performance assessment and optimization of global...
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Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
Bangkok, Thailand, 20-22 February 2015 Paper ID: T596
1 www.globalbizresearch.org
Performance Assessment and Optimization of Global Supply Chains
Jagadeesh Rajashekharaiah,
SDM Institute for Management Development,
Mysore, Karnataka, India,
E-mail: [email protected]
___________________________________________________________________________
Abstract
Supply chains are assessed for their performance using various metrics and attributes that
help to compare and benchmark the performance across the globe. Several models have been
developed in the past but are limited to one particular approach and this paper develops a
model using both the metrics and the challenges faced by the global supply chains. This
allows the performance assessment against a supply chain’s capabilities to meet the
challenges. The paper uses the results of two independent surveys based on their applicability
and comprehensiveness and develops the model. The paper also describes how these metrics
can be used to optimize and compare using a weighted score model. The objective is to
provide a better decision making model using well established mathematical models.
___________________________________________________________________________
Key words: supply, chains, performance, metrics, optimization, global, assessment, criteria
JEL Classification:
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
Bangkok, Thailand, 20-22 February 2015 Paper ID: T596
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1. Introduction
Supply chains constitute the backbone of business and economy. The increased attention
on supply chain management focusing on issues like supply chain competitiveness, risk,
networking and collaboration, vendor managed inventory, among other topics, prompts more
and more researchers to examine these issues. In the domain of Operations Management, the
supply chain management along with the logistics function is a key area management. Both in
engineering and management degree courses, the students study supply chain management
(SCM) as a core subject and acquires the necessary skills. The proliferation of the retail trade
enabled the SCM function to bloom and spread across various disciplines along with global
presence.
The SCM function involves a number of people and organizations who interlink and exchange
information, money or goods, (and the supply chain performance is dependent on several drivers,
as illustrated by a simple diagram shown in Figure 1, as given by Chopra & Meindl (2007).
However, it is necessary to properly integrate both the internal and the external supply chains
and be inter supporting to ensure supply chain success, (Bratić, 2011), as given in Figure 2.
Figure 1: Drivers of supply chain performance
Figure 2: External and the internal supply chain elements.
Supply chain priorities - Do they align with operations’ performance?
Operations managers constantly grapple with meeting multiple objectives and thus seek
optimal utilization of the resources. Considering the evolution of the production systems,
starting from handicraft or job systems to mass and flow systems, the operations priorities
varied to accommodate the changing strategies over time. This also prompted the operations
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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managers to develop "operations strategies" to successfully meet and beat the competition
offered by the global players.
It is understandable that the operations managers focused on key aspects while
manufacturing products and services and focused on 'critical success factors'. These factors
traditionally became the priorities and the challenge was to satisfy them to the maximum
possible extent. This also led to the practice of compromising whenever required because of
the inherent conflicts and constraints, (Boyer and Lewis, 2002). The three fundamental
success factors recognized as priorities are: quality, cost, and delivery, not necessarily in that
order but with equal importance. Later, three more factors namely flexibility, innovation, and
speed were added to expand the basket of success factors, (Ward, et al. 1998). It is obvious
that to realize these success factors a supportive supply chain should exist and enables to
realize the targets in each of the success factors considered.
This further requires the cooperation and coordination of all the supply chain partners
involved in the entire network. However, the strategic alignment between the partners is
difficult to measure and analyze, (Vachon, et al. 2009).
2. Measuring the supply chain performance – Literature Review
Measuring the performance of supply chains is a very popular area of research as
observed by the number of publication in the last two decades. While some researchers have
proposed different measures and performance metrics, some others have developed a
framework that enables performance assessment. Stewart (1995) illustrates the benchmarking
of the supply chain performance. Tan, et al. (1998) suggest assessment at different levels to
enable a better and comprehensive reporting.
Beamon (1999) identified three types of performance measures as necessary components
in any supply chain performance measurement system, and also recommends new flexibility
measures for manufacturing supply chains. Wong and Lee (2008) while arguing about the
complexities in performance assessment indicate how difficult the assessment could be
because the supply chain itself is a new field. Several researchers have developed frameworks
to help better assessment of the supply chain performance. For example, Gunasekaran, et al.
(2001) demonstrates a framework for measuring the strategic, tactical and operational level
performance in a supply chain.
