An IntegrAn integrated BSC-AHP approach for supply chain management evaluationated BSC-AHP Approach for Supply Chain Management Evaluation

7/23/2019 An IntegrAn integrated BSC-AHP approach for supply chain management evaluationated BSC-AHP Approach for Su

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An integrated BSC-AHP approach for

supply chain management evaluation

Milind Kumar Sharma and Rajat Bhagwat

Summary

Purpose The purpose of this paper is to develop an integrated balanced scorecard (BSC) analytical

hierarchy process (AHP) approach for supply chain management (SCM) evaluation. It aims to measure

SCM performance from the following four perspectives: finance, customer, internal business process,

and learning and growth.

Design/methodology/approach The BSC is developed in the paper based on an extensive review of

literature on SCM performance measures, supported by AHP analysis.

Findings The paper develops a BSC for SCM evaluation and proposes a method to prioritize the

different performance levels in any organization using AHP methodology. It also suggests from the view

of different decision levels and overall performance measurement that is the best BSC perspective.

Practical implications The integrated BSC-AHP methodology developed in this paper provides

useful guidance for practical managers in evaluation and measuring of SCM in a balanced way.

Originality/value This paper proposes a balanced performance evaluation system for SCM. While

suggesting BSC, different SCM performance metrics have been distributed into four perspectives.

Different performance levels are highlighted and preferred BSC perspectives are suggested.

KeywordsBalanced scorecard, Supply chain management, Analytical hierarchy process,Performance measures

Paper typeResearch paper

1. Introduction

In recent years, a number of firms have realized the potential of supply chain management

(SCM) in day-to-day operations management. However, they often lack the insight for the

development of effective performance measures and metrics needed to achieve a fully

integrated SCM due to lack of a balanced approach and lack of clear distinction between

metrics at strategic, tactical, and operational levels (Gunasekaran et al., 2001; Hudson et al.,

2001). Therefore, it is clear that for effective SCM, measurement goals must consider the

overall scenario and the metrics to be used. These should represent a balanced approach

and should be classified at strategic, tactical, and operational levels, and include financial

and non-financial measures. Taking into account the above factors, a balanced SCM

scorecard has been developed in this paper to discuss the various measures and metrics of

SCM. Analytical hierarchy process (AHP) methodology is then integrated with balancedscorecard (BSC) for SCM evaluation. This helps supply chains to prioritize different

performance levels and identify preferred BSC perspectives.

1.1. The BSC

The need for performance measurement systems at different levels of decision making,

either in the industry or service contexts, is undoubtedly not something new (Bititiciet al.,

2005). Kaplan and Norton (1992, 1996) have proposed the BSC, as a means to evaluate

corporate performance from four different perspectives: the financial, the internal business

DOI 10.1108/13683040710820755 VOL. 11 NO. 3 2007, pp. 57-68, Q Emerald Group Publishing Limited, ISSN 1368-3047 jMEASURING BUSINESS EXCELLENCE j PAGE 57

Milind Kumar Sharma is

Assistant Professor and

Rajat Bhagwat is Associate

Professor, both at the

Faculty of Engineering and

Architecture, Department of

Production and Industrial

Engineering, MBM

Engineering College, JNV

University, Jodhpur, India.


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process, the customer, and the learning and growth. Their BSC is designed to complement

financial measures of past performance with their measures of the drivers of future

performance. The name of their concept reflects an intent to keep score of a set of items

that maintain a balance between short-term and long-term objectives, between financial

and non financial measures, between lagging and leading indicators, and between internal

and external performance perspectives. The early image of the BSC serving the CEO like a

control panel serves an aircraft pilot seems to have expanded to include mechanisms to alter

the course of action as well. Now, the BSC seems to serve as a control panel, pedals and

steering wheel (Malmi, 2001). Table I outlines the four perspectives included in a BSC.

Many companies are adopting the BSC as the foundation for their strategic management

system. Some managers have used it as they align their businesses to new strategies,

moving away from cost reduction and towards growth opportunities based on more

customized, value-adding products and services (Martinsons et al., 1999).

