Supply Chain Efficiency Evaluation: A Contemporary Theoretical Model

World Academic Journal of Business & Applied Sciences-Journal of Supply Chain Management-Vol.1 No.1 (2013)
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
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
International journal of
Supply Chain
Management
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Journal of Supply Chain Management (2013)

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 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.
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:
a. 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.
b. 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.
c. 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.
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 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 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 set. The efficiency set in the form of a fuzzy
vector . These 6 grades indicate the gradational measure results varying
from the excellent to the worst. The triangular fuzzy numbers defines these grades following:

This efficiency grade set in the finite universe of discourse is 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 set . The defuzzified crisp number
(efficiency index), indicates the synthetic measurement of 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 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.
4. 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:
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.
5. 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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