Based on trust, terms like Supply Chain Event Management, Supply Chain Process
Management, and Supply Chain Execution Management are used interchangeably. Supply
chain monitoring must start with tight tracking of the many different processes involved in a
supply chain. As products and information flow through different parts of the supply chain, it
is necessary to capture the information and ensure that the end users’ requirements are
satisfied. Supply chain automation is a major trend in this direction that offers a variety of
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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tools and techniques to monitor and improve supply chain performance, (Huhns and
Stephens, 2001). Shepherd and Günter, (2006) have attempted a critical review of literature
pertaining to supply chain performance evaluation and have given some directions for further
research.
In another survey Gunasekaran and Kobu (2007) have provided an overview of measures
applicable for performance assessment of supply chains. Several researchers have
investigated the issue of performance measurement considering various aspects of supply
chain include. Chan (2003) introduces five other performance measurements like resource
utilization; flexibility; visibility; trust; and innovativeness., Bhagwat, and Sharma (2007)
developed a balanced scorecard for supply chain management (SCM) that measures and
evaluates day-to-day business operations from following four perspectives namely: finance,
customer, internal business process, and learning and growth. Wong and Wong (2007)
suggest two DEA (Data Envelopment Analysis) models– the technical efficiency model and
the cost efficiency models that are coupled with scenario analysis to enable improved
resources planning decisions.
A hierarchy based supply chain performance measurement system using the Analytic
Hierarchy Process is reported by Xu, et al. (2007). Brun, et al. (2009) provides a framework
for the selection of the right Performance Measurement System (PMS) for different supply
chain typologies. Further, supply chain performance measurement system implementation
(Charan et al. 2008) indices how the system is implemented. It is obvious from the literature
review that the performance measures have attracted the attention of the researchers and it is a
challenging task to develop an exhaustive performance measurement system considering all
the factors suggested or recommended across the world by researchers and practitioners.
3. Global supply chains - challenges and issues
Since the dawn of globalization in the early nineties, researchers across all disciplines
have studied the impact of going global and the associated success factors. The term
globalization is now deeply rooted in everyday business and general talk. Wikipedia
(www.wikipedia.com) defines globalization as “the process by which regional economies,
societies, and cultures are integrated through a global network of communication,
transportation, and trade. The term is used to refer specifically to economic globalization: the
integration of national economies into the international economy through trade, foreign direct
investment, capital flows, migration, and the spread of technology, (Bhagwati, 2004).
Globalization is usually recognized as being driven by a combination of economic,
technological, socio-cultural, political, and biological factors, (Sheila, 2004).The term can
also refer to the transnational circulation of ideas, languages, or popular culture through
acculturation. Alli, et al. (2007) has given a good interpretation of globalization and its
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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effects. According to them globalization is the interaction between economies, technologies
and politics which creates an environment that reduces state regulation of the market
promoting a more dominant role for large multinational corporations.
The advent of globalization made the operations mangers to look beyond the local
boundaries and start getting inputs from several places across the world and to look at the
whole world as their markets. Global supply chains with inbound and/or outbound logistics
are quite common today as the suppliers and customers could be located anywhere in the
world. Secondly, it is prudent to look for suppliers and customers far beyond the local
boundaries to realize several distinct advantages in terms of quality, quantity, price, variety,
currency fluctuations, regional policy matters, and to build balanced networks. On the other
hand global supply chains also have their limitations and challenges. A survey conducted by
McKinsey reveals the interesting responses as depicted in Figure 3. This paper proposes to
measure the supply chain performance against these perceptions to construct the supply
chains to meet these challenges. This ensures that the assessment of the supply chains are
with reference to the actual performance parameters taking into mind the challenges and the
realities across the globe.
4. Mapping of global supply chain challenges and supply chain
performance measures
Quality, cost, and delivery are the primary key metrics anytime applicable to assess the
supply chain performance. In addition as already informed, flexibility, innovation and speed,
constitute the expectations from the supply chains. Flexibility and speed refer to several sub-
factors like flexibility in terms of volume, variety, lead times, pricing, batch size, delivery
modes, packaging, distance traveled, shelf life and ability to handle last minute changes, and
several others. Similarly, speed of operations in terms of fast delivery, rapid changes in
design, ability to introduce new practices quickly, improved responsiveness, faster
turnarounds in inventory, and above all faster communication capabilities, will be helpful for
a comprehensive assessment.