The BSC framework for supply chain management presented here in this article is

structurally similar to the BSC framework proposed by Kaplan and Norton.

The outline of the paper is as follows: Section 2 discusses performance evaluation

framework for SCM. Section 3 throws light on BSC evaluation of SCM. Section 4 and section

5 deal with AHP and AHP in SCM evaluation respectively. Section 6 presents result and

discussion. Finally, the conclusions and implications are presented in section 7.

2. Performance evaluation framework for SCM

Gunasekaran et al. (2001, 2004) claim that there is a greater need to study the measures and

metrics in the context of SCM for two reasons:

1. lack of a balanced approach; and

2. lack of clear distinction between metrics at strategic, tactical, and operational levels.

A set of performance measures and metrics in supply chain is discussed in the literature:

B Metrics of planned order procedures. These are used to measure the performance of the

order-related activities. Some metrics are order entry method, order lead-time, and order

path.

B Supply chain partnership and related metrics. These are used to assess the level of

coordination among supply chain partners. Some evaluation criteria are the level and

degree of information sharing, buyer-vendor cost initiatives, extent of mutual cooperationleading to improved quality, and the extent of mutual assistance in problem-solving

efforts.

B Production level measures and metrics. This category consists of range of product and

services, capacity utilization, and effectiveness of scheduling techniques.

B Delivery link measures. These are designed to evaluate the performance of delivery and

distribution cost.

Table I The four perspectives in a balanced scorecard

Customer perspective (value-adding view) Mission: to achieve our vision by delivering value

to our customer

Financial perspective (shareholders view) Mission: to succeed financially, by deliveringvalue to our shareholders

Internal perspective (process-based view) Mission: to promote efficiency and effectiveness

in our business processesLearning and growth perspective (future view) Mission: to achieve our vision, by sustaining

innovation and change capabilities, through

continuous improvement and preparation for

future challenges

Source: Kaplan and Norton (1992)

PAGE 58 jMEASURING BUSINESS EXCELLENCE jVOL. 11 NO. 3 2007


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B Customer service and satisfaction measures. The measurement is aimed to integrate the

customer specification in design, set the dimensions of quality and as the feedback for

the control process. They contain product/service flexibility, customer query time, and

post-transaction service.

B Finance and logistics cost metrics: They are used to assess the financial performance of

supply chain, such as assets cost, return on investment, and total inventory cost.

Gunasekaran et al. (2001, 2004) identified and discussed the different performance

measures and metrics of the SCM with help of a framework that gives cohesive picture to

address what needs to be measured, and how it can be dealt with. The frameworkdeveloped is shown in Table II.

Table II A framework of metrics for the performance evaluation SCM

Level Performance metrics Financial Non-financial

Strategic Total supply chain cycle time UTotal cash flow time UCustomer query time U ULevel of customer perceived value of product UNet profit vs. productivity ratio URate of return on investment U

Range of products and services U

Variations against budget UOrder lead time UFlexibility of service systems to meet particular

customer needs UBuyer-supplier partnership level U USupplier lead time against industry norms ULevel of suppliers defect free deliveries UDelivery lead time UDelivery performance U U

Tactical Accuracy of forecasting techniques UProduct development cycle time UOrder entry methods UEffectiveness of delivery invoice methods UPurchase order cycle time UPlanned process cycle time U

Effectiveness of master production schedule USupplier assistance in solving technical

problems USupplier ability to respond to quality problems USupplier cost saving initiatives USuppliers booking in procedures UDelivery reliability UResponsiveness to urgent deliveries UEffectiveness of distribution planning schedule U

Operational Cost per operation hour UInformation carrying cost U UCapacity utilization UTotal inventory cost as: U

Incoming stock levelWork-in-progressScrap value

Finished goods in transitSupplier rejection rate U UQuality of delivery documentation UEfficiency of purchase order cycle time UFrequency of delivery UDriver reliability for performance UQuality of delivered goods UAchievement of defect free deliveries U

Source: Gunasekaranet al. (2001)

VOL. 11 NO. 3 2007 jMEASURING BUSINESS EXCELLENCEj PAGE 59


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The metrics discussed in this framework are classified into strategic, tactical and operational

levels of management. The metrics are also distinguished as financial and non-financial so

that a suitable costing method based on activity analysis can be applied. A balanced

scorecard approach is discussed to evaluate these measures and metrics for SCM in the

section that follows.

