Supply Chain Efficiency Model

WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Journal of Logistics & Supply Chain

MAY 2013 VOL.1, No,3

Supply Chain Efficiency Evaluation: A Contemporary
Theoretical Model

Janvier-James Assey Mbang
Glorious Sun School of Business & Management,Donghua University
P.O.box: 200051, 1882 West Yan an road, Shanghai, China

Accepted 2 May 2013

Abstract
Supply chain management has gained a prodigious amount of attention from both practitioners and
industries since the last decade. Until now, there are many articles, and dissertations that address
supply chain management, but there is still a lack of integration between the current efficiency
evaluation methods and practical requisites for the supply chain management. A contemporary
efficiency evaluation method is proposed to provide necessary support for efficiency improvement in
supply chain management. The proposed method will address this aim in the following main aspects: a
basic supply chain model; concrete and unconcrete efficiency measurement in various dimensions; a
cross-organizational efficiency evaluation; and weighted average and fuzzy set theory method.
Keywords: Supply chain, Efficiency evaluations, Theoretical Model

1. Introduction
In contemporary business environments, producers face high pressure of customers' requirements
in goods quality amelioration, customization, and demand responsiveness. In consideration of
supporting the business under these pressures, many companies are striving to develop long-term
collaborations with a few adequate suppliers and cooperate with them in inventory control and product
development. Furthermore, the high competitive requirements of customer responsiveness and cost
efficiency have encouraged companies to pursue strategic partnership with suppliers, downstream
customers to exploit their competences and create new value to end consumers. This alliance is known
as supply chain and the control, organizing and planning of the supply chain activities is called supply
chain management
Even though supply chain management has become common practice across all enterprises, and
many papers related to theories and practices of supply chain management have been published, the
topic of efficiency evaluation of supply chain management does not receive enough attention therein
(Gunasekaran, A., Patel, C. and Tirtiroglu, E.,2001; Mithun J. Sharma and Song Jin Yu,2010). As a
fundamental management tool, efficiency evaluation provides the necessary support for efficiency
improvement in pursuit of supply chain superiority. However, many critical deficiencies pervert the
current efficiency measurement systems from making important contribution to the development of
supply chain management. With the purpose to fill this gap, the present paper attempts to propose a
contemporary efficiency evaluation method for supply chain.
Efficiency evaluation is an important element of effective control and decision making, as well as
planning It can provide essential feedback information to disclose progress, augment communication
and motivation, and identify problems (Waggoner, D.B., Neely, A.D. and Kennerley, M.P., 1999;Amos
Sola Ogunsiji and Oluwatosin Oba Ogunsiji,2011). In supply chain management context, efficiency
evaluation can further ease integration among the supply chain members. The evaluation results
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disclose the effects of potential opportunities strategies in supply chain management. There are many
articles and papers that have addressed efficiency evaluation in supply chain management. Beamon
Martin (1999), Jian Cai, Xiangdong Liu, Zhihui Xiao,Jin Liu (2009) identifie the following measures:
flexibility, output, and resources. Gunasekaran, A., Patel, C. and Tirtiroglu, E.. (2001) develop a model
for evaluating the efficiencies from, operational, tactical, and strategic levels in supply chains; this
model principally concerns supplier, delivery, inventory and logistics costs, and customer service.
In spite of the importance of efficiency evaluation, there is very little literature available for
efficiency evaluation of supply chain management, especially that deals with measures selection and
system design (Beamon, 1999; Jian Cai, Xiangdong Liu, Zhihui Xiao,Jin Liu,2009). The contributions
of the efficiency evaluation in use are lowered by existence of many imperfections in supply chain
management context. Classic finance-based efficiency measurement has already received wide
judgment on short-term profit orientation, stimulating local optimization, thus failing to support
constant improvement. In addition, efficiency evaluations in supply chain context are also associated
with many problems, as asserted below (Gunasekaran, A., Patel, C. and Tirtiroglu, E., 2001, Asghar
Sabbaghi and Ganesh Vaidyanathan ,2008):
being not linked with adequate strategy;
being lack of equalized approach to integrating non-financial and financial measures;
being lack of system thinking, in which a supply chain must be perceived as one whole entity,
and
being loss of supply chain context, and thus stimulating local optimization.
With these imperfections above-mentioned, an effective efficiency evaluation method has always
been under considerable discussion, and necessitates further research investigation.
This paper is organized as following: this part is the preliminary part to supply chain management and
efficiency measurements in supply chain management. Part two is literature review. Part three
introduces the proposed efficiency evaluation method. Part four is conclusion.
2. Literature review
Supply chain collaboration helps in strengthening the customer responsiveness, increase of
flexibility for changing market conditions, amelioration of customer service, and also benefits to retain
customers. The primary initiative of supply chain integration could be antedated to 1992, when
fourteen trade association sponsors created the Efficient Consumer Response (ECR) group (Robins,
1994; Barratt and Oliveira, 2001; Ursula Y. Alvarado and Herbert Kotzab ,2001). Then in 1995, five
enterprises: the Warner-Lambert, Wal-Mart Stores, Manaugistics, and SAP worked on the
Collaborative Planning, Forecasting and Replenishment project. The objectives of the project were to
ameliorate the business (Cooke, 1998; Felix TS Chan & SH Chung,2004). Collaborative Planning,
Forecasting and Replenishment attempted to bring organizations (manufacturers and retailers) together
to make collaborative planning, encompassing promotion sales, purchasing, logistics planning, and
replenishment. Blair, N. (1998) and Mark Powell, Paul Childerhouse (2010).asserted that
Collaborative Planning, Forecasting and Replenishment had won the support of organizations in the
grocery, general commodities, and clothing industries.
Practitioners in supply chain management are many. Barratt, M. and Oliveria, A. (2001) and
Margaret L. Sheng (2006) pointed out that two important bottlenecks encountered in implementation
of supply chain integration were the lack of perceptibility of real customer demand, and the joint
relationships in the area involved collaborative decision making. New, S. and Ramsay, J. (1997) also
asserted that there was a danger of arbitrary costs’ distribution and advantages in practice. This is due
to the inequality of power between different organizations. Neuman, J. and Samuels, C. (1996)
suggested that adequately sharing the benefits from the supply chain was important. Pfohl,
Hans.Christian. and Buse, H.P. (2001) had interrogated that what type of organization, in the supply
chain, should be the fundamental decision maker to decide all of the operation and coordination
decisions. Stank, T.P., Daugherty, P.J. and Autry, C.W. (1999) demonstrated that there was a vigorous
support in using automatic inventory replenishment in cross-organizational partnership.

