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International Journal of Productivity and Performance ManagementEmerald Article: A review on supply chain performance measures andmetrics: 2000-2011

P.R.C. Gopal, Jitesh Thakkar

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P.R.C. Gopal, Jitesh Thakkar, (2012),"A review on supply chain performance measures and metrics: 2000-2011", Internationalournal of Productivity and Performance Management, Vol. 61 Iss: 5 pp. 518 - 547

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A review on supply chainperformance measures and

metrics: 2000-2011P.R.C. Gopal and Jitesh Thakkar

Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur, India

Abstract

Purpose – The paper reports a comprehensive review of supply chain performance measurementsystems and raises a set of research issues leading to selected research questions.

Design/methodology/approach – The articles which have been published in selectedpeer-reviewed international journals in the last ten years were collected by using databases Scopusand ISI Web of Knowledge. The articles were scrutinized based on authors’ perspective analysis (usingsupply chain measures and metrics, and enhancing supply chain performance as the key perspectives).The articles contributing significantly in the domain of supply chain measures and metrics wereselected for final review and various issues were identified.

Findings – The paper argues that, despite considerable evidence from the literature in supply chainperformance measurement in recent years, there is a large scope for research to address the issues insupply chain performance measurement, including: characteristics of measures and metrics,benchmarking of measures, use of management practices, integration and partnership andsocio-environmental relevance.

Research implications/limitations – The insights deduced in the paper are primarily based on 28articles selected for critical review and analysis in the domain of supply chain measures and metricsand hence should be interpreted only as key concerns in the area.

Originality/value – The paper reports an evaluation of 28 key articles reported in the domain of supply chain performance measurement and indicates the research opportunities in the area.

Keywords Supply chain management, Performance measurement, Supply chain metrics,Distribution and inventory management

Paper type Literature review

1. IntroductionIn the last three decades, a plethora of literature has been generated in the area of performance management. Researchers have focused initially on business performance(Venkatraman and Ramanujam, 1986), its importance, definitions of performancemeasurement, measures and system (Neely, 1999), models and frameworks (Kaplan

and Norton, 1992; Fitzgerald et al., 1991; Heskett et al., 1994; Neely et al., 1996; Kanji,1998; Bititci et al., 2000; Epstein and Westbrook, 2001; Neely et al., 2001; Ratnatungaet al., 2004). Subsequently the perspective of performance management (PM) has beenexpanded to various areas such as lean manufacturing, logistics and supply chain. Thecore purpose of a performance measurement system (PMS) is for quantifying theefficiency and/or effectiveness of action (Neely et al., 1995). A PMS can be analyzed byasking questions such as “What performance measures are used? What are they usedfor? How much do they cost? And what benefit do they provide?” (Neely et al., 1995). Toaddress these questions PMS can be seen to comprise key performance indicators

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1741-0401.htm

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518

Received 20 September 2011Revised 2 January 2012Accepted 3 January 2012

International Journal of Productivity

and Performance Management

Vol. 61 No. 5, 2012

pp. 518-547

q Emerald Group Publishing Limited

1741-0401

DOI 10.1108/17410401211232957


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(KPIs), which may be seen as a representative set of measures, and logically establishinterrelationships among those measures. These KPIs comprise a set of both financialand non-financial measures (Kaplan and Norton, 1992). Initially the literatureemphasized financial measures such as profit, return on investment, productivity, sales

and efficiency, as the cost accounting and management control systems were designedbased on these measures (Nudurupati et al., 2011). However, due to the changes in theworld market during the late 1980s and early 90s many academicians and practitionersbegan to diagnose the problems with the traditional financial measures, which areinternal and historical based (Dixon et al., 1990; Johnson and Kaplan, 1987; Kaplan andNorton, 1992; Keegan et al., 1989; Neely et al., 1995; Nudurupati et al., 2011).

Commentators believe performance measures and metrics will facilitate a moreopen and transparent communication between people, leading to a co-operativesupported work environment and hence improved organizational performance(Gunasekaran and Kobu, 2007). However, design, implementation, and use of a setof performance measures are not a one-time effort; a firm should install processes thatensure continuous review of the system (Beamon, 1998; Bourne et al., 2000; Medori and

Steeple, 2000). Performance measures and metrics are not just measuring objectivelythe performance; they are also embedded with politics, emotions and several otherbehavioral issues (Gunasekaran and Kobu, 2007). Shepherd and Gunter (2006)highlighted the contemporary performance measurement issues such as, the factorsinfluencing the successful implementation of performance measurement systems(Bourne et al., 2000), the forces which shape the evolution of performance measurementsystems (Kennerley and Neely, 2000, Waggoner et al., 1999) and how to maintainperformance measurement systems over time so they remain aligned with dynamicenvironments and changing strategies (Bourne et al., 2000; Kennerley and Neely, 2003).PMS in the context of a supply chain becomes more important. Many organizations areendeavoring to capture the benefits of shorter lead times, flexibility in production, firstmover advantages (shorter product development time) and win-win approaches. Chow

et al. (1994) were probably the first to attempt to define supply chain (logistics)performance and they presented some measures for measuring logistics performance(Chia et al., 2009). The supply chain definition broadened due to factors such asdevelopments in information systems and technologies, businesses becomingincreasingly boundary-less (Puigjaner and Lainez, 2008), increased challenges of globalization, increased use of outsourcing, vendor managed inventory, advancedplanning systems (APS) and increased demands of integration (Meixell and Gargeya,2005). A supply chain measurement system is seen to be more than a disparateassortment of individual metrics. It has to be valid, robust, integrative, economical andcompatible (Caplice and Sheffi, 1994). Designing the supply chain performancemeasurement system is a challenging task; it needs practical guidelines. Brewer andSpeh (2000) recommend the following amendments to the performance tools and

models across the supply chain to counter the following issues:. Overcoming mistrust . Traditional SCM practices have been adversarial. Trust in

data sharing, acquisition and monitoring needs to be built.. Lack of understanding . Multi-organizational measures are difficult to understand

for managers focused on internal systems.. Lack of control. Managers and organizations wish to be evaluated on measures

they can control. Inter-organizational measures are difficult to manage and thuscontrol.