3. BSC for SCM evaluation

The BSC for SCM framework presented here is developed by Bhagwat and Sharma (2007)

and structurally similar to the BSC framework at the corporate management level asproposed by Kaplan and Norton. Gunasekaran et al.(2001) identified supply chain metrics

and proposed a framework for SCM performance evaluation. Bhagwat and Sharma (2007)

applied BSC to these metrics with the intent to evaluate SCM performance comprehensively.

Four perspectives of the BSC are applied to these discussed metrics or in other words the

different metrics are fitted into four different perspectives of BSC as shown below:

1. Performance metrics for the financial perspective:

B customer query time;

B net profit vs productivity ratio;

B rate of return on investment;

B variations against budget;

B buyer-supplier partnership level;

B delivery performance;

B supplier cost saving initiatives;

B delivery reliability;

B cost per operation hour;

B information carrying cost; and

B supplier rejection rate.

2. Performance metrics for the customer perspective:

B customer query time;

B level of customer perceived value of product;

B range of products and services;

B order lead time;

B flexibility of service systems to meet particular customer needs;


B delivery lead time;

B delivery performance;

B effectiveness of delivery invoice methods;

B delivery reliability;

B responsiveness to urgent deliveries;B effectiveness of distribution planning schedule;

B information carrying cost;

B quality of delivery documentation;

B driver reliability for performance;

B quality of delivered goods; and

B achievement of defect free deliveries.



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3. Performance metrics for the internal business perspective:

B total supply chain cycle time;

B total cash flow time;

B flexibility of service systems to meet particular customer needs;

B supplier lead time against industry norms;

B level of suppliers defect free deliveries;

B accuracy of forecasting techniques;

B product development cycle time;

B purchase order cycle time;

B planned process cycle time;

B effectiveness of master production schedule;

B capacity utilization;

B total inventory cost as: incoming stock level, work-in-progress, scrap value and

finished goods in transit;

B supplier rejection rate;

B efficiency of purchase order cycle time; and

B frequency of delivery.

4. Performance metrics for the innovation and learning perspective:

B supplier assistance in solving technical problems;

B supplier ability to respond to quality problems;

B supplier cost saving initiatives;

B suppliers booking in procedures;

B capacity utilization;

B order entry methods;

B accuracy of forecasting techniques;

B

product development cycle time;B flexibility of service systems to meet particular customer needs;


B range of products and services; and

B level of customer perceived value of product.

Each of the four perspectives translatedinto corresponding metrics and measures that reflect

strategic goals and objectives. It is recommended that the perspectives should be reviewed

periodically and updated as necessary. The measures included in the given BSC should be

tracked and traced over time, and integrated explicitly into the strategic SCM process.

3.1. Measuring and evaluating financial metrics

Financial performance measures indicate whether the companys strategy, implementation

and execution are effectively contributing to the bottom line improvement of a firm. Financial

goals include achieving profitability, maintaining liquidity and solvency both short term as

well as long term, growth in sales turnover and maximizing wealth of shareholders. Financial

performance indicators are shown in the list above. In simplicity, financial goals are to

survive, succeed and prosper. Survival is measured by cash flow, success by growth in

sales and operating income and prosperity by increased market share and return on equity

and capital employed.



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3.2. Measuring and evaluating customer perspective

How do customers see the business: The BSC demands that the management must

translate their general mission statement on customer service into specific measures that

reflect the factors that really matter to the customers. Customers generally, concern to

lead-time, quality of products and services, companys performance service and the cost

effectiveness. But on long term basis and more importantly in the era of globalization any

firms competitiveness lies on different customer-related factors are shown in the

performance metrics for the customer perspective section in the above list.

