation of a SCM system has been outlined. Performance evaluation usually emphasises on two often contrasting aspects such as efficiency (a cost oriented approach) and the customer responsiveness. The paper made a summary discussion on the management tools popular among researchers such as AHP, DEA, BSC, SCOR, etc. Finally, the paper highlighted sum of the key research literature in last decade related to performance measurement of SCM system and presented the broad framework, proposed model as well as the associated measurement metrics in a summary table for comparison and future direction of research in this field which attracts plenty of attention from academic and industry alike.

This paper talks about the proposed framework to measure the supply chain performance given by eminent authors, and different measurable attributes having their direct impact on supply chain performance. In Table 2, the authors have summarised the results and pointed out the key factors that influence supply chain performance.

The study is all about the proposed frameworks and methodology of performance measurement of supply chain; however study does not validate the frameworks by quantitative analysis. There is a strong need to compare the proposed frameworks through case study and quantitative analysis.

Acknowledgements

We would like to thank all the reviewers for finding time to review the paper and providing critical comment on study. The review comments were very useful in improving the quality of paper and also their suggestions helped me to make the content publishable in International journal.


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performance evaluation of supply chain management systems: a critical review of literature

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