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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Figure 3: Percent respondents agreeing to a given aspect of challenges
(Source: http://www.mckinsey.com/insights/operations/
the_challenges_ahead_for_supply_chains_mckinsey_global_survey_results)
Considering the moderate amount of literature dealing with the performance assessment of
the supply chains, the author proposes to adopt the model suggested by Anvari, et al. (2011)
based on the following considerations:
The proponents of this model have examined the various models of performance
assessment developed by different authors and have given those factors due
consideration
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Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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Firstly, the affecting factors on SC performance are addressed on the basis of
literature and elites' opinions; and later industrial connoisseurs' ideas were
gathered to identify the factors to be included in the questionnaire
The survey reveals the important factors
The list of factors is modified to reflect the changes in the environment
4.1 Mapping of factors and he challenges
The next step involves the mapping of the list of factors given by Anvari, et al. (2011)
and the challenges given by the McKinsey studies by Gorey, Jochim, and Norton. (2015)
reveal how the assessment can become more relevant to the industry requirements. Further
based on the respondents' perceptions and comments, the lists are ranked from most preferred
to least preferred parameters. Table 1 shows the assessment factors arranged in decreasing
order of importance. (The ranks below27 are not part of the ranks given by the respective
authors but included here for the completeness of the earlier list, and the ranks are just serially
given). Later using the McKinsey's report by Gorey, Jochim, and Norton (2015), Table 2
shows the challenges and the corresponding ranks.
Table 1: Assessment factors and corresponding ranks (Anvari, et al. (2011)
Assessment factors Rank
Purchase order cycle time 1
Order entry methods 2
Quality of delivered goods 3
Supplier ability to respond to quality problems 4
Buyer-supplier partnership level 5
Cycle Time 6
Delivery performance 7
Rejection rate 8
Effectiveness of distribution planning schedule 9
Customer satisfaction 10
Range of product and services 11
Order responsiveness 12
Fill rate 13
Warehouse cost 14
Accuracy of forecasting techniques 15
Lead time 16
Information sharing and availability 17
Frequency of delivery 18
Supplier assistance in solving technical problems 19
Flexibility to meet particular customer needs 20
Total Cash Flow Time 21
Supplier cost saving initiatives 22
Delivery reliability 23
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Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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Quality of delivery documentation 24
Inventory flow rate 25
Product development cycle time 26
Delivery lead time 27
Effectiveness of delivery invoice methods 28
Level of customer perceived value of product 29
Level of supplier's defect free deliveries 30
Master Production Scheduling 31
Rate of Return On Investment 32
Rate of unfilled orders 33
Variations against budget 34
Table 2: Global challenges ranked in Gorey, T., Jochim, M. and Norton, S. (2015)
Global Challenges Rank
Increasing volatility of customer demand 1
Increasing consumer expectations about quality 2
Increasing cost pressure in logistics/transportation 3
Increasing pressure from global competition 4
Increasing volatility of commodity prices 5
Increasingly complex patterns of customer demand 6
Increasing financial volatility 7
Increasingly global markets for labor and talent 8
Increasing complexity in supplier landscape 9
Growing exposure to differing regulatory requirements 10
Increasing environmental concerns 11
Geopolitical instability 12
4.2 Observations and remarks
The first challenge in Table 2 pertains to the "Increasing volatility of customer demand"
which refers to the unpredictability of the demand and makes the forecasting difficult. This in
turn demands applying sophisticated methods of forecasting to improve the accuracy. But,
from Table 1, "Accuracy of forecasting techniques" is ranked at 15 thereby showing a lesser
preference. This is an indication of mismatch between what the customers perceive and the
experts opine. Complex pattern of customer demand is a challenge, ranked at the middle of
the list almost corroborating to the lesser preference to the forecasting accuracy. However,
the conventional factors like quality, cost, and delivery, rank higher in both the customers' list
Proceedings of the International Conference on Global Business, Economics, Finance and
Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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and list of the challenges. Similarly, factors like flexibility, innovation, and time related
parameters, are ranked almost at the same level of preferences in the two lists. However, the
two lists do not relate in any way in terms of the people surveyed or place of survey or
industries or the profile of the respondents. Hence, the lack coherence between the two lists
need not surprise in general, nevertheless shows some connectivity across the factors.