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2.1 Supply chain efficiency measures
Anderson, P., Aronson, H. and Storhagen, N.G. (1989) pointed out that, in evaluating logistics
efficiency, a strategy of evaluation is necessary for the successful realization, management and planning
of the different activities, which include the business logistics function. Thor, C.G. (1994) asserted that
there should be a group of measures. This is a collection of four to six efficiency measurements, generally
encompassing quality, productivity, and customer satisfaction, which, together, provide an all-embracing
view of results but also provide a characteristic value. Stainer, Alan (1997) pointed out that an efficiency
measure is used to determine the efficiency and effectiveness of a current system. Efficiency
measurements are also used to design proposed systems, by determining the values of the decision
variables that grant the most judicious level of efficiency. Generally, efficiency measurements can be
categorized as quantitative and qualitative in nature.
2.1.1 Quantitative efficiency measurements
Quantitative efficiency measurements are those measures that may be straightforwardly depicted
numerically. Quantitative supply chain efficiency measurements may be classified by goals that are based
on profit or cost, productivity, and customer responsiveness’ measures. Since quantitative measurements
are something that can be depicted and managed easily, any qualitative measurements should be
interpreted into quantitative measurements. Some illustrations of quantitative efficiency measurements
are as follows:
Measurements based on cost
Cost reduction: Cost is generally reduced for a whole supply chain. For instance transportation cost
reduction.
Sales increase: Increase the amount of sales dollars.
Profit increase:Increase revenues less costs
Inventory investment reduction: Reduce the amount of inventory costs so minimization of the inventory
level is necessary.
Return on investment increase: Increase the ratio of net profit to capital that was used to produce that
profit.
Measurements based on customer responsiveness:
Fill rate increase: Increase the portion of customer orders filled on time.
Product lateness reduction: Reduce the amount of time between the agreed goods delivery date and the
current goods delivery date.
Customer response time reduction: Reduce the amount of time required from the time an order is placed
until the time the order is received by the client, such as order lead time.
Lead time reduction: Reduce the time that is required from the time an order has started its production
until the time the order is ready for shipment.
Function duplication reduction: Reduce the volume of business functions that are provided by more than
one business entity.
Measurements based on productivity:
Capacity utilization increase: Increase the capacity utilization.
Resources utilization increase: Increase the resources utilization.
2.1.2 Qualitative efficiency measurements
Qualitative efficiency measurements are those measurements for which there is no direct numerical
measure, although some aspects of them may be measured. For instance:
Consumer satisfaction: The extent e to which consumers are satisfied with the goods and service received,
and can be applied to external consumers and internal consumers. Consumer satisfaction mainly includes
three components: pre-transaction satisfaction, transaction-satisfaction, and post-transaction satisfaction.
Flexibility: The extent to which the supply chain can respond to fluctuation in the demand pattern.
Material flow and information integration: The extent to which functions within the supply chain can
pass transport materials and information easily.
Effective risk management: The relations within the supply chain include inherent risk. Effective
risk management depicts the extent to which the influence of these risks is reduced.
Supplier efficiency: A measure to depict how good a supplier can deliver raw materials to manufacturing
facilities in good conditions and on time.
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3. A contemporary efficiency evaluation method
In consideration of solving the above- mentioned problem, a contemporary efficiency evaluations method
is presented in this paper. The proposed method is a model that uses fuzzy-set theory to assess the
integrated efficiency of compound supply chain. Fuzzy set theory is generally employed to address the real