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. Different goals and objectives. Differing organizations have different goals andthus would argue for differing measures.

. Information systems. Most corporate information systems are incapable of gathering non-traditional information relating to supply chain performance.

. Lack of standardized performance measures. Agreed upon measures in terms of units to use, structure, format, etc. may not exist.

. Difficulty in linking measures to customer value. Linkage to stakeholder value(expanding to environmental issues) is becoming more complex. The definitionof who the customer may be inside a supply chain also is not clear.

. Deciding where to begin. Developing supply chain-wide performance is difficultsince it is not always clear where boundaries exist.

Unfortunately, there is little evidence of systematic empirical research on theimplementation of performance measurement systems (Bourne et al., 2000; Neely et al.,2000; Nudurupati et al., 2011). Most of the academic literature and practitioner activityhas focused on the early stages of the development of the performance measurementsystem, the conceptual frameworks and processes for designing the performancemeasures. But only a few longitudinal studies of the implementation and continuousupdating of performance measurement systems are available (Bourne et al., 2000).Therefore, implementation as well as using and updating performance measurementsystems has received attention only in recent years (Bititci et al., 2005; Bourne et al.,2000; Kennerley and Neely, 2003; Nudurupati and Bititci, 2005; Nudurupati et al., 2011).It was found that much of the criticisms on measurement systems designed to evaluatethe performance of supply chains, match with those in the wider performancemanagement literature (see Neely et al., 1995; Shepherd and Gunter, 2006). The issuesinclude:

.

lack of connection with strategy (Beamon, 1999; Chan and Qi, 2003; Gunasekaranet al., 2004);

. focus on cost to the detriment of non-cost indicators (Beamon, 1999; De Toni andTonchia, 2001);

. lack of a balanced approach (Beamon, 1999; Chan, 2003);

. insufficient focus on customers and competitors (Beamon, 1999);

. loss of supply chain context, thus encouraging local optimization (Beamon,1999); and

. lack of system thinking (Chan, 2003; Chan and Qi, 2003).

However, researchers have addressed some criticisms such as implementation issuesin PMS (Micheli and Neely, 2010); and balanced scorecard (Thakkar et al., 2009,Gunasekaran et al. (2001). But the current research has not adequately addressed arange of potential issues (Shepherd and Gunter, 2006). These include:

. less attention on systematic collation of measures for evaluation of supply chainperformance;

. lack of addressing the integration issues of modern manufacturing practices andperformance measurement systems;

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. ongoing management of performance measurement systems, or the forcesaffecting their evolution over time (Waggoner et al., 1999; Kennerley and Neely,2002, 2003);

. few empirical studies of the factors influencing the success or failure of attempts

to implement performance measurement systems; and. need of international benchmarking of supply chain performance.

Interestingly, authors have found that in addition to the above-mentioned list, someother issues such as those related to socio-environment, integration and KPIs play akey role in the development of a supply chain performance system. The literaturesupporting these findings is presented in section 2.

1.1 Supply chain performance: measures and metricsThe first universal performance measures that were used in supply chain performancemeasurement were generated by Pittiglio, Rabin, Todd and McGrath, widely known asPRTM (Wong and Wong, 2008). Interest in performance measurement and

management has notably increased in the last 20 years (Taticchi et al., 2010). Theeffects of globalization, technology and the growing need for environmentalresponsibility and sustainability is forcing organizations and individuals to makechanges in the way they live, work and play (Bititci et al., 2008). Hence, it is critical todevelop an efficient (efficiency is a measure of how economically the firm’s resourcesare utilized when providing a given level of customer satisfaction Neely et al., 2005)supply chain performance measurement system. However, monitoring andimprovement of performance of a supply chain has become an increasingly complextask (Cai et al., 2009). Practitioners should know about what measures they should use?When to use? How to analyze the performance of supply chain by using suitablemeasures? The reason for this complexity is performance measures differ from contextto context. The notion of a “right supply chain strategy” cannot be generalized. There

has to be synchronization between supply chain strategy (such as risk hedging,efficient, responsive and agile) and characteristics of the product (functional vs.innovative). The issue gets further complicated when it comes to evaluating supplychain strategy for different structures of supply chain (such as liner, network,amorphous). This demands a critical evaluation of a supply chain performancemeasurement system before it can be generalized for a given industry. Further, thecomposition (right mix of measures) of the supply chain performance measurementsystem will differ in relation to desired competencies (agility-adaptability-alignment)of a supply chain. This justifies the importance of developing, and improving thesupply chain measures from time to time.

Selection of supply chain measures is critical because managers have to evaluatesupply chain on various aspects as a whole entity rather than on an individual basis.

Decision-makers in supply chains focus on developing measurement metrics forevaluating performance (Beamon, 1999; Gunasekaran et al., 2004). Gunasekaranet al.(2001) have provided an overview of the various performance metrics across thesupply chain and have described sources using these performance metrics.Researchers have associated the supply chain performance with measures in thefollowing diverse ways:

. qualitative or quantitative (Beamon, 1999; Chan, 2003);

. cost and non-cost (Gunasekaran et al., 2001; De Toni and Tonchia, 2001);


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. quality, cost, delivery and flexibility (Schönsleben, 2004);

. cost, quality, resource utilization, flexibility, visibility, trust and innovativeness(Chan, 2003);

.

resources, outputs and flexibility (Beamon, 1999);. supply chain collaboration efficiency; coordination efficiency and configuration

(Hieber, 2002);. input, output and composite measures (Chan and Qi, 2003);. strategic, operational or tactical focus (Gunasekaran et al., 2001);. supply chain operations reference (SCOR) model (plan, source, make, deliver and

return or customer satisfaction); whether they measure cost, time, quality,flexibility and innovativeness; and, whether they were quantitative or qualitative(Shepherd and Gunter, 2006);

. modeling the metrics of lean, agile and leagile supply chains (Agarwal et al.,2006);

. key performance measures and metrics in supply chain (Gunasekaran and Kobu,2007);

. scorecard approach (Brewer and Speh, 2000, 2001; Bullinger et al., 2002);

. tangible/intangible (Park et al., 2005; Saad and Patel, 2006);

. sustainability/green (Clift, 2003; Hervani et al., 2005); and

. financial/non-financial (Beamon and Balcik, 2008; Gunasekaran et al., 2004;Gunasekaran et al., 2001).