5. Weighted score model using the multiple criteria of performance assessment
Whenever a certain decision is based on multiple criteria a simple approach would be to
use a weighted score model. In the case of performance assessment of supply chain as shown
in Table 1, there are 34 factors established and hence a weighted score model would be
appropriate to simplify the decision of comparing the performance of the same supply chain
over a period of time or comparing a set of supply chains using similar criteria. The first step
in using the weighted score model is to convert the ranks to corresponding weights. The
criteria weights are developed by using the approach suggested by Alfares and Duffuaa
(2006), where a linear relationship specifies the average weight for each rank, assuming a
weight of 100% for the first-ranked (most important) factor. For any set of n ranked factors,
the percentage weight of a factor ranked as r is given by:
W(r, n) = 100 – Sn (r – 1)
Where, Sn = 3.19514 + (37.75756/n), 1<= r <= n, and r and n are integers
In the present case n = 34 and using a spreadsheet the weights are calculated and shown in
Table 3 along with their ranks.
Table 3: Rank and weights of the factors
Assessment factors Rank Weight in %
Purchase order cycle time 1 100
Order entry methods 2 95.69434353
Quality of delivered goods 3 91.38868706
Supplier ability to respond to quality
problems
4 87.08303059
Buyer-supplier partnership level 5 82.77737412
Cycle Time 6 78.47171765
Delivery performance 7 74.16606118
Rejection rate 8 69.86040471
Effectiveness of distribution planning
schedule
9 65.55474824
Customer satisfaction 10 61.24909176
Range of product and services 11 56.94343529
Order responsiveness 12 52.63777882
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Fill rate 13 48.33212235
Warehouse cost 14 44.02646588
Accuracy of forecasting techniques 15 39.72080941
Lead time 16 35.41515294
Information sharing and availability 17 31.10949647
Frequency of delivery 18 26.80384
Supplier assistance in solving technical
problems
19 22.49818353
Flexibility to meet particular customer needs 20 18.19252706
Total Cash Flow Time 21 13.88687059
Supplier cost saving initiatives 22 9.581214118
Delivery reliability 23 5.275557647
Quality of delivery documentation 24 0.969901176
Multiplying the regular scores by the weights, the weighted scores can be established and
the composite score is calculated taking up the sum of all the weighted scores. The weights
assigned by the model follow a linear decrement. However, this model starts tapering to lower
values and eventually reaches close to zero when there are 24 factors. Another approach to
assign weights could be to use "learning curve" theory, which starts assigning weights from
100 to the first value and then decrements the values in a negative exponential manner.
However, these models are definitely worth examining further in order to justify the
methodology of assigning weights. Variance around mean is established and any model
selected should be having a minimum deviation from the central value. This paper will not
delve into the details as it would demand a separate analysis.
6. Conclusions and Recommendations
Performance assessment of supply chains is considered a vital aspect sine the last two
decades because of the immense importance of the supply chains in the global economy and
also due to the proliferation of the global supply chains. Many researchers and professional
bodies have developed a variety of measures to assess the performance of supply chains and
most of these assessment parameters seem to be agreeing with the conventional measures that
existed right from the days of prioritizing the operations requirements. In this paper the
factors as obtained through a comprehensive survey and the challenges identified by a well-
known research based professional agency, have been mapped to examine how the
assessment can be made with respect to the challenges. This serves the objective of assessing
against the challenges faced and hence tests the ability of the supply chains in meeting those
challenges. However, the model proposed here is limited by the fact that the two lists
containing the factors and the challenges are not based on the survey conducted on common
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Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
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respondents nor the two lists have any other common factors. The paper demonstrates the
methodology to lead to a better model compared to simply ranking the factors and converting
the values to a single score says using the sum of the weighted scores. Further research on
similar lines but with a common participating group of respondens will yield reliable results.
References
Alfares, H.K., and Duffuaa, S.O., 2008. Assigning cardinal weights in multi-criteria decision
making based on ordinal ranking. Journal of Multi-Criteria Decision Analysis, 15(5/6), 123-
133.