situation in measurement and judgment processes. It can deal with uncertain information to help decision
making. The measurement’s procedure is very simple: after choosing the adequate efficiency
measurements as mentioned above, data should be collected for examination. The efficiency measurements
are weighted by determining the normalized importance weight through a geometric scale of triangular
fuzzy number. Then, fuzzy efficiency grade is defined to determine the fuzzy evaluation result and an
efficiency score can be estimated. In conclusion, the evaluation results can be defuzzified to an efficiency
index, which can be used to show the efficiency of the system under evaluation.
3.1 Process-based model and System-thinking view
The goal of supply chain management is to create the most value, not only for some enterprises,
but for the entire supply chain network, even encompassing the end consumers. In this context,
favorable supply chain evaluation systems do more than just concentrate on partial areas, but rather
look across the entire network. This paper proposes that an integrated system-thinking view is used to
suit the essence of supply chain management, in which the supply chain efficiencies should be
evaluated beyond the classic boundaries of organizations and functions. Then, an efficiency evaluation
system that bridges the key business aspects will facilitate seamless integration and global
optimization of supply chain efficiencies.
It is difficult to control supply chains than just to define it. A supply chain is an inter-connected
network of various members and complex relationships (Lambert, D.M., Cooper, M.C. and Pagh, J.D.,
1998). It is common that, in practice, a company participates in many supply chain, and a company
has not all its divisions and functions involved in one supply chain with the same integration. This
complexity also confuses efficiency evaluation of supply chains, and then requires building an
effective model to facilitate the examination and evaluation of supply chain management.
This research attempts to build a process-based method to facilitate the practical supply chains
from their commonalities and essence. In general, a process is a set of activities designed to perform
particular functions and generate particular outputs. In this model, a process refers to a series of
activities from original producers and suppliers till retailers add value for the end consumers. The core
business processes, which are of critical importance to corporate strategies and goals, are proposed to
identify and enclose herein as the framework of this efficiency evaluation systems. For any supply
chain, the basic structure and processes can be described as indicated in figure 1, in which six core
processes are connected.
The key processes identified can be further classified into activities and sub-processes to address
their efficiencies. For instance, the inbound logistics can be classified into such sub-processes as
purchasing, transportation, supply base management. These key processes and sub-processes consist
of a hierarchy of supply chain model, which is the model of the proposed efficiency evaluation
systems.
This efficiency evaluation method is based on the process model of the supply chain, so the
measurements can be formulated from process efficiency.
Any process employs particular company resources, achieves the planned objectives and
functions, and then adds value to goods that are delivered to end consumers. The consumed resources,
and planned operations are the important efficiency of processes. Power, Time, capital, labor facilities,
and information are generally the resources that processes employ. Generally, they can be evaluated in
terms of their amount per output unit. The efficiency on expected outcomes and operations can be
evaluated according to their planned operations. For instance, purchasing process is principally
responsible for material replenishment and supply base management. Thus it can be assessed from
such efficiency as quality and reliability of material replenishment, and supplier-purchaser relationship.
Reliability in transportation and delivery, and flexibility in production, material supply, and order
delivery have received more attention in efficiency evaluation of supply chains.
For each process and its sub-processes that need to be evaluated, the corresponding measurements are
identified and classified into the processes and measurements hierarchy. This composes the framework
64


