A SUPPLY CHAIN ONTOLOGY CONCEPTUALIZATION WITH
FOCUS ON PERFORMANCE EVALUATION
Alicia C. Böhm, Horacio P. Leone
Instituto de Desarrollo y Diseño, UTN – CONICET, Santa Fe, Argentina
Gabriela P. Henning
Instituto de Desarrollo Tecnológico para la Industria Química, UNL–CONICET, Santa Fe, Argentina
Keywords: Ontology, Supply Chain Management, Performance Evaluation, Metrics.
Abstract: Organizations all over the world are increasingly aligning in Supply Chains (SCs) in order to perform more
efficiently and to achieve better results. This contribution presents a SC ontology that aims at
conceptualizing and formalizing this domain knowledge. Its goal is to: a) enable a better understanding
among the various stakeholders & b) set the basis for an effective information sharing and the development
of integrations tools. The ontology introduces concepts associated with the SC structure, functions,
resources, and management issues. Since one key component of management is performance assessment,
which must be done along the whole SC, the proposed ontology focuses on performance evaluation issues.
1 INTRODUCTION
To efficiently operate a Supply Chain (SC), all its
participants (suppliers, manufacturers, distributors,
customers, third and fourth party logistics) must
have an enhanced and common understanding of it.
This allows to better communicate and to attain a
genuine integration of the activities executed by the
different functional areas and/or companies. This
challenge has motivated several research efforts that
addressed the development of models aimed at
describing the elements and processes associated
with a supply chain, as well as tackling specific SC
integration problems. Beamon (1998) presented a
review of the models that have been proposed for the
analysis and design of the SC. However, the only de
facto standard is the Supply Chain Operations
Reference (SCOR) model (SCOR, 2007). Although
this model is a good starting point for
communication among SC stakeholders, it provides
a slender modelling of processes, resources and the
relationships among them; so, its formalization
becomes a requirement for a more comprehensive
usage of the model.
Furthermore, performance evaluation is an
important supply chain management issue since it
provides significant information to make decisions
and to assess results. Thus, it can be seen as a basic
prerequisite for improvement.
In recent years, research on SC measurement has
increased significantly. This is reflected by the
growing number of contributions that have been
reported (Beamon, 1999; Brewer and Speh, 2000;
Lambert and Pohlen, 2001; Hausman, 2002;
Kleijnen and Smits, 2003; Gunasekaran et al., 2005;
Gaiardelli et al., 2007; Bhagwat and Sharma, 2007).
Nevertheless, most of these proposals do not
consider the fact that a measurement system may
involve different companies along the SC, and that
this issue could yield semantic problems when
information is shared by these distinct enterprises or
by different organizational areas.
Additionally, many contributions have put
forward several metrics, but their specification is
neither clear nor complete. Therefore, in most cases
it is difficult to distinguish what is supposed to be
measured and how measurements must be done. For
example, the metric identified as ‘Number of
stockouts’, proposed by Beamon (1999), is defined
as ‘Number of requested items that are out of stock’,
but it does not specify which period must be covered
(a week?, a month?, a year?), neither the ‘location’
where it must be measured (concerns a company?,
the whole supply chain?), nor the items being
402
C. Böhm A., P. Leone H. and P. Henning G. (2008).
A SUPPLY CHAIN ONTOLOGY CONCEPTUALIZATION WITH FOCUS ON PERFORMANCE EVALUATION.
In Proceedings of the Tenth International Conference on Enterprise Information Systems - ISAS, pages 402-409
DOI: 10.5220/0001718004020409
Copyright
c
 SciTePress

considered (all the products?, a product family?),
etc. Another relevant issue is that there are many
contributions which introduce valuable information
to help managers in the administration and operation
of an appraisal system. However, this matter is just
undertaken in different works in an isolated fashion
and using dissimilar terminology. In consequence,
there is a need to manage precise definitions; thus,
leading to a universal understanding of the SC
domain and measurement concepts, as well as a
proper interpretation of the shared information.
Considering all these challenges, this proposal
aims at contributing towards the formalization of the
SC domain and its evaluation system. Since
ontology-based models are expressive and minimize
interpretation ambiguities (Kim and Fox, 2002), the
goal of this paper is to propose an appropriate SC
ontology, named SCOntology. It provides a first
conceptualization of the SC structure, functions,
performance and management concepts. A special
emphasis is made on measurement and evaluation
aspects. Regarding this last issue, an ontology would
enable to make suitable comparisons, which
otherwise could not be done without interpreting the
relevant concepts in the same way.
In the next section the proposed ontology is
presented and an example on its application is
discussed. In section 3, conclusions are drawn.
2 SCOntology
2.1 Methodological Approach
The development of SCOntology was based on the
activities and construction life cycle recommended
by METHONTOLOGY (Fernández-López et al.,
1999). This methodology identifies specification,
conceptualization, formalization and implementation
activities as steps of the development process. In this
contribution, only the first two phases are addressed.
The specification entails the definition of the
ontology purpose, degree of granularity and scope.
In the conceptualization phase, the knowledge of the
domain is organized and structured using external
representations, which are independent of the
implementation languages and environments.
2.2 Specification
In order to specify the scope of the ontology, to
identify the set of relevant terms to be captured and
the relations among them, as well as to define the
characteristics and granularity of the relevant
concepts, a series of informal competency questions
were defined. Some of them are shown below.
1- Which organizations participate in a SC?
2- Which processes executed in a certain
organization are involved in a given SC?
3- How is a given process carried out? Which
activities are involved in its execution?
4- Which are the strategic, tactical and operational
goals of a SC?
5- How is a given goal monitored?
6- Which metrics can be used to assess the
performance of the SC from a customer/internal/
long term point of view?
7- What does a specific metric evaluate?
8- How is a certain metric calculated/computed?
9- Which temporal interval does a measure cover?
10- Which is the most recent measure of a certain
attribute of a given entity?
The most relevant terms to be represented are the
ones highlighted in bold.
The main knowledge sources for the ontology
development are the SCOR model (SCOR, 2007),
the Coordinates enterprise modelling language,
developed by Mannarino (2001), and the concepts
and ideas that resulted from a critical analysis of
other proposals on measurement systems.
The SCOR reference model is a general
framework proposed by the Supply Chain Council
that defines a language to represent the business
activities associated with all phases of satisfying a
customer's demand. In turn, the Coordinates
language allows representing enterprise processes
and their associated resources and products in an
integrated fashion, considering any type of possible
relations among them. It allows the analysis,
representation and comprehension of an enterprise in
terms of several dimensions.
2.3 Conceptualization
Many aspects need to be taken into account in a SC,
such as the network of participating organizations,
the different kinds of flows (material, information
and money), the several operational and
management strategies and practices, etc. Due to this
complexity, it is quite important to have mechanisms
to help analyzing this domain. Since all the domain
concepts cannot be included in just one view, the
proposed ontology considers the following
perspectives: structural, functional, performance and
management. This separation aims at clarifying the
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403

model; however, these different viewpoints are
interrelated, as they are part of the same ontology.
Figure 1 presents a UML diagram that includes
the different SCOntology views, their associated
concepts and relationships. Table 1 defines the main
concepts. The Entity concept is introduced in this
model in order to abstract any concrete or
conceptual thing of interest in the SC domain.
Nevertheless, this notion is specialized in SC Entity
and SC Information Entity. The former represents
the entities that are direct components of a SC,
which are related to the SC structural and functional
aspects, and the latter represents those entities
involved in the SC description (SC meta
information), which correspond to the SC
management and performance information views.
Management Concepts
Perf ormance Concepts
Functional Concepts
SC Structