International Journal of Information Management 34 (2014) 634–638
Contents lists available at ScienceDirect
International Journal of Information Management
journal homepage: www.elsevier.com/locate/ijinfomgt
Analytical hierarchy process and SCOR model to support supply chain
re-design
Jaime A. Palma-Mendoza ∗
Department of Industrial Engineering and Operations, Instituto Tecnologico Autonomo de Mexico, Rio Hondo No. 1 Col. Progreso Tizapan, Mexico D.F.,
01080 Mexico City, Mexico
a r t i c l e
i n f o
Article history:
Available online 28 June 2014
Keywords:
Supply chain integration
SCOR model
Analytic hierarchy process
Supply chain re-design
a b s t r a c t
A supply chain consists of different processes and when conducting supply chain re-design is necessary
to identify the relevant processes and select a target for re-design. Through a literature review a solution
is presented here to identify first the relevant processes using the Supply Chain Operations Reference
(SCOR) model, then to use Analytical Hierarchy Process (AHP) analysis for target process selection. AHP
can aid in deciding which supply chain processes are better candidates to re-design in light of predefined
criteria.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
The necessity to coordinate several business partners, internal
corporate departments, business processes and diverse customers
across the supply chain gave rise to the field of Supply Chain
Management (SCM), (Turban, King, Lee, Liang, & Turban, 2011). At
the core of gaining competitive advantage through SCM is Supply
Chain Integration (SCI); when integration is achieved, the supply chain operates as a single entity driven directly by customer
demand (Farhoomand, 2005). However the supply chain literature shows the existence of a number of challenges associated to
the integration of supply chains (Awad & Nassar, 2010; Bagchi &
Skjoett-Larsen, 2005; Sweeney, 2011). In search for solutions which
can facilitate the construction of SCI, companies have turned their
attention to e-business technologies (Auramo, Aminoff, & Punakavi,
2002; Cagliano, Caniato, & Spina, 2003; Chen & Holsapple, 2012;
Wiengarten, Humphreys, McKittrick, & Fynes, 2013). Nevertheless evidence in the e-business and supply chain literature shows
only a limited adoption of e-business for SCI, (Auramo et al., 2002;
Bagchi & Skjoett-Larsen, 2005; Chen & Holsapple, 2012; Croom,
2005). This lack of adoption highlights the existence of challenges
in the application of e-business to enable SCI. New internet based ecollaboration tools allow the integration of multiple organizations,
making it feasible to construct SCI systems. However, tools alone
are not sufficient; it is necessary to undertake organizational and
technological changes together with a co-alignment in structure,
management processes, strategy, technology and individuals/roles
∗ Tel.: +52 55 56284000x3683.
E-mail address: Jaime.palma@itam.mx
http://dx.doi.org/10.1016/j.ijinfomgt.2014.06.002
0268-4012/© 2014 Elsevier Ltd. All rights reserved.
for successful e-business adoption (Chen & Ching, 2002). At the
core of organizational changes from an operational point of view
are business processes; when e-business technologies are implemented the business processes should be re-designed to support
the new technology (Gunasekaran & Ngai, 2004). However to redesign supply chain processes to support SCI implementation is
difficult (Palma-Mendoza, Neailey, & Roy, 2014). The increase of
complexity in business processes in supply chains results in the
need for new methodologies to handle this complexity; in particular, on how to integrate process information in enterprise networks
(Roder & Tibken, 2006). Accordingly building on a literature review
conducted in three different domains – business process design,
supply chain re-design, and e-business process design – a methodology is proposed to re-design business processes to support SCI
(Fig. 1).
One of the critical steps in this methodology is the identification
of relevant supply chain processes and selection of a target process
for re-design (step 3). A supply chain re-design can achieve radical
improvement but can also be risky if it is not focused on the appropriate process; thus, if supply chain process re-design is going to
take place, it is better to focus on a target process (Ashayeri, Keij, &
Broker, 1998).
A solution is proposed here to use the Supply Chain Operations
Reference (SCOR) model (SCC, 2012) for the identification of relevant supply chain processes and Analytical Hierarchy Process (AHP)
(Saaty & Vargas, 2012), for the selection of a target for redesign.
This paper starts with a review of the literature on the identification of relevant processes and selection of a target for redesign. Next
is presented the proposal of using SCOR model to identify relevant
processes and SCOR model performance attributes and metrics as
evaluation criteria to conduct an AHP analysis for the selection of
J.A. Palma-Mendoza / International Journal of Information Management 34 (2014) 634–638
635
chain. Finally Bolstorff and Rosenbaum (2012) propose to use the
SCOR model to capture the AS-IS (current status) of a supply chain
under study. The Supply Chain Council (SCC) developed the SCOR
model in 1996 to understand, describe and evaluate supply chains
[9]. The SCOR model provides a common supply chain framework,
standard terminology, common metrics and best practices (Huan,
Sheoran, & Wang, 2004). One of the applications of the SCOR model
is to aid the understanding of a particular supply chain by means of
mapping it in business process terms using SCOR model terminology (Wang et al., 2010). Thus, mapping with SCOR model will show
the relevant SC processes present in the particular supply chain
under study.
In respect to the selection of a key process target for redesign,
the Cardiff supply chain modelling and reengineering methodology (Towil, 1996) does not mention how to select a key process
for redesign. Bolstorff and Rosenbaum (2012) propose the use of
a worksheet to conduct an assessment of the impact and effort
necessary to re-design the different relevant processes identified.
The result from this assessment will be an impact/effort matrix
showing the different processes according to their potential impact
if redesigned and the effort necessary in time and money. The
main drawbacks with this approach are the difficulties associated
with producing a good estimate of cost and time necessary to redesign a particular process before conducting a complete analysis
of the relevant processes. Changchien and Shen (2002) propose a
Core Process Analysis Matrix (CPAM). CPAM needs a set of criteria to be defined in order to select a target process for re-design.
Changchien and Shen (2002) suggest using four views; strategic,
function, logistics-transportation and information management
views. A number of authors propose to use AHP to identify and
select target processes (Hahm & Lee, 1994; Korpela, Lehmusvaara,
& Tuominen, 2001). In summary, it is clear that for the selection of
a target for redesign, it is necessary to define a set of criteria, and
then perform a comparison among the processes identified against
the criteria. From the methods reviewed, multi-criteria decision
analysis appears the most adequate in particular when it can be
combined with SCOR model to establish a standard criteria for
comparison (Huan et al., 2004; Rabelo, Eskandari, Shaalan, & Helal,
2007).
3. Identification of relevant supply chain processes
Fig. 1. Business process re-design methodology to support supply chain integration.
Source: Palma-Mendoza et al. (2014).
a target for redesign. The model was tested through application in
an Airline MRO supply chain, showing this proposal can guide the
identification of relevant supply chain processes and the selection
of a target for re-design. Finally, this paper concludes with some
final reflections and implications in the use of SCOR model and AHP
for supply chain redesign.
2. Supply chain re-design
A number of methodologies have been proposed in the literature
to support supply chain re-design (Bolstorff & Rosenbaum, 2012;
Changchien & Shen, 2002; Towil, 1996; Wang, Chan, & Pauleen,
2010).
Changchien and Shen (2002) identify seven general relevant supply chain processes as defined by the International
Centre for Competitive Excellence (customer relationship, customer service, demand, order fulfilment, manufacturing flow,
procurement and development and commercialization); with these
processes Changchien and Shen (2002) propose to describe a supply
The Supply Chain Council (SCC) developed the SCOR model
in 1996, to understand, describe and evaluate supply chains. It
provides a common framework, standard terminology, common
metrics, and best practices (Huan et al., 2004). The SCOR model
follows a hierarchical structure with different levels of decomposition. The basic hierarchical composition of the SCOR model is as
follows:
• SCOR model Level I Process types: Level 1 defines scope and content using five process types: Plan, Source, Make, Delivery and
Return.
• SCOR model Level II Process categories: This level defines configuration level, where a supply chain can be defined using core
process categories.
• SCOR model Level III Process activities: This level decompose
processes in process elements, describing inputs and outputs,
process performance metrics and recommended best practices.
The SCOR model aids the understanding of a particular supply
chain by means of mapping it in business process terms. Accordingly, SCOR model levels I (process types) and II (process categories)
can be used to identify and map the supply chain processes present.
The mapping process starts at level I by identifying the process
636
J.A. Palma-Mendoza / International Journal of Information Management 34 (2014) 634–638
Fig. 2. AHP structure for selection of a target supply chain process for re-design.