of the efficiency evaluation systems.
For each process and its sub-processes that need to be assessed, the corresponding measurements are
identified and classified into the processes and measurements hierarchy (figure 2)

Figure1: Supply chain flow chart

Figure 2: Generic design of the PMH
3.2 Relevant efficiency measurements
These efficiencies should include such areas as those:
 of important concern to supply chain current objectives and strategies;
 of inter-influence and of current concern among the supply chain collaborators; and concerned
by both internal collaborators and external customers.
3.3 Efficiency evaluation teamwork
In this paper, an efficiency evaluation team is proposed. This efficiency evaluation team is composed of the
representatives from different areas of the supply chain, which can be department directors, plant managers,
and process supervisors. The members of efficiency evaluation team serve principally as the appraisers, and
provide point of views for each efficiency. They come from different management areas and have wide
experiences, and thus can cover a wide range of perspectives. Concurrently, the weights of their point of
views are not necessarily the same. When combining their point of views, the weights will be assigned.
There are varieties of ways to determine the weights; for instance, by the supply chain’s top officials, or
balancing the opinions of efficiency evaluation team members.
3.4 The innovative evaluation algorithm
This part is devoted to describe the evaluation algorithm and application of evaluation results. The
data that indicate different efficiencies are compared against the evaluation scales that are set by the
efficiency evaluation team through measuring the corresponding efficiency objectives and operation
environments. An efficiency grade in forms of fuzzy set is acquired to indicate the result of each efficiency
measurement. The measurement results of different measurements by each efficiency evaluation team
member are integrated with the weighted averaging aggregation method. The aggregated results are
defuzzified and employed to measure the supply chain efficiency impartially.
3.4.1 Measure and processes’ relative weights
Considering the changing goals and strategies of supply chains, the prerogatives of individual
65


processes and their different dimensions of efficiency should diverge from each other in efficiency
measurement. Therefore, it is necessary to set relative weights for them to aggregate the evaluation results.
General scale of comparison ratio with crisp numbers fails to address the fuzziness. Until now, many
literatures have suggested new applications by using fuzzy set theory. This research proposes a
mathematic scale of triangular fuzzy numbers (Boender Boender, C.G.E., de Graan, J.G. and Lootsma,
F.A.., 1989).
3.4.2 Fuzzy efficiency grade and measurement scale
After obtaining the relative weights of each efficiency measurements, it is still absurd to measure any
efficiency without its related context about histories and goals. Furthermore, the current evaluation
methods, in which the current efficiency are assessed through being divided by the expectations, have
such imperfections as ignoring operation context, and losing the critical information arising from the
ambiguity of human judgment (Zadeh, Lotfi Asker (1965)). This research creates a fuzzy efficiency
grade and measurement scale to address these issues.
When assessing efficiency, the appraisers of the efficiency evaluation team consider the planned
history and objective, as well as the related operation environments, and then set the measurement scale in
forms of the interval, varying from the agreeable bottom of efficiency to the completely satisfactory
efficiency. The effect of the supply chain context and associated operation environment being measured
and taken into account, the agreeable bottom and completely satisfactory efficiency are not inevitably
same to efficiency objective and history, respectively.
The measurement scales’ judgment process includes fuzziness as well. Accordingly, the measurement
results are acquired and denoted by fuzzy numbers through the following steps: first, comparing current
efficiency against their measure scales, and then indicating with the crisp numbers varying from 0 to 10
as script marking method does; second, codifying the acquired crisp number into fuzzy efficiency grade
. These 6 grades
set. The efficiency set in the form of a fuzzy vector
indicate the gradational measure results varying from the excellent to the worst. The
triangular fuzzy numbers defines these grades following:

in the finite universe of discourse
is
This efficiency grade set
defined by a set of ordered pairs as following:
Where
a mapping is named “the membership function of the fuzzy set G”, and
shows the extent of belongingness. is the crisp number in comparison of current efficiency against
measurement scales.
3.4.3 Defuzzi6fing and aggregating the measure results
In evaluation activity, the point of views of all the appraisers in the efficiency evaluation team are
required to integrate; in order to get the general picture of one process the measure results of
individual measurements and its sub-processes are necessary to integrate as well. As annotated above,
due to the various backgrounds in different areas, the point of views of the appraisers from diverging
areas should be given distinct weights. The relative weights of different efficiency measurements and
sub-processes can be deduced from the changing supply chain strategies and objectives.
Finally, these results are efficiency grades in forms of fuzzy sets .According to their definitions, these
efficiency grades that denote the measure results symbolize the connotations of approximation "about".
That is, these 6 grades denote "about 10", "about 8", and "about 0". In this connection, these efficiency
grades can be defuzzified into the crisp numbers from 10 to 0 through weighted averaging the grade
. The defuzzified crisp number (efficiency index), indicates the synthetic measurement of
set
the holistic efficiency of different areas of supply chains by the appraiser team.
3.5 The applications of the efficiency index
The efficiency index is a global, single, and integrated process efficiency score. According to the
design of this efficiency evaluation method, this integrated result is the weighted integrative
measurement of the entire supply chain process efficiency with the multi-dimensions. This number
provides a concise means to analyze and measure the efficiency in the supply chain systems for
their general managers. Put in the range [0, 10], this result can be measured. Because the evaluation
66