However, there are a limited number of articles that deal with performance measures andmetrics in a supply chain environment (Gunasekaran and Kobu, 2007). According toCuthbertson and Piotrowicz (2008), the majority of supply chain measures are economic

and quantitative (cost, customer, responsiveness, and productivity) rather thanqualitative. From the analysis of Chow et al. (1994) practitioners have assigned lessbenefits and measures at strategic level compared to operations and individualprocesses. There are not many review articles on performance measures and metrics inlogistics and supply chain (Gunasekaran and Kobu, 2007). From the above highlightedpoints, authors can conclude that researchers have perceived supply chain performancefrom various perspectives. The researchers’ perspective is a unique view of what Supplychain management (SCM) is about. Researchers’ perspective can be described in terms of the perceived nature of the supply chain (Otto and Kotzab, 2003). According to theauthors’ perspective, supply chain performance can be divided into two categories:

(1) Supply chain measures and metrics.

(2) Enhancing the supply chain performance.

The detailed analysis of the above two categories will be discussed in section 2 and 3.Rapidly changing global economic environment, green concepts and socialresponsibility pressures from governments shows the significant need to raisecritical questions such as: Do organizations need different set of measures for bothresponsive and efficient supply chains? Do environmental measures fit for existingsupply chain performance models? Do safety-related measures impact on supply chainperformance? Are management practices having an impact on supply chain

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performance of organizations? What measures are needed for more sustainable supplychains? These questions motivate the authors to conduct a review on supply chainperformance measurement, which will help academicians and practitioners tounderstand the existing gaps in the literature.

The organization of the paper is as follows: section 2 describes the reviewmethodology, section 3 covers the literature review and research issues, section 4contains findings and conclusions, and section 5 mentions the agenda for futureresearch and ends with a few important suggestions to contemporary researchers.

2. Review methodologyKeywords searches are employed to identify articles published between 2000 and 2011in specific management databases such as ISI Web of Knowledge and Scopus. Initialkey word searches are performed using terms such as “supply chain measurement”,“supply chain performance”, “supply chain measures”, “supply chain metrics”. Thesesearches resulted in 220 articles in the ISI Web of knowledge and 103 articles in

Scopus. In total 323 articles were identified. Summary of the search results is shown inTable I and the review methodology shown in Figure 1. In the identified articles a fewpapers were found duplicated in these two databases and those papers were eliminatedand finally 270 articles resulted. Distribution of these articles with respect to journals isgiven in Table II.

An analysis by year and approach of published articles is presented in Figures 2and 3 respectively. The analysis shows notable growth in the number of articlespublished from 2008 (Figure 2). Authors have suggested one of the reasons for thisspectacular growth is economic crisis during the last quarter of 2008 and the firstquarter of 2009 (Bénassy-Quéré et al., 2009). Drastic changes in exports andfragmentation of supply chains during this period made researchers focus more onsupply chain performance issues. Researchers have used the survey approach morethan case study. Hence, there is low attention to the case study approach in supplychain area (Figure 3). The 270 articles were further scrutinized based on authors’perspective analysis on supply chain performance, which we have briefly introduced insection 1. This includes enhancing the supply chain performance, and supply chainmeasures and metrics. In enhancing the supply chain performance perspective, theauthors considered papers which focused on specific areas of the supply chain such as,collaboration and trust, (Papakiriakopoulos and Pramatari, 2010; Panayides and Lun,2009), integration (Fabbe-Costes and Jahre, 2008; Flynn et al., 2010), product variety(Thonemann and Bradley, 2002); partnership (Ryu et al., 2009), organizationalstructures (Kim, 2007), collaboration (Simatupang and Sridharan, 2005), informationtechnology (Wu et al., 2006), system perspective (Chan and Qi, 2003), environmental(Shaw et al., 2010), agile (Van Hoek et al., 2001) and risk (Srinivasan et al., 2011). While,the supply chain measure and metrics perspective papers (Gunasekaran et al. 2001;Otto and Kotzab, 2003; Shepherd and Gunter, 2006) focused on measures and metrics of

Database KeywordsNo. of articles

published

ISI web of knowledge Supply chain: performance, metrics, measurement, metrics 220Scopus Supply chain: performance, metrics, measurement, metrics 103

Table I.Summary of database

review (year 2000-2011)


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supply chain. The authors considered the articles focused on supply chain measuresand metrics. Further, in order to justify the analysis adopted for this extraction, we

offer the following reasons for selection criteria:

. General issues of supply chain measures.

. Supply chain measures for designing, implementing and monitoring of measures.

. Key Performance Indicators.

. Approaches to supply chain measures.

. Application of supply chain measures.

In summary, our argument is that papers, which extensively address the issue of supply chain performance measurement and provides detailed key insights on the

issue and satisfy any of the above criteria are potential candidates for inclusion in this

Figure 1.Research methodology

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SL no. Journal name Count

1 International Journal of Production Economics 312 International Journal of Production Research 26

3 Journal of Operations Management 194 Industrial Management & Data Systems 155 Management Science 106 European Journal of Operational Research 97 Production Planning Control 108 SCM: An International Journal 489 International Journal of Physical Distrubution and Logistics 19

10 International Journal of Productivity and Performance Measurement 811 International Journal of Operations & Production Management 2012 International Journal of Logistics Management 1213 Benchmarking: An International Journal 1214 Others 31

Total 270

Table II.Distribution of articleswith respect to journal

wise

Figure 2.Year wise representations

of articles

Figure 3.Approach wise

representations of articles


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paper. This has helped in extracting the most relevant 28 articles from the pool of 270articles for the scope and objectives of this paper. An analysis of the list of 270 articlesbased on researcher’s categorization of topics is given in Appendix (Table AI).