Alli, A.M., Winter, G. S. and May, D. L., 2007. Globalization: Its Effects. International
Business & Economics Research Journal, 6(1), 89-96.
Beamon, B. M., 1999. Measuring supply chain performance. International Journal of
Operations & Production Management, 19(3), 275 - 292.
Bhagwat, R. and Sharma, M. K., 2007. Performance measurement of supply chain
management: A balanced scorecard approach. Computers and Industrial Engineering, 53(1),
43-62.
Bhagwati, J., 2004. In Defense of Globalization. Oxford, New York: Oxford University Press.
Boyer, K., and Lewis, M., 2002. Competitive priorities: investigating the need for trade-offs
in operations strategy. Production and Operations Management. 11(1), 9-20.
Bratić, D., 2011. Achieving a Competitive Advantage by SCM. IBIMA Business Review
Journal. 1-13.
Brun, A., Salama, K. F. and Gerosa, M., 2009. Selecting performance measurement systems:
matching a supply chain's requirements. European Journal of Industrial Engineering, 3(3),
336 – 362.
Chan, F.T.S., 2003. Performance measurement in a supply chain. International Journal of
Advanced Manufacturing Technology. 21, 534-548.
Charan, P., Shankar, R. and Baisya, R., 2009. Modeling the barriers of supply chain
performance measurement system implementation in the Indian automobile supply chain.
International Journal of Logistics Systems and Management. 5(6), 614-630.
Chopra, S., and Meindl, P., 2007. Supply chain management. Upper Saddle River, N.J.:
Pearson Prentice Hall.
Gunasekaran, A. and Kobu, B., 2007. Performance measures and metrics in logistics and
supply chain management: a review of recent literature (1995–2004) for research and
applications, International Journal of Production Research. 45(12),
Gunasekaran, A. Patel, C. and Tirtiroglu, E., 2001. Performance measures and metrics in a
supply chain environment. International Journal of Operations & Production Management.
21 (1/2), 71 – 87.
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Social Sciences (GB15_Thai Conference) ISBN: 978-1-941505-22-9
Bangkok, Thailand, 20-22 February 2015 Paper ID: T596
12 www.globalbizresearch.org
Gorey, T., Jochim, M. and Norton, S. (2015). The challenges ahead for supply chains:
McKinsey Global Survey results. [online] Mckinsey.com. Available at:
http://www.mckinsey.com/insights/operations/the_challenges_ahead_for_supply_chains_mck
insey_global_survey_results [Accessed 12 Jan. 2015].
Huhns, M. N., and Stephens, L. M., 2001, Automating Supply Chains. IEEE Internet
Computing, 5(5), 92-95
Shepherd, C. and Günter, H., 2006. Measuring supply chain performance: current research
and future directions. International Journal of Productivity and Performance Management.
55(3/4), 242 - 258.
Sheila, C. L., 2004. Globalization and Belonging: The Politics of Identity in a Changing
World. Rowman & Littlefield, US.
Stewart, G., 1995. Supply chain performance benchmarking study reveals keys to supply
chain excellence. Logistics Information Management. 8, (2), 38-44.
Tan, K.C., Lyman, S.B., and Wisner, J.D., 2002. Supply Chain Management: A Strategic
Perspective. International Journal of Operations & Production Management. 22 (6),
614-633
Vachon, S., Halley, A., and Beaulieu, M. 2009. Aligning competitive priorities in the supply
chain: the role of interactions with suppliers. International Journal of Operations &
Production Management, 29(4), 322-340.
Ward, P., McCreery, J., Ritzman, L., and Sharma, D., 1998. Competitive Priorities in
Operations Management. Decision Sciences, 29(4), 1035-1046.
Wong, W. P. and Wong, K. Y., 2007. Supply chain performance measurement system using
DEA modeling. Industrial Management & Data Systems. 107(3), 361 - 381.
Wong, W. P., Jaruphongsa, W. and Lee, L. H. (2008). Supply chain performance
measurement system: a montecarlo DEA-based approach. International Journal of Industrial
and Systems Engineering, 3 (2), 162 – 188.
Xu, L. X. X., Bin, M., and Lim, R. (2007). AHP Based supply chain performance
measurement system. In: IEEE Conference on Emerging Technologies and Factory
Automation, 25-28 September, Patras, Greece. pp. 1308-1315.