result of each process on the higher layer is aggregated from the evaluation results of sub-processes,
the bad results can be captured layer by layer in the PMH. Thus the proneness and strengths of supply
chain processes are identified. Furthermore, the parallel processes can be compared and the enigmatic
nodes can be found. Next, from a dynamic point, the efficiency of all the business processes of the
supply chain system can be measured and recorded on the base of a monthly period. With a series of
evaluation results at normal intervals, the trend of efficiency of each business process can be examined
and irregular efficiency can be disclosed clearly. This information can help corporate managers
identify the issues in the management of supply chain processes.
Example
In this part we propose an example to illustrate the evaluation method proposed above. Assume
cost is one of measurements in a supply chain network to show its efficiencies and there are 4
appraisers in the efficiency evaluation team with the relative weights.
WT = (0.10,0.20,0.25,0.45) of their corresponding points of views Note that
weights=1,as they
must normalized before putting into the equation above.
Firstly, one appraiser makes his judgment for the measure. Suppose that the efficiency history of
this cost is $22 per unite, and the efficiency goal requires this cost to be minimized to $19 per
unit .The appraiser first determines the measure scale of cost, to suppose which is the interval as [21,
19].Assume the current efficiency on production cost is average 19.45 per unit, according to the daily
operation records, the efficiency score and efficiency grades are estimated as following:
,
Efficiency score =
Efficiency grades:
PA (7.75) =0, PE (7.75) =0, PC (7.75) =0, PD (7.75) =
, PE (7.75) =
, PF= 0
Thus, the efficiency grade set can we formulated as follows:
PG= (7.75) =
)
Or
This is the evaluation result of cost that has been judged by the first appraiser. Assume the
efficiency grade sets by the other three appraisers, in form of row vector, to be as follows:

These vectors compose the fuzzy efficiency grade matrix as following:

=

Then the evaluation results of these four appraisers, with their corresponding weights are aggregated
as following:
.W

=

This vector shows the aggregated point of view of the evaluation of cost efficiency by the four
appraisers. It takes the form of fuzzy efficiency grade set.
The efficiency index is:

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Undoubtedly “7.13” is not a satisfactory index with respect to the 10- point scale. The supply chain
network should be refined in order to improve this efficiency measurements defined by appraisers, the
individual efficiency index can be estimated through the same procedures.
4. Conclusions
This research discloses the key problems in the current efficiency evaluation method in supply
chain management context. In order to support efficiency improvement in supply chain management,
this research proposes a cross-organizational efficiency evaluation method from a system view.
Process-based framework, relevant efficiency measurements, teamwork measurement, and fuzzy
evaluation algorithm are summarized, and some propositions are given. These designs support
integrated evaluation of the holistic efficiencies of supply chains. Particularly, the introduction of
fuzzy set theory in evaluating efficiencies is beneficial, because this fuzzy method addresses the actual
situation of human judgment with fuzziness in evaluation activity. The defuzzified results provide
facile access to benchmark the efficiencies.
The main contribution of the proposed approach is to provide a strong model to calculate an efficiency
e index of an efficiency evaluation in a supply chain network to deal with both intangible and tangible
and efficiency measurements. The model integrates fuzzy set theory, which can symbolize ambiguities
in real-life applications. This method can be used to replace a classical pair wise comparison technique
such as Analytic Hierarchy Process (Saaty, 1980). De facto, Saaty's pair wise comparison engenders
the asymmetrical scale of weight.
With the proposed efficiency evaluation method, supply chain managers can smoothly assess the
efficiencies of the entire system, and then analyze the efficiency of their strategies, and determine the
potential opportunities. This feedback information eases more decision making and efficiency
improvement in supply chain management.
To optimize the supply chain model, much efficiency evaluation should be considered. But, the
following important question should be answered first: how to combine all quantitative and qualitative
efficiency measurements to compose a significant figure to support decision making? In most cases,
two methods can be used for the measurement; especially, mathematical simulation and optimization.
Mathematical optimization methods encompass accurate algorithms that are settled to find an optimal
solution. Additionally, heuristic algorithms can be used to find good solutions, but not inevitably the
optimal solutions. Future research could consolidate all efficiency measurements through similar
algorithms so that a single efficiency index can be discovered to represent the entire network,
regardless of individual efficiency index.
Acknowledgements
The authors gratefully acknowledge the con-structive and helpful comments of two anonymous
referees on the earlier version of the manuscript.
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