3.3. Measuring and evaluating internal business perspective

What must business excel at: the internal measures for the BSC stems from the business

process that have the greatest impact on customers satisfaction factors that affect cycle

time, quality, skill of the employees, and of course, productivity. Firms should decide what

processes and competencies they must excel at and specify measures for each of them.

Performance metrics for the internal business perspective are shown in the list above.

3.4. Measuring and evaluating innovation and learning perspective

Can we continue to improve and create value: A companys ability to innovate, improve and

learn leads directly to companys value. Innovation and continuous learning process can

bring about efficiency in the operating domain of the business. Moreover, it ensures cost

reduction and product differentiation to meet the varied requirements of the customers. As a

result, it strengthens the financial ability through earning higher profitability and greaterdegree of appropriation of profit and retaining larger share of earnings to finance the

forthcoming expansion of future projects of the company under consideration. Performance

metrics for the innovation and learning perspective in a BSC includes measures as shown in

the list above.

Now the challenge before firms is to identify the most preferred BSC perspective so as to

identify the leading or lagging business area to measure business performance on

day-to-day basis. For this, in the next section AHP is integrated with the BSC for SCM

evaluation that not only prioritizes different performance levels in the organization, but also

suggests the best BSC perspective as alternative.

4. The AHP

The AHP is a multi-criteria decision-making tool developed by Saaty (1980). The AHP is asystematic procedure for representing the elements of any problem, hierarchically. A

hierarchy is structured from the top (objectives from a managerial standpoint), through

intermediate levels (criteria/sub-criteria on which subsequent levels depend) to the lowest

level (which is usually a list of alternatives). It organizes the basic rationality by breaking

down a problem into its smaller and smaller constituent parts and then guides decision

makers through a series of pair-wise comparison judgments (which are documented and

can be re-examined) to express the relative strength or intensity of impact of the elements in

the hierarchy. These judgments are then translated into numbers. AHP uses pair-wise

comparison of the same hierarchy elements in each level (criteria or alternatives) using a

scale indicating the importance of one element over another with respect to a higher-level

element. The importance of scale between elements is shown in Table III.

The scaling process yields a relative priority or weight of elements with respect to criterion orelement of the highest level. The comparisons are performed for all the elements in a level

with respect to all the elements in the level above. The final and global weights of the

elements at the lowest level of the hierarchy are found by adding all the contributions of the

elements in a level with respect to all elements in a higher level.

The AHP includes procedures and principles used to synthesize the many judgments to

derive priorities among criteria and subsequently for alternative solutions. It is useful to note

that the numbers thus obtained are ratio scale estimates and correspond to so-called hard

numbers (Saaty, 1980). Once the pair-wise comparison of alternatives or sub-criteria is



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made with respect to an element in a higher criterion (formed as a matrix), the largest

eigenvalue (lmax) should be approximately equal to the number of elements in the

comparison matrix (n). The deviation of lmax from n is a measure of the consistency ofjudgment of the decision maker. The consistency index (CI) is found using:

CI lmax 2 n=n2 1:

The consistency ratio (CR) is found by:

CR CI=RI:

RI is a random index of the same order matrix shown in Table IV.

Generally, the value of the consistency ratio should be around 10 percent or less to be

acceptable. In some cases 20 percent may be tolerated but never more (Saaty, 1980).

The AHP method has the following advantages (Abdul-Hamid, 1999).

B A subjective decision process can be formalized owing to the hierarchy structure. This

leads to accurate decisions.

B Insures consistency of the decision judgment.

B Clearer understanding of the problem by dividing it into sub-problems.

B The comparison may be made by teams or an iterative process until an agreement is

reached by the team members.

B Sensitivity analysis may be performed by the results using computers before final

judgment is rendered.