The detailed classification of the final extracted papers (28) with respect to author,

title, approach and focus are shown in Table III.

3. Literature reviewThe 28 scrutinized papers and are viewed on the basis of three phases of the PMSprocess as reported below:

(1) designing of measures;

(2) implementing of measures;

(3) monitoring of measures.

3.1 Designing of measures

In this phase, authors took in papers which were focused on development of frameworks, conceptual models, classification of measures and supported theories, andwhich focused on design of supply chain performance measures for improving overallsupply chain performance. In the literature, Kaplan and Norton’s (1992) original,publication on the balanced score card (BSC) has been the most cited performancemeasurement article for eight out of the last ten years and every year for the last seven(Neely, 2005). This indicates the significance of balanced measurement of businessprocesses. Lapide (2000) focused importance on balanced score card, processmeasurement and limiting of total metrics in the supply chain. Researchers haveacknowledged the importance of integrated metrics, because these metrics allowmanagement to assess the overall competitiveness of the supply chain and todetermine which internal improvement efforts produce the greatest impact on overall

competitiveness Lambert and Pohlen (2001). Hence, application of balanced score cardcan be extended to develop integrated frameworks with supply chain operationsreference model (SCOR) for analyzing supply chain performance. For example,Bullinger et al. (2002) discussed the integration of SCOR and balanced score cardmeasurement, and proposed a methodology integrating bottom-up and top-downmeasures as a hybrid balanced measurement approach; and Thakkar et al. (2009)proposed a SCOR-BSC framework for small and medium enterprises of supply chains.In supply chain management Gunasekaran et al. (2001) probably made the first attemptto classify the metrics into a balanced approach with respect to organization levels(strategic-tactical-operational) and SCOR process stages (plan-source-make-deliver).Further, Shepherd and Gunter (2006) classified metrics into cost, quality, time,flexibility and qualitative versus quantitative with respect to SCOR process stages.

There are several metrics in the literature and in business organizationsrecommended for use in measuring the performance of a supply chain management(Gunasekaran et al., 2004; Gunasekaran and Kobu, 2007; Folan and Browne, 2005,Fynes et al., 2005). A major challenge for many companies that are developing ameasurement process is limiting the number of measures (Lapide, 2000). Organizationsoften find there is a lack of practical guidelines on how to develop KPIs (Chae, 2009).Chae (2009) suggested guidelines for designing metrics and proposed key performancemetrics for the SCOR model. With this view Gunasekaran and Kobu (2007) have

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A p p r o a c h

F o c u s

S L n o .

A u t h o r

T i t l e

F / T

S

R

1

2

3

1 .

L a p i d e ( 2 0 0 0 )

T r u e m e a s u r e s o f s u p p l y c h a i n p e r f o r m a n c e

U

U

2 .

G u n a s e k a r a n

e t a l . ( 2 0 0 1 )

P e r f o r m a n c

e m e a s u r e s a n d m e t r i c s i n a s u p p l y c h

a i n

e n v i r o n m e n

t

U

U

3 .

L a m b e r t a n d

P o h l e n ( 2 0 0 1 )

S u p p l y c h a i n m e t r i c s

U

U

4 .

B u l l i n g e r e t a l . ( 2 0 0 2 )

A n a l y z i n g s u p p l y c h a i n p e r f o r m a n c e u s i n g a

b a l a n c e d m

e a s u r e m e n t m e t h o d

U

U

5 .

O t t o a n d K o t z a b ( 2 0 0 3 )

D o e s s u p p l y c h a i n m a n a g e m e n t r e a l l y p a y ? S i x

p e r s p e c t i v e s t o m e a s u r e t h e p e r f o r m a n c e o f

m a n a g i n g a

s u p p l y c h a i n

U

U

6 .


e t a l . ( 2 0 0 4 )

A f r a m e w o r k f o r s u p p l y c h a i n p e r f o r m a n c e

m e a s u r e m e n t

U

U

U

7 .

H e r v a n i e t a l .

( 2 0 0 5 )

P e r f o r m a n c

e m e a s u r e m e n t f o r g r e e n s u p p l y c h a i n

m a n a g e m e n t

U

U

8 .

S h e p h e r d a n d

G u n t e r ( 2 0 0 6 )

M e a s u r i n g

s u p p l y c h a i n p e r f o r m a n c e : c u r r e n t

r e s e a r c h a n

d f u t u r e d i r e c t i o n s

U

U

9 .

Y a o a n d L i u ( 2 0 0 6 )

A n i n t e g r a t e d a p p r o a c h f o r m e a s u r i n g s u p p l y c h

a i n

p e r f o r m a n c

e

U

U

1 0 .

A g a r w a l e t a l . ( 2 0 0 6 )

M o d e l i n g t h

e m e t r i c s o f l e a n , a g i l e a n d l e a g i l e s u p p l y

c h a i n : a n A

N P - b a s e d a p p r o a c h

U

U

1 1 .


a n d K o b u ( 2 0 0 7 )

P e r f o r m a n c

e m e a s u r e s a n d m e t r i c s i n l o g i s t i c s a n d

s u p p l y c h a i n m a n a g e m e n t : a r e v i e w o f r e c e n t

l i t e r a t u r e ( 1

9 9 5 - 2 0 0 4 ) f o r r e s e a r c h a n d a p p l i c a t i o n s

U

1 2 .

B h a g w a t a n d

S h a r m a ( 2 0 0 7 )

P e r f o r m a n c

e m e a s u r e m e n t o f s u p p l y c h a i n

m a n a g e m e n t u s i n g t h e a n a l y t i c a l h i e r a r c h y p r o c e s s

U

U

1 3

G u l l e d g e a n d

C h a v u s h o l u ( 2 0 0 8 )

A u t o m a t i n g t h e c o n s t r u c t i o n o f s u p p l y c h a i n k e y

p e r f o r m a n c

e i n d i c a t o r s

U

U

U

1 4 .

