The paper develops a framework for benchmarking internal supply chain performance using financial data, offering an alternative to traditional performance evaluations. Illustrated through the FMCG industry, the framework utilizes publicly available financial data to identify areas for improvement in supply chain efficiency and productivity. This methodology enables firms to compare their performance against competitors and highlights specific shortcomings for potential enhancements.

1. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 119 editor@iaeme.com
1
Department of Mechanical Engineering,
CT Institute of Engineering Management and Technology, Jalandhar, India
2
Department of Industrial and Production Engineering,
National Institute of Technology, Jalandhar, India
3
Department of Mathematics, Lovely Professional University, India
ARSTRACT
In this paper, a frame work is developed for benchmarking internal supply chain performance
using financial data as an alternative to traditional approach of use of different models of supply
chain performance evaluation. This frame work is demonstrated by using the publicly disclosed
financial data compiled and distributed in the PROWESS databases maintained by the Center for
Monitoring Indian Economy (CMIE). By following this framework, a firm can identify areas of
opportunity for improvement in its internal supply chain. Further, the framework can help to identify
specific reasons behind the performance levels in the internal supply chain and stimulate
performance improvement. To illustrate the framework, it is applied to fast moving consumer goods
(FMCG) industry. The framework provides meaningful results for the firms.
Keywords: Supply chain performance, Benchmarking, Fast moving consumer goods (FMCG),
PROWESS, Length of supply chain, Efficiency of supply chain, Supply Chain working capital
Productivity
I. INTRODUCTION
There has been an increased awareness in recent years regarding the role and potential of
supply chain managementin supporting corporate goals. Management theoristsas well as
practitioners have addressed the problem of how to improve supply chain processes. This article is
focused to a discussion of the internal supply chain, defined as the flow of materials from the
procurementof raw materials to the delivery of finished goods to thecustomers of an organization [1].
For improving the supply chain performance of a particular firm, it is essential to use performance
measures appropriate to its business. Subsequently, it may carry out a benchmarking exercise.
Benchmarking is one way of assessing performance based on these measures[2]. Smeltzer et al.
tested the relationships among benchmarking, strategic purchasing, and performance of firms and
found that benchmarking is positively related to firms performance and strategic purchasing [3].
BENCHMARKING INTERNAL SUPPLY CHAIN
PERFORMANCE: DEVELOPMENT OF A FRAME WORK
Harjit Singh1
, Anish Sachdeva2
, Gurpreet Kaur3
Volume 6, Issue 6, June (2015), pp. 119-126
Article ID: 30120150606011
International Journal of Mechanical Engineering and Technology
© IAEME: http://www.iaeme.com/IJMET.asp
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
IJMET
© I A E M E

2. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 120 editor@iaeme.com
A number of measurement models was then defined in the 2000s and helped to analyse
supply chains in terms of some or all of their components (collaboration, human resource
management, sus- tainability, etc.)[6].Various sets of supply chain performance measures
discucussed in the literature, the most widely accepted in the industry is Supply Chain Opeartions
Reference (SCOR) model. It has developed by Supply-Chain Council which is an independent, non-
profit, global corporation interested in getting the industry to standardize supply chain terms so that
meaningful supply chain benchmarking can be carried out. Supply chain software vendors such as
SAP have adopted the SCOR performance measures in their performance management module.The
maturity classification proposed in the Supply Chain Operations Reference (SCOR) model relates to
companies’ ability to manage the full scope of a supply chain [10]. As per the SCOR model, supply
chain performance measures fall under the following four broad caegories:
• Cost
• Assets
• Reliability
• Flexibility
The measures related to costs and assets as internal-facing measures, while reliability and
flexibility are termed as customer-facing measures. Typically, a firm offers a bundle consisting of
price, delivery and flexiblity to its customers. Price, in competitive markets, is dictated by the market
place. Thus, only delivery and response related measures are termed as customer-facing measures.
The performance measures related to assets and costs affect the profitability of the firm and are, thus,
termed as internal-facing measures.
Each supply chain evaluation model is not suitable for each and every sector of industry due
to some limitations of each of these models. Besides plenty of models, SCOR is most widely
accepted model in the industry.Many companies have no measures for their supply chains or they
have poor measures. That is incredible given the importance, complexity and scope of supply chains
with international sourcing and competitors. Such companies have the supply chains they designed
and deserve. Supply chain management excellence is no longer a matter of competitive advantage. It
is matter of survival. Meeting and exceeding customer expectations requires it. Firms that do not
include supply chain manegement as a core competency do not lead and do not do a good job .
SCOR measures, however, do not capture order delivery lead time and measure related to product
variety. So, to that extent, performance measures under the SCOR model do not seem to be
comprehensive. Another shortcoming of SCOR model is unlike Westerncountries, most countries in
Asia suffer from the problem of data availability. Even if the relevant data are available, one is not
sure of the validity and reliability of the data.
The opportunity analysis tool is used to ascertain how efficiently firms are managing the
internal supply chain processes. Financial measures are used to gauge the firm’s operational
performance [13].
II. BENCHMARKING FRAMEWORK
This Study is focused on important metrics like cost and assets utilization data, for which
data are available in annual financial statements of listed companies.This financial data is also
obtainable from database like PROWESS (India) and COMPUSTAT (United States) that provide
information in compiled form. The objective of the present work is development of a framework for
“benchmarking internal supply chain performance using financial data” that can help to identify
specific reasons behind the performance levels in the internal supply chain and stimulate
performance improvement. To illustrate the frame work it is applied to FMCG (fast moving

3. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 121 editor@iaeme.com
consumer goods). The frame work provides meaningful results for the firms in the industry. The
advantage of this approach lies in the fact that it allows benchmarking using public information. This
information is available in financial statements of annual reports and in business periodicals. To
demonstrate this framework, publicly disclosed financial performance data, compiled and distributed
in the PROWESS database maintained by the Centre for Monitoring Indian Economy (CMIE), were
analysed. One can obtain, through these databases, information such as background, share prices,
sensitivity index, financials, product profile, raw materials consumed, and accounting policies of the
firms. The relevant expressions which are used in this study are shown in Table 1 and these are
available in Prowess.
Table 1: Terms directly obtained from Financial Statements
Terms from the income and expenditure statement Symbol
Cost of raw materials CRM
Cost of Production CP
Cost of Distribution DC
Cost of Sales CS
Net Sales NS
Inventories (inclusive of raw materials, semi-finished goods and
finished goods)
INV
Raw material inventory RM
Semi-finished goods inventory SFG
Finished goods inventory FG
Account receivable (excluding loans and advances) AR
Accounts payables AP
In this study the following three parameters of Supply Chain Performance Measures are calculated:
1. Total Length of Supply Chain:
The total length of the chain is arrived at by adding up the days of inventory for raw
materials, work-in-process and finished goods remain in the firm. The firm that has the minimum
total length of the chain is said to be have the best performance. The total length of supply chain is
calculated by
Days of raw material (DRM) =RM * 365CRM
RM = Raw Material Inventory for one financial year
CRM = Cost of raw material for one financial year
Days of Work in Process (DWIP) = SFG * 365CP
SFG = Semi finished goods inventory for one financial year.
CP = Cost of Production for one financial year.
Days of Finished Goods (DFG) =FG * 365CS
FG = Finished goods inventory for onefinancial year
CS = Cost of sales for one financial year
Total Length of supply chain in days = DRM + DWIP + DFG

4. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 122 editor@iaeme.com
The duration of time taken by the material flow is captured by this measure. Firms like Dell
Computers perform very well on this dimension.
2. Efficiency of Supply Chain Management:
The internal supply chain inefficiency ratio is a measure of the efficiency of internal supply
chain management. To calculate this ratio, total inventory carrying costs and the distribution costs is
considered to be the components of the internal supply chain management costs. The Supply Chain
Inefficiency Ratio is calculated as:
Supply Chain Management Costs (SCC) = DC + INV + ICC
Supply Chain Inefficiency Ratio (SCI) = SCC NS
DC = Cost of Distribution for one financial year
INV = Total Inventory for one financial year
ICC = Inventory carrying cost
NS = Net Sales for one financial year
The supply chain inefficiency ratio (the lower the better) provides an insight into the internal
supply chain management efficiency of the firm. This measure is termed the supply chain
inefficiency ratio since the supply chain cost will be higher if there are inefficiencies in the system.
Firms with efficient supply chain systems will have relatively lower scores on this performance
measure.
3. Supply Chain Working Capital Productivity
The analysis of firm on this metric will also be based on the levels of inventory, accounts
receivable and accounts payable. Firms with efficient supply chains will usually have high supply
chain working capital productivity.
The supply chain working capital productivity is calculated as:
Supply Chain Working Capital (SWC) = INV + AR – AP
Supply Chain Working Capital Productivity (SWCP) =NS SWC
INV = Total Inventory for one financial year
AR = Accounts receivable (excluding loans and advances) for one financial year
AP = Accounts payables for one financial year
NS = Net Sales for one financial year
A firm can compare its own performance with that of its competitors and that the industry
aggregate in order to ascertain where it stands in terms of supply chain performance. Using
benchmarking data, a firm can also map a supply chain profile that allows it to effectively capture
both the dimensions of time and cost in one diagram. Further, a firm can also compare its own
profile with that of competitors in order to ascertain where it stands in terms of costs and length of
time in the chain.
In this study the new concept of financial benchmarking is focused, which can help a firm in
comparing its supply chain performance with competitors using financial data.
III. COMPARATIVE ANALYSIS OF FMCG SECTOR COMPANIES
In a highly competitive market environment, the relative performance of a firm in sale,
market share, and its supply chain depends primarily on its Strategic decisions and financial aspects.

5. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 123 editor@iaeme.com
Supply chain effectively makes the firm profitable in one or many ways, either through efficient
distribution network or through less cost transactions and well defined information flow.
The top three public firms (A, B and C) from the fast moving consumer goods sector are
selected for analysing the supply chain performance. By using the above mentioned methodology,
days of raw material inventory, days of work-in-process, and finished goods inventory are calculated
for last four years.
Analysis of Days of Raw Material Inventory
Table 2: Days of raw material inventory
Year A B C
2011 80.47 64.51 45.09
2012 95.06 69.92 27.02
2013 66.42 69.08 15.87
2014 59.44 78.58 16.98
Figure 1: Comparison of days of raw material inventory
The days of raw material inventory of company C are very less as compared to Company A and B.
Analysis of Days of Work-in- Process Inventory:
Table 3: Days of work in process inventory
Year A B C
2011 1.66 10.64 1.25
2012 2.01 11.35 1.35
2013 5.80 15.42 2.42
2014 9.53 13.07 2.17
0
10
20
30
40
50
60
70
80
90
100
2011 2012 2013 2014
Daysofrawmaretial
inventory
A
B
C

6. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 124 editor@iaeme.com
Figure 2: Comparison of days of work in process inventory
The days of work in process inventory for company B are much greater than company A and
C and this also affects the overall length of supply chain. The company B has to improve its process
to reduce the days of work in process inventory.
Analysis of Days of Finished Goods Inventory
Table 4: Days of finished goods inventory
Year A B C
2011 24.49 19.20 20.06
2012 26.75 17.79 18.70
2013 24.05 10.14 16.06
2014 27.29 19.06 18.45
Figure 3: Comparison of days of finished goods inventory
Total Length of Supply Chain
Table 6: Total length of Supply Chain in days of all three companies
Year A B C
2011 106.62 94.35 67.19
2012 123.83 99.06 47.06
2013 96.26 95.24 34.35
2014 96.26 110.71 37.60
0
2
4
6
8
10
12
14
16
18
2011 2012 2013 2014Daysinworkinprocessinventory
A
B
C
0
5
10
15
20
25
30
2011 2012 2013
A
B
C

7. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 125 editor@iaeme.com
Figure 4: Comparison of length of supply chain in
In the study from 2011 to 2014, A and B has almost same length of supply chain but C is
much better in length of supply chain. C has reduced its length from 67.19 to 37.60. The C is best
practice firm in the length of supply chain. It has fewer days of raw material and work in process as
compared to its competitors.
IV.CONCLUSIONS
This article provides the performance measures that can be evaluated through publicly
available information. A framework for benchmarking using these performance measures was
presented and applied to the FMCG sector industry. By following this framework, firms can identify
areas of opportunity for improvement in their internal supply chain. The framework was one of the
main benefits of this exercise in that it highlights performance shortcomingsin specific areas. Such
apractice encourages firms to look outward and gain an external perspective on performance
improvement opportunities
REFERENCES
1. Krajewski, L. and L. Ritzman. Operations Management: Strategy and Analysis, Addison
Wesley, MA, 1990.
2. Bogan, C. and M. English. Benchmarking for Best Practices: Winning through Innovative
Adaptation, McGraw-Hill, New York, NY, 1994.
3. Smeltzer, L. and A. Carr. “The Relationship among Purchasing Benchmarking, Strategic
Purchasing, Firm Performance, and Firm Size,” The Journal of Supply Chain Management,
(35:4), Fall 1999, pp. 4-16.
4. Janat Shah and Nitin Singh, “Benchmarking Internal Supply Chain Performance: Development
of Frame Work,”International Journal of Supply Chain Management, 2001. pp 37-42
5. JanatShah .Supply chain management Text and Cases. Pearson Education, 2009
6. Beamon, B.M., “Supply chain design and analysis: models and methods”. International Journal
of Production Economics, Vol. 55 (3), 1998 pp 281-294.
7. Beamon, B.M.,“Measuring supply chain performance”.International Journal of operations &
Production Management, 1999 Vol.19 (3), pp 275-292
8. Centre for Monitoring Indian Economy, PROWESS User’s Manual: Vol. 1, 2, 3, Bombay,
India, 2014.
9. Chandra, P. Financial Management, Tata McGraw-Hill, New Delhi, India, 1997.
0
20
40
60
80
100
120
140
2011 2012 2013 2014LengthofSupplyChainindays
A
B
C

8. Benchmarking Internal Supply Chain Performance: Development of A Frame Work, Harjit Singh,
Anish Sachdeva, Gurpreet Kaur, Journal Impact Factor (2015): 8.8293 Calculated by GISI
(www.jifactor.com)
www.iaeme.com/ijmet.asp 126 editor@iaeme.com
10. Hartley, J.L. and G.E. Jones. “Process Oriented Supplier Development: Building the Capability
for Change, International Journal of Purchasing and Materials Management, (33:3), Summer
1997,pp. 24-29.
11. Lester, M. “An Interview with Bill L. Ramsey: One on One,” The Journal of Supply Chain
Management (35:4), Fall 1999, pp. 2-6.
12. Monczka, R., R. Trent, and R. Handfield. Purchasing and Supply Chain Management,
Southwestern Publishing, College Division, Cincinnati, OH, 1998.
13. Narasimhan, R. and J. Carter. “Linking Business Unit and Material Sourcing Strategies,”
Journal of Business Logistics, (19:2), 1998.
14. Smolen, G. “Appraisal Company Status and Direction for Survival,” The Appraisal Journal,
(65:2), Chicago, IL, 1997,pp. 156-165.
15. Gunasekaran, A., Patel, C.,Tirtiroglu, E., “Performance measures and metrics in a supply
chain environment,”International Journal of Operations & Production, 2001
16. Lamouri, S., Thomas, A., 2000. “The low level master production schedule and planning bills
in a just in time context,” International Journal of Production Economics, Vol 64, 2000, pp
409-415.
17. Ms. Uma Priyadharshini and Dr. S. A. Lourthuraj, “An Empirical Analysis on Semi Strong
Form Efficiency In Select FMCG Companies Listed In Nse” International Journal of
Management (IJM), Volume 6, Issue 1, 2015, pp. 343 - 347, ISSN Print: 0976-6502, ISSN
Online: 0976-6510.
18. Abhinna Srivastava and Vineet Singh, “Augmentation of Promotion Sensitivity For FMCG In
India” International Journal of Management (IJM), Volume 6, Issue 1, 2015, pp. 28 - 37, ISSN
Print: 0976-6502, ISSN Online: 0976-6510.
19. Bijesh Paul and Dr Jayadas.N.H, “A Generalized Algorithm For The Demand Prediction of A
Short Life Cycle Product Supply Chain and Its Implementation In A Baked Product”
International Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 1,
2013, pp. 44 - 53, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.
20. Ch. Srinivas, “A View On Conwip Control Policy In Supply Chain Using Heuristic Method”,
International Journal of Production Technology And Management (IJPTM), Volume 5, Issue 1,
2014, pp. 1 - 9, ISSN Print: 0976- 6383, ISSN Online: 0976 – 6391.