The tedious calculations of the AHP process are no longer a problem using computers and

specialized software such as Expert Choicee software. AHP has been used in a wide range

of applications such as plant layout (Abdul-Hamid, 1999; Dweiri and Meirer, 1996), new

product screening (Calantone, 1999), part-machining grouping (Gungor and Arikan, 2000),

Table III Scale of relative importance

Intensity of relative

importance Definition Explanation

1 Equal importance Two activities contribute equally to the objective3 Moderate importance of one over another Experience and judgment slightly favor one activity

over another5 Essential or strong importance Experience and judgment strongly favor one activity

over another7 Demonstrated importance An activity is strongly favored and its dominance is

demonstrated in practice9 Extreme importance The evidence favoring one activity over another is of

the highest possible order of affirmation2,4,6,8 Intermediate values between the two adjacent

judgments

When compromise is needed

Reciprocals of above

non-zero numbers

If an activity hasone of theabove numbers compared

with a second activity, then the second activity has

the reciprocal value when compared to the first

Source: Saaty (1980)

Table IV Random index (RI) for factors used in the decision-making process

n 1 2 3 4 5 6 7 8 9 10 11 12

RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.58

Source: Saaty (1980)



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vendor selection (Partovi et al., 1990), quality function deployment (Bergquist and

Abesysekera, 1996), software metrics evaluation (Sureshchandar and Leisten, 2006),

material selection (Dweiri and Al-oqla, 2006) and supplier selection (Percin, 2006). Use of

AHP in a problem-like IS architecture evaluation, however, is not prominent in the literature.

5. AHP in SCM evaluation

This work presents the integrated BSC-AHP approach for SCM evaluation. The AHP can be

the best tool for prioritizing and choosing the best BSC perspectives for SCM operations.

The hierarchic portrayal of a problem is as follows-

In the present study, the overall performance measurement system (PMS) of SCM has been

defined by three performance criteria in the hierarchy, i.e. strategic, tactical and operational

level. At the lowest level the four BSC perspectives have been kept as alternatives. The result

of AHP will help in prioritizing the most critical perspective of the SCM evaluation.

For decomposition or structuring of the problem as a hierarchy, the first (or top) level is the

overall performance measurement system. In the second level are the three factors or

criteria, which contribute to the goal (overall PMS), in the third level (bottom level) are the four

BSC perspectives. Different BSC perspectives are the alternatives in the hierarchy to be

evaluated in terms of the criteria in the second level. The pictorial representation of the

hierarchy is as shown in Figure 1.

As discussed above, the important criteria to the overall PMS are three performance levels of

the organization as:

1. PMS at strategic level (Ps);

2. PMS at tactical level (Pt); and

3. PMS at operational level (Po).

These three performance levels have been considered so as to evaluate the SCM

performance from the overall perspective and provide SCM a comprehensive performance

measurement system.

In the AHP, elements of a problem are compared in pairs with respect to their relative impact

(weight or intensity) on a property they share in common. Pair-wise comparisons are

reduced to a matrix form. When sets of elements are compared with each other a square

Figure 1 Pictorial representation of the problem hierarchy



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matrix is produced. The square matrix has an equal number of rows and columns together

with eigenvectors and eigenvalues. The reason for this computation is that it gives a way to

determine quantitatively the relative importance of factors. The factors with the highest

values are the ones that should be concentrated on for developing a plan of action to

achieve objective. AHP structures the problem hierarchically and a matrix is arranged to

compare the relative importance of criteria in the second level with respect to the overall

objective or focus of the first level. Similarly, matrices are also constructed for pair-wise

comparisons of each alternative in the bottom level with respect to the criteria of the second

level. These are shown in Tables V-VII and described in section 5.2. Case study

methodology was used in making the pair-wise comparisons and the following types ofquestions have been noted to occur.

In comparing one element with another:

B Which is more important or has a greater impact?

B Which is more likely to happen?

B Which is more preferred?

All the questions asked during the case study appeared to fall in one of these three

categories. In comparing criteria it is asked which criterion is more important? In comparing

alternatives with respect to criteria it is asked which alternative is desired?

5.1. Case study

Five supply chains from different industrial contexts and backgrounds were chosen for this

study in order to achieve a fairly generalizable set of results. These companies are selected

on the basis of their business operations as well as performance measurement related

practices. All the five companies are leading companies in their respective areas with

sizable market shares. From five cases, one company is a leading automotive company, one

is an electronic goods company, one is a food and beverage company and the other two

companies are leading fast moving consumable goods supply chains. The study comprised

open and semi-structured interviews with the senior executives. Apart from executives, key

Table VI Priorities with respect to P strategic, P tactical and P operational

BSC perspectives P strategic P tactical P operational

Financial 0.227 0.212 0.345Customer 0.326 0.205 0.149Internal business 0.234 0.224 0.350Innovation and learning 0.213 0.359 0.156

Table V P overall performance (level 1)

Po 1 2 3 Weights

1 P strategic 1.00 6.00 8.00 0.7552 P tactical 0.17 1.00 0.20 0.0673 P operational 0.13 5.00 1.00 0.178

Notes: Max. eigenvalue 3:4134; consistency ratio 0:0913

Table VII Priorities with respect to P overall performance

1 Financial perspective 0.2472 Customer perspective 0.2863 Internal business perspective 0.2544 Innovation and learning perspective 0.213



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functional managers as well as supervisory staff were also interviewed to obtain their

viewpoints. Interviewees were asked to compare pair-wise on a scale of 1 to 9 their

agreement with a number of criteria/alternatives. Interviews lasted from 1 to 2 hours. Criteria

and alternatives were ranked on the basis of the opinion of the majority of the interviewees.

Wherever available, the interview data was supplemented with archival data such as

department manuals, process manuals, financial reports and other performance

measurement related documents. Use of multiple-informants and use of archival data

helped us crosscheck pertinent information and verify the reliability of the data obtained.

5.2. An illustration of subjective judgments using the scaleWhile considering criteria and alternatives independent, the cells of the AHP matrix have

been filled in with the subjective judgments using the 1 to 9 scales and based on the

preference and perception of the criteria for the overall performance measurement. For

example in Table V, which represents the level 1 of hierarchy, when asked, With respect to

overall performance measurement, what is the importance of performance measures at

strategic level (P strategic) to performance measures at tactical level (P tactical)? If the P

strategic was strongly more important then the integer 6 was entered in the corresponding

cell; it is reciprocal, or 1/6 was automatically entered for the reverse comparison. In the same

way other cells of the matrix were also filled in. According to the majority of respondents

feedback in the case study, different ranks are entered in the table. In the bottom level, the

four BSC perspectives are to be pair-wise compared for each of the performance levels

(criteria). Priorities are synthesized from the second level down by multiplying local priorities

by the priority of their corresponding criterion in the level above and adding them for eachelement in a level according to the criteria it affects. This gives the global or composite

priority of that element which is then used to weight the local priorities of elements in the level

below compared by it as criterion and so on to the bottom level.

6. Results and discussion

Clearly from Table V, P strategic is (0.755) perceived to be the most important criterion

followed by the P operational (0.178) and P tactical (0.067). It reveals that performance

measurements related to strategic level have been considered to be most important

whereas the measures at tactical levels have been rated least. It also suggests that

performance measures, which reflect the strategic performance for the long term, are

preferred. It is interesting to note that performance measures at operational level have been

preferred over the same of at tactical level. It shows that the day-to-day performance

measures have been considered to play more significant role than the same of the middlelevel management. The tactical level, in general, plays a role of catalyst in background to

convert the objectives of strategic level into reality through operational level. Hence, from the

view of physical performance, the operational level performance measure may get an edge

over the tactical level. However, the performance measures related to tactical levels have

their own importance in achieving the objective.