C u t h b e r t s o n a n d P i o t r o w i c z ( 2 0 0 8 )

S u p p l y c h a i n b e s t p r a c t i c e s – i d e n t i fi c a t i o n a n d

c a t e g o r i z a t i o n o f m e a s u r e s a n d b e n e fi t s

U

U

1 5 .

W o n g a n d W

o n g ( 2 0 0 8 )

A r e v i e w o n b e n c h m a r k i n g o f s u p p l y c h a i n

p e r f o r m a n c

e m e a s u r e s

U

U

( c o n t i n u e d )

Table III.Comprehensive summaryof articles with respect to

author, title, approachand focus


measures

527


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A p p r o a c h

F o c u s

S L n o .

A u t h o r

T i t l e

F / T

S

R

1

2

3

1 6 .

M a r t i n a n d P a t t e r s o n ( 2 0 0 9 )

O n m e a s u r i n g c o m p a n y p e r f o r m a n c e w i t h i n a

s u p p l y c h a i n

U

U

1 7 .

C h a e ( 2 0 0 9 )

D e v e l o p i n g

k e y p e r f o r m a n c e i n d i c a t o r s f o r s u p p l y

c h a i n : A n i n d u s t r y p e r s p e c t i v e

U

U

1 8 .

C h i a e t a l . ( 2 0 0 9 )

P e r f o r m a n c

e m e a s u r e m e n t i n s u p p l y c h a i n e n t i t i e s :

B a l a n c e d s c o r e c a r d p e r s p e c t i v e

U

U

1 9 .

C a i e t a l . ( 2 0 0

9 )

I m p r o v i n g s u p p l y c h a i n p e r f o r m a n c e m a n a g e m e n

t : a

s y s t e m a t i c

a p p r o a c h t o a n a l y z i n g i t e r a t i v e K P I

a c c o m p l i s h m e n t

U

U

2 0 .

T h a k k a r e t a l . ( 2 0 0 9 )

S u p p l y c h a i n p e r f o r m a n c e m e a s u r e m e n t f r a m e w o r k

f o r s m a l l a n d m e d i u m s c a l e e n t e r p r i s e s

U

U

2 1 .

B h a g w a t a n d

S h a r m a ( 2 0 0 9 )

A n a p p l i c a t i o n o f t h e i n t e g r a t e d A H P - P G P m o d e l

f o r

p e r f o r m a n c

e m e a s u r e m e n t o f s u p p l y c h a i n

m a n a g e m e n t

U

U

2 2 .

A k y u z a n d E r k a n ( 2 0 1 0 )

S u p p l y c h a i n p e r f o r m a n c e m e a s u r e m e n t : a l i t e r a t u r e

r e v i e w

U

U

2 3 .

S h a w e t a l . ( 2 0 1 0 )

D e v e l o p i n g

e n v i r o n m e n t a l s u p p l y c h a i n

p e r f o r m a n c

e m e a s u r e s

U

U

2 4 .

L i n a n d L i ( 2 0 1 0 )

A n i n t e g r a t e d f r a m e w o r k f o r s u p p l y c h a i n

p e r f o r m a n c

e m e a s u r e m e n t u s i n g s i x - s i g m a m e t r i c s

U

U

U

2 5 .

Z h a n g e t a l . ( 2 0 1 1 )

A f e w m e a s u r e s f o r e n s u r i n g s u p p l y c h a i n q u a l i t y

U

U

2 6 a

F a b b e - C o s t e s

e t a l . ( 2 0 1 1 )

F u t u r e s u s t a i n a b l e s u p p l y c h a i n s : w h a t s h o u l d

o r g a n i z a t i o n s s c a n ?

U

U

2 7 .

O l u g u e t a l . ( 2 0 1 1 )

D e v e l o p m e n t o f k e y p e r f o r m a n c e m e a s u r e s f o r t h e

a u t o m o b i l e

g r e e n s u p p l y c h a i n

U

U

U

2 8 .

M o n d r a g o n e t a l . ( 2 0 1 1 )

M e a s u r e s f o r a u d i t i n g p e r f o r m a n c e a n d i n t e g r a t i o n

i n c l o s e d - l o o p s u p p l y c h a i n s

U

U

N o t e s : a

T h i s p a p e r d o e

s n o t d i s c u s s a n y m e a s u r e s h o w e v e r

i n c l u s i o n i s j u s t i fi e d f o r i t s p o t e n t i a l t o s u p p o r t s u s t a i n a b i l i t y a s p e c t i n s u p p l y c h a i n

p e r f o r m a n c e m e a s u r e m e n t ; F / T : F r a m e w o r k / T h e o r y S : S u r v e y R : R e v i e w ; 1 . D e s i g n i n g o f m e a s u r e s ; 2 . I m p l e m e n t i n g o f m e a s u r e s ; 3 . I m p r o v e m e n t /

M o n i t o r i n g o f m e a s u r e s

Table III.

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analyzed and identified 27 key performance indicators from literature on the basis of the following criteria:

. balanced score card perspective;

.

components of measures;. location of measures in supply chain links;. decision levels;. nature of measures;. measurement base; and. traditional vs modern measures.

However, Cuthbertson and Piotrowicz (2008) have found from their studies that currentperformance approaches do not generally include social and environmental aspects andare concentrated on economic aspects, not on sustainable aspects. Hervani et al.(2005)listed environmental measures and provided an integrated framework of supply chain

management, environmental management, and performance management. However,there is no ideal existing performance framework or environmental supply chainperformance measure (ESCP). Hence, an integrated framework could facilitate theenvironmental supply chain benchmarking process Shaw et al. (2010).