Source: Palma-Mendoza et al. (2014).
types present in the supply chain under study, provided that the
scope of the study was defined beforehand as described in stages
1 and 2 (Fig. 1) of the BPR methodology (Palma-Mendoza et al.,
2014). Once the adequate process types have been selected, it is
necessary to select which configuration better describes the supply chain processes present. For the execution processes (Make,
Source, and Deliver) there are three main configurations: to stock,
to order, and engineer to order, with an additional configuration
for deliver, which is retail delivery. For the Plan process there are
four configurations: plan source, plan make, plan deliver and plan
supply chain. The return process has two elements: return deliver
and return source, and both of these have three process categories:
return excess product, return Maintenance, Repair and Overhaul
(MRO) product, and return defective product. Validation of the
SCOR model structure and supply chain processes relationships was
provided by a large empirical research conducted by Zhou, Benton,
Schilling, and Milligan (2011). Definitions and description of each
process configuration are available in SCOR model version 11 (SCC,
2012).
4. Selection of key supply chain process for re-design
Some processes in a supply chain are more critical than others (Palma-Mendoza et al., 2014). Thus, in order to differentiate
the degree of importance among several supply chain processes
it is proposed to use multi-criteria decision analysis such as AHP
as a decision support tool for process selection (Palma-Mendoza
et al., 2014). AHP assumes that decision problems can be structured by translating goals into measurable criteria, which, in turn,
can be related to alternative decisions. As result, AHP provides a
priority number at each level of the hierarchy; then priorities of
the alternatives are weighted against those of the criteria so that
the eventual importance of the alternatives related to the goal are
quantified (Saaty & Vargas, 2012).
AHP decomposes a complex problem into a multi-level hierarchical structure of objectives, decision criteria, and alternatives
(Huan et al., 2004). The AHP structure proposed for the selection
of a key supply chain process for re-design consists of a two level
criteria composed by SCOR model performance attributes and level
1 metrics (Fig. 2) as first reported in Palma-Mendoza et al. (2014).
At the top of Fig. 2 is the overall objective, in this case the selection of a target for re-design. The next two levels are the criteria,
here consisting of SCOR model performance attributes and level 1
metrics. Below are the decision alternatives, here represented by
relevant supply chain processes previously identified through SCOR
model mapping.
In the SCOR model, performance attributes serve to define
generic supply chain characteristics and to describe supply chain
strategy. According to SCOR model ver.11 performance attributes
are
•
•
•
•
•
Reliability
Responsiveness
Agility
Supply Chain Cost
Asset management
SCOR model metrics are organized around the performance
attributes and possess different hierarchical levels, similarly to
SCOR processes. Fig. 3 shows how level 1 metrics relate to performance attributes. SCOR model level 1 metrics are considered to be
Key Performance Indicators (KPI) intended to measure and express
the overall performance of a particular performance attribute. The
other metrics levels are considered diagnostic measurements associated with particular process activities (SCOR model Level III).
Considering that the identification of relevant processes will use
only SCOR model Level I and II processes, the AHP structure proposed for the selection of a target process uses only performance
attributes and level 1 metrics (Fig. 2).
Based on the SCOR model version 11, level 1 metrics are:
•
•
•
•
•
Perfect order fulfilment
Order fulfilment cycle
Upside supply chain flexibility
Upside supply chain adaptability
Supply chain management cost
J.A. Palma-Mendoza / International Journal of Information Management 34 (2014) 634–638
637
Fig. 3. SCOR model performance attributes and 1st level metrics.
Source: SCC (2012).
•
•
•
•
Cost of goods sold
Cash-to-cash cycle time
Return on supply chain fixed assets
Return on working capital
Detailed description of performance attributes and level 1
metrics is found in SCOR model version 11 (SCC, 2012).
At the bottom of the AHP structure (Fig. 2) are the relevant supply chain processes, which will be identified through SCOR model
mapping. These relevant processes will be compared using the
two level criteria (SCOR model performance attributes and level
1 metrics). In respect to how relevant supply chain processes will
relate to the two level criteria, SCOR model assigns for each process
category (SCOR model level II) different level 1 metrics (SCC, 2012).
Once the structure is constructed, the AHP analysis for the identification of a target for re-design will follow the next steps (Satty
& Vargas, 2012):
1. Pair-wise comparison: Pair wise comparison aims at determining the relative importance of the elements in each level
of the hierarchy starting from the second level (performance
attributes) and ending at the lowest level (supply chain processes). The decision maker expresses his/her preferences for
each pair of elements.
2. Weight calculation: Mathematical normalization methods are
used to calculate the priority vector from a comparison matrix
constructed from the pair-wise comparisons. This priority vector
shows the total relative weights among the criteria compared.
3. Consistency check: A consistency ratio is calculated to check for
consistency in making the pair-wise comparisons.
4. Hierarchical synthesis: The calculated priority vectors at different levels are integrated to allow overall evaluation of the
alternatives (supply chain processes).
5. Determine priority for all alternatives: The alternative (supply
chain process) with the highest overall priority weight is chosen.
In the end the AHP analysis will provide a priority numerical
order for the supply chain processes under consideration. From this
priority numerical order it should be easy to decide on which supply
chain process to focus the re-design effort.
One of the criticisms to the AHP is the process of selecting
the set of criteria and the way the AHP is structured (Ishizaka &
Labib, 2009). However, an advantage of combining the SCOR model
with the AHP is that the SCOR model provides a standard and
accepted structure of supply chain metrics as a criterion for the
selection of a target for redesign. Moreover using SCOR metrics will
potentially facilitate the evaluation process considering that managers involved will be familiar with this set of metrics. Furthermore,
managers involved will be able to utilize their experiences in the
selection of the target for redesign.
Another criticism is the rank reversal phenomenon: if a copy
(Belton and Gear, 1983) or a near copy (Dyer, 1990) of an alternative is added or removed, (Troutt, 1988) a rank reversal may appear.
This phenomenon has been explained in that the alternatives
depend on what alternatives are considered; thus, adding or deleting alternatives can lead to a change in rank (Harker & Vargas,
1990). However, if we are in a closed system (that is, no alternative will be added or removed) then the rank reversal phenomenon
will not appear (Ishizaka & Labib, 2009). Huan et al. (2004) states
clearly that the combination of AHP and SCOR model metrics will
not cause rank reversal since the set of criteria does not change;
thus, there are no multiple choices to cause rank reversal.
Finally, another criticism of the AHP is that the uncertainty associated with subjective judgemental errors may affect the rank order
of decision alternatives (Rabelo et al., 2007). Thus, the measure of
consistency can be used to improve the consistency of judgements
(Saaty & Vargas, 2012). If the consistency ration is less than 10%,
then the pairwise comparison matrix can be considered as having
an acceptable consistency; otherwise the judgements need to be
checked.
5. Conclusions
Despite the need to re-design supply chain processes to support
supply chain integration there is a lack of an adequate methodological framework to guide its implementation (Palma-Mendoza
et al., 2014). In particular, it is not clear from the available methodologies how to identify relevant supply chain processes and select
a target for re-design. From a literature review a solution has been
developed to tackle this problem. First it is recommended to use
SCOR model to map a supply chain under study, this will reveal the
relevant supply chain processes present. The SCOR model, has been
widely accepted by supply chain practitioners and researchers and
has been proven to be valid (Zhou et al., 2011). Next, here it is recommended to use the AHP analysis combined with the SCOR model
to conduct the selection of a target for re-design. The AHP hierarchical structure follows the natural tendency of the human mind
to sort elements of a system into different levels and group similar
elements at each level (Huan et al., 2004). This structured approach
facilitates decision making. The SCOR model is a hierarchical model
that consists of different process and metric levels; thus, it seems
natural to combine the AHP with the SCOR model (Li, Su, & Chen,
638
J.A. Palma-Mendoza / International Journal of Information Management 34 (2014) 634–638
2011). Although AHP still suffers some criticisms such as the rank
reversal phenomenon, as previously explained, this is unlikely to
affect the proposed AHP structure for the selection of a target for
re-design.
Finally, results provided by the AHP analysis go beyond target
process selection. From the AHP analysis, it is possible to calculate
a priority rank for the metric criteria used; thus, making it possible
to identify the most important SCOR metrics associated with the
target for re-design. Identification of these relevant metrics will be
the starting point for the definition of objectives for improvement
(Palma-Mendoza et al., 2014).
Acknowledgement
The author Jaime A. Palma gratefully expresses its gratitude to
Asociacion Mexicana de Cultura A.C for its support during the elaboration of this article.
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Jaime Palma joined Warwick Manufacturing Group (WMG) at the University
of Warwick 6 years ago as a research engineer on the Engineering Doctorate
programme. His doctoral research consisted in the creation, development and
application of a Business Process Redesign Methodology to support e-business
implementation for Supply Chain Integration. He was awarded the Doctor of Engineering degree in 2011 and since July 2012 is an Associate professor at Instituto
Tecnologico Autonomo de Mexico (ITAM).