For the criterion P strategic (Table VI) the customer perspective (0.326) is perceived as the

most important BSC perspective followed by the internal business perspective (0.234). It

shows that to survive in the present era of globalization, the companies should constantly

gauge the customers and market trends to design and deploy new strategies continuously

through internal operations. With respect to P tactical and P operational the innovation and

learning (0.359) and internal business (0.350) perspectives are perceived as the most

important BSC perspectives respectively. This result shows that at middle level

management, issues pertaining to the new ideas, product/process developments and

training etc. should be concentrated on. It will help to transform the vision of the strategic

level management by executing ideas at operational level. Operational level usually controls

the day-to-day execution in any organization. So at this level, by focusing on the internal

functional activities could be crucial for any SCM operations. To summarize, it can be seen

that internal operation is getting consistently comparable weights at strategic, tactical and

operational levels. The results are justified, as one of the major objectives of SCM is to

synchronize the internal operations with respect to operations/requirements of

suppliers/customers.



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Finally in P overall (Table VII), the customer perspective (0.286) would be selected first

followed by the internal business perspective (0.254). It shows that for overall performance

measurement, the criteria related to customer perspective and internal business operations

should be focused most as compared to other BSC perspectives. In summary, above results

suggests prioritization of the different performance levels. It further ranks the different BSC

perspectives in SCM evaluation.

7. Conclusions and implications of the study

The integrated BSC-AHP approach, as a decision-making tool presented in the paper isefficient in dealing with multi-criteria decision-making problems. AHP involves the process of

choosing among many alternatives based on multiple criteria and sub-criteria. The

decision-maker can perform sensitivity analysis on the selection choices and the sub-criteria

to account for variations (changes) of the pair-wise comparisons and have a high degree of

confidence in his/her judgment.

Performance evaluation of SCM is a problem facing decision-makers nowadays, especially

in the era of globalization. Results of this study give useful insights to managers to prioritize

different BSC perspectives. It gives rational to decide which decision level performance

plays the most important role in overall performance measurement. At the same time it also

ranks different BSC perspectives to prioritize them rationally in normal business operations.

The research work has contributed to important issues of SCM performance evaluation

theory and practice. The following points can be summarized:

B This study contributes to performance evaluation of SCM. It points out the importance of

key players in the performance measurement of SCM, and the nature of roles they need to

play.

B Results of case study throw light on method of prioritizing performance measurements at

different decision levels also. The approach can help firms to focus on the most critical

performance measurement levels while giving them the top priority.

B A balanced performance evaluation such as, balanced scorecard not only helps

organizations in faster and wider progress monitoring of their operations but can also help

them in improving their internal and external functions of business.

B BSC perspective can be important in firms specific contexts at different decision levels

and how to prioritize different perspectives from the point of view of the overall

performance measurement. It focuses on critical factors that are likely to contribute for thesuccessful performance measurement of SCM.

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About the authors

Milind Kumar Sharma has taught many subjects related to production and industrial

engineering and operationsmanagement. Priorto joining the JNV University, Jodhpur in 1998,

he servedin industry for four years. He hasbeen awarded researchprojectsunder theCareer

Award for Young Teacher Scheme by the All India Council for Technical Education (AICTE)

and University Grants Commission (UGC), New Delhi, India. His areas of research interests

include management information system, performance measurement, supply chain

management and small business development. He has published research papers in

Production Planning and Control, Computers & Industrial Engineering, Journal of

Manufacturing Technology Management, International Journal of Globalization and Small

Business,International Journal of Enterprise Network Management,International Journal of

Productivity and Quality Managementand Measuring Business Excellence. Milind Kumar

Sharma is the corresponding author and can be contactedat: [email protected]

Rajat Bhagwat is an Associate Professor in the Department of Mechanical Engineering, JNV

University, Jodhpur. He has also worked as a Research Assistant in the University of Hong

Kong, Hong Kong. His areas of research interests include information systems, simulation,

modeling and control of flexible manufacturing systems. He has working experience in

industrial projects in the areas of production, planning and control, capacity expansion, and

layout planning. He has been awarded a postdoctoral fellowship at the University ofBordeaux, France. He has a number of publications in international journals and conferences.


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