The perspectives of measuring supply chain management have been extended fromBSC and SCOR to value and cost accounting. Lambert and Pohlen (2001) provided aframe work which helps to develop the performance metrics in supply chain,identifying those that translate into shareholder’s value. In their view, the overallperformance is determined by the increase in market capitalization for each firm in thesupply chain. From a cost accounting point of view Yao and Liu (2006) developed anintegrated framework of economic value added (EVA), balanced scorecard (BSC) andactivity-based costing (ABC) to measure supply chain performance. Further to these

perspectives, Otto and Kotzab (2003) proposed six perspectives of measuring supplychain performance such as: system dynamics, operations research, logistics,marketing, organization and strategy areas. These follow a particular set of goals,which lead to particular set of metrics. Finally, Akyuz and Erkan (2010) conducted acritical review in the domains of supply chain, information technology (IT), businessprocess management and performance management and brings forth the requirementsof performance measurement metrics in present era, which will help while designingthe metrics to encounter the issues related supply chain measures.

3.2 Implementing measuresIn this phase, authors included papers which focused on empirical testing of frameworks, survey and case study examples to understand the implementation issuesassociated to supply chain performance measures. More research is needed to developsupply chain metrics and to overcome the implementation barriers Lambert andPohlen (2001). Chia et al. (2009) tested empirically the BSC framework in the supplychain by considering the 15 generic performance measures. Gunasekaran et al. (2004),in their empirical study of a framework focused on classification of various supplychain measures based on supply chain activities with respect to levels (strategic,operational and tactical) of organization to address the authority and responsibility of management at appropriate level.


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Prioritizing the measures and metrics in supply chain management is the key to thesuccess Gunasekeran and Kobu (2007). In the era of globalization it is critical to selectthe right choice of performance metrics and measures. In this view, Analyticalhierarchy process (AHP) can be the best tool for decision makers that best suits their

understanding, prioritizing and choosing the best measure and metric for day-to-daybusiness operations. Bhagwat and Sharma (2007) developed a supply chain decisionmaking problem hierarchy (Goal as an overall supply chain performance; criteria as alevels of organizations; alternatives as a BSC perspectives) by using AHP and obtaineddata for the model with the help of a survey. Further to this, Bhagwat and Sharma(2009) developed a combination of analytical hierarchy process (AHP) and pre-emptivegoal programming (PGP) model by considering qualitative and quantitative measuresfor optimizing supply chain performance. However, some state that AHP helps tochoose most suitable alternatives but it cannot capture interdependencies (Meade et al.,1997; Meade and Sarkis, 1999). Hence, Agarwal et al. (2006) proposed a framework byusing three types of metrics such as, lean, agile and leagile with the help of analyticnetwork process (ANP), to support managers in making strategic decisions in supply

chains.Application of management concepts such as six sigma, and E-business for

selecting the supply chain metrics were explained by Lin and Li (2010) and Gulledgeand Chavusholu (2008). Martin and Patterson (2009) identified cycle time and inventoryas the key performance measures to analyze the company performance in a supplychain. However, continuous improvement of supply chain performance needs frequentmonitoring of these key performance measures (KPIs). Cai et al. (2009) explained howto accomplish this for the iterative KPIs in supply chains with a cost transformationmatrix (PCTM).

With the advent of environmental concerns organizations have been redefiningtheir supply chain measurement process by selecting green measures. For example,Olugu et al. (2011) explained green supply chain KPIs in the automobile industry for

both forward and backward chains. Mondragon et al. (2011) discussed the measures forclosed loop supply chains of both forward and backward directions for shorter lifecycle products.

3.3 Monitoring of measuresIn this section, the authors considered articles that contributed particularlypragmatic guidelines and benchmarking issues for monitoring of supply chainperformance as, it reveals the gap between planning and execution (implementing)and helps companies to identify potential problems and areas for improvement(Chae, 2009). Fabbe-Costes et al. (2011) discussed sustainability of supply chainswith the help of a scanning framework; it includes six levels such as, societal,network, chain, firm, function, supply chain managers and people level. To ensuresupply chain quality and continuous improvement, Zhang et al. (2011) found thatsupply chain co-ordination, technology application, risk management, and reliabilityassurance are important performance measures. The success of the supply chaindepends on how we assess and monitor these measures. Benchmarking is one of thebest ways to assess these measures (Shah and Singh, 2000). The generalbenchmarking process differs from supply chain benchmarking since performancemeasures differ field to field. Insights of supply chain benchmarking such as,problems, and tools to use benchmarking were discussed by Wong and Wong (2008)

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and, also they explained the application of data envelopment analysis (DEA) insupply chain benchmarking.

Selected noteworthy contributions delivering new approaches to measurement,including novel methodologies in the area of supply chain performance measurement,

are reported in Table IV.The overall evaluation of the papers under these phases has helped the authors to

highlight the key research issues. These include a total 15 (RI1-RI15) research Issues(RI) and a total 16 (RQ1-RQ13) research questions (RQ). These research issues andquestions are listed in Table V.

4. Findings and conclusionResearchers’ focus on the domain of supply chain measures and metrics, improvedremarkably from the year 2000. Initially, attempts were applied to development of integrated frameworks (Bullinger et al.(2002), with balanced scorecard, classifyingmeasures (Gunasekaran et al., 2001; Shepherd and Gunter, 2006); over time attentionmoved to other areas namely, application of measures (Lin and Li, 2010),identification of KPIs (Gunasekaran and Kobu (2007), Small and Medium scaleEnterprises (Thakkar et al., 2009) and measures for green supply chains (Hervaniet al.(2005). Unlike in pure management, this is not a paradigm shift from one era toother; as it altogether depends on the researcher’s view towards supply chainmeasures and application of their knowledge in this domain. Based on the review of selected research papers, and taking into account the previous considerations of Shepherd and Gunter (2006) Gunasekaran and Kobu (2007), and Akyuz and Erkan(2010), the authors have provided a few insights for contemporary researchers in thedomain of supply chain measures and metrics, which are demanded for growth andsustainability of organizations, in the present contemporary competitiveenvironment. These include:

(1) Extent to which organizations should identify the key performance indicators(KPIs) in the following views:. Supply chain length (includes: parent organizations, suppliers, distributors,

logistic service providers).

Model/framework/methodology Author Year

Framework based on levels Gunasekaran et al. 2001Using Six sigma metric Dasguptha.T 2003Framework based on SCOR model Gunasekaran et al. 2004SCOR with AHP model Haun et al. 2004Taxonomy of measures Shepherd and Gunter 2006

KPIs identification Gunasekaran and Kobu 2007Supply chain performance model using AHP Bhagawat and Sharma 2007Supply chain performance model using BSC Bhagawat and Sharma 2007i-SCOR Methodology Gulledge and Chavusholu 2008SCOR-BSC framework for SMEs Thakkar et al. 2009AHP with PGP model Bhagawat and Sharma 2009Integrated framework of SCM-ESCM Shaw et al. 2010Integrated Six sigma and capability maturity model Lin and Li 2010Scanning framework Fabbe-Costes et al. 2011

Table IV.Summarization of works

in supply chain measuresand metrics from

(2000-2011)


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P h a s e s

R e p r e s e n t a t i v e a r t i c l e s

R e s e a r c h i s s u e s

R e s e a r c h q u e s t i o n

D e s i g n i n g o f

m e a s u r e s

A k

y u z a n d E r k a n ( 2 0 1 0 ) ; G u n a s e k a r a n

e t a l . ( 2 0 0 1 ) ; S h a w e t a l . ( 2 0 1 0 ) ;

M o

n d r a g o n e t a l . ( 2 0 1 1 ) , G u n a s e k a r a n

e t a l . ( 2 0 0 4 ) ; C h i a e t a l . ( 2 0 0 9 ) ;

G u

n a s e k a r a n a n d K o b u ( 2 0 0 7 ) ;

C u t h b e r t s o n a n d P i o t r o w i c z ( 2 0 0 8 ) ;

B h

a g w a t a n d S h a r m a ( 2 0 0 7 ) ; S h e p h e r d

a n d G u n t e r ( 2 0 0 6 )

R I 1 : L a c k o f d e v e l o p m e n t o f m e a s u r e s

f o r c o s t e f f e c t i v e r e s p o n s i v e s u p p l y

c h a i n s

R I 2 : L a c k o f d e v e l o p m e n t o f k e y

p e r f o r m a n c e m e a s u r e s ( K P M ) i n

s u p p l i e r d e v e l o p m e n t o r p a r t n e r s h i p

f o r m a t i o n

R I 3 : A b s e n c e o f m e a s u r e s f o r l e a n

i n t e r n a t i o n a l s u p p l y c h a i n s

R I 4 : P o o r i n t e g r a t i o n o f e n v i r o n m

e n t a l

m e a s u r e s w i t h e x i s t i n g s u p p l y c h a i n

p e r f o r m a n c e m o d e l s

R I 5 : L a c k o f c o m m o n M e a s u r e s

R I 6 : L a c k o f d e v e l o p m e n t o f s u p p

l y

c h a i n p e r f o r m a n c e m e a s u r e s f o r

d i f f e r e n t p r o d u c t l i f e c y c l e s

R I 7 : L a c k o f c r o s s i n d u s t r y s t u d i e

s i n

s u p p l y c h a i n p e r f o r m a n c e a r e a

R I 8 : L a c k o f d e v e l o p i n g t h e m e a s u r e s f o r

s u s t a i n a b l e s u p p l y c h a i n s

R Q 1 : A r e e x i s t i n g m e a s u r e s f o r a n y

s u p p l y c h a i n p e r f o r m a n c e m e a s u r e m e n t

s y s t e m a m p l e t o a u d i t t h e r e s p o n s i v e

s u p p l y c h a i n s ?

R Q 2 : D o o r g a n i z a t i o n s h a v e d i f f e r e n t

s e t s o f m e a s u r e s f o r b o t h r e s p o n s i v e a n d

e f fi c i e n t s u p p l y c h a i n s ?

R Q 3 : A r e l e a n s u p p l y c h a i n p r a c t i c e s

h a v i n g i m p a c t o n s u p p l y c h a i n

p e r f o r m a n c e o f o r g a n i z a t i o n s ?

R Q 4 : D o k e y p e r f o r m a n c e m e a s u r e s

a d d r e s s t h e p e r f o r m a n c e i s s u e s w i t h

r e g a r d t o p a r t n e r s h i p f o r m a t i o n i n b o t h

u p a n d d o w n s t r e a m s o f s u

p p l y c h a i n s ?

R Q 5 : D o s p e c i fi c i n d u s t r y s u p p l y c h a i n

m e a s u r e s a d d r e s s t h e s u p p l y c h a i n

p e r f o r m a n c e o f a n y i n d u s t r

y ?

R Q 6 : D o e n v i r o n m e n t a l m e a s u r e s fi t f o r

e x i s t i n g s u p p l y c h a i n p e r f o

r m a n c e

m o d e l s ?

R Q 7 : A r e e x i s t e d p e r f o r m a n c e m e a s u r e s

a d d r e s s i n g t h e s h o r t a n d l o

n g p r o d u c t

l i f e c y c l e s ’ s u p p l y c h a i n s

R Q 8 : A r e s u s t a i n a b l e s u p p l y c h a i n s

m o r e n e e d e d f o r d i f f e r e n t s e t s o f

m e a s u r e s t h a n t h e e x i s t i n g

m e a s u r e s ?

( c o n t i n u e d )

Table V.Research issues andquestions

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P h a s e s

R e p r e s e n t a t i v e a r t i c l e s

R e s e a r c h i s s u e s

R e s e a r c h q u e s t i o n

I m p l e m e n t i n g o f

m e a s u r e s

A k

y u z a n d E r k a n ( 2 0 1 0 ) , O t t o a n d

K o

t z a b ( 2 0 0 3 ) ; S h e p h e r d a n d G u n t e r

( 2 0

0 6 ) ; O l u g u e t a l . ( 2 0 1 1 ) ; G u n a s e k a r a n

a n d K o b u ( 2 0 0 7 ) ;

R I 9 : L a c k o f v a l i d a t i n g t h e m e t r i c

s i n

d i f f e r e n t a p p r o a c h e s ( s y s t e m d y n a m i c s ,

o p e r a t i o n s r e s e a r c h , l o g i s t i c s ,

m a r k e t i n g , o r g a n i z a t i o n a n d s t r a t e g y )

f o r d i f f e r e n t s u p p l y c h a i n s c o n t e x

t s

R I 1 0 : L a c k o f e m p i r i c a l s u p p o r t f o r

v a l i d a t i o n o f s u p p l y c h a i n m e a s u r e s

R 1 1 : L a c k o f a d d r e s s i n g f a c t o r s

e f f e c t i n g s u c c e s s o r f a i l u r e o f

p e r f o r m a n c e m e a s u r e m e n t s y s t e m

R I 2 : L e s s f o c u s o n e m p i r i c a l s u p p

o r t o f

e n v i r o n m e n t a l s u p p l y c h a i n m e a s u r e s

R Q 9 : A r e o r g a n i z a t i o n s a n a l y z i n g

s u p p l y c h a i n p e r f o r m a n c e o n c o n t e x t

b a s e ?

R Q 1 0 : D o o r g a n i z a t i o n s a d o p t t h e

d i s t i n c t m e a s u r e s f o r v a r i o u s

a p p r o a c h e s ?

R Q 1 1 : D o o r g a n i z a t i o n s h a

v e

c o g n i z a n c e o f t h e e n v i r o n m

e n t a l

m e a s u r e s ?

R Q 1 2 : A r e o r g a n i z a t i o n s a n a l y z i n g t h e

c a u s e s a n d e f f e c t s o n s u p p l y c h a i n

m e a s u r e s i n c h a n g i n g e n v i r o n m e n t ?

R Q 1 3 : D o o r g a n i z a t i o n s c o m f y w i t h t h e

r e s u l t s o f g r e e n s u p p l y c h a i n m e a s u r e s ?

M o n i t o r i n g o f

m e a s u r e s

S h e p h e r d a n d G u n t e r ( 2 0 0 6 ) ; W o n g a n d

W o n g ( 2 0 0 8 ) ; A k y u z a n d E r k a n

( 2 0

1 0 ) ; Z h a n g a e t a l . ( 2 0 1 1 )

R I 1 3 : L a c k o f a d d r e s s i n g t h e o n - g

o i n g

m a i n t e n a n c e o f s u p p l y c h a i n

p e r f o r m a n c e m e a s u r e m e n t s y s t e m

s

R I 1 4 : L e s s f o c u s o n s u p p l y c h a i n

b e n c h m a r k i n g

R I 1 5 : L a c k o f a d d r e s s i n g m e a s u r e s f o r

p r o g r e s s a n d i m p r o v e m e n t o f

i n t e g r a t i o n

R Q 1 4 : A r e e x i s t e d s u p p l y c h a i n

p e r f o r m a n c e m e a s u r e m e n t f r a m e w o r k s

a d d r e s s i n g t h e b e n c h m a r k i n g i s s u e s o f


R Q 1 5 : A r e o r g a n i z a t i o n s h a v i n g

s u s t a i n a b l e b e n c h m a r k i n g t o o l s f o r t h e i r

s u p p l y c h a i n s

R Q 1 6 : D o o r g a n i z a t i o n s h a

v e r o b u s t

m e a s u r e s f o r fl e x i b l e i n t e g r

a t i o n o f


Table V.


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. Supply chain width (includes: Job type contractors/all contract worksproviders).

. Supply chain depth (includes: sub suppliers, sub retailers).

(2) Ability of metrics to handle supply chains for long and short product life cycles.(3) Metrics should be classified based on push, pull and push-pull supply chains.

(4) Extent to which organizations understand the external forces and how they areacting on their performance measurement system.

(5) Metrics and performance system/model should be mathematically valid.

(6) Cross functional fit of metrics across industries.

(7) Measures for addressing the continuous improvement of organizationalperformance systems.

(8) Tailoring the measures for complex supply chain networks in present networkera.

(9) Ability of the organization to understand and respond to the rapidly changingvalue addition curve.

(10) Ability of KPIs to handle assorted supply chain collaborations andpartnerships.

(11) Competitive environment demands empirical measures and case studyapproaches for measuring the supply chain.

(12) Measures should be rigorously compliance.

(13) Concept of “sustainability” should understand in the context of supply chains.

(14) Extent to which organizations understand the impact of management practiceson supply chain performance.

(15) Identifying the effects of strategic, tactical and operational measures on overallprofitability of supply chain.

(16) Extent to which organizations classify the metrics based on long and short termstrategies of supply chains.

Over all, these insights enable organizations to make their supply chain performancemeasurement systems more robust and flexible. Changes in global economic, socialand environmental conditions are increasing the occurrence of fragmented supplychain networks. This induces organizations to focus on ongoing maintenance of supplychain performance measurement systems.

This paper has analyzed the development of research on supply chain measures andmetrics over recent years by reviewing the articles published in the relevantpeer-reviewed international journals. Our prime goal has been to analyze theresearchers’ views towards supply chain performance over the years. In order tosupport a detailed analysis of selected key articles, the authors have adopted adeductive approach to decide about the inclusion or exclusion of the papers.

From the review it is very much important that the organization’s potential andcompetence in supply chain management and their ability to go with the selected,prescribed measures are closely related. An organization with less of supply chaincompetence, adopting too advanced supply chain performance measures wouldsimply be taxing their resources (technology and people). This approach may show

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some good research for the time being but may hamper the long term growthperspective of the organizations. On the other hand organizations adopting verypreliminary supply chain measures (cost, quality, time, flexibility) despite their duecompetence and potential clarity demonstrate their unwillingness to co operate in

the supply chain. This behavior has to be re advised or corrected usingreward/punishment measures.

5. Agenda for future researchToday, the competition is neither in between organizations nor supply chains.Organizations are conceiving how unique we are in the market. This demands arealistic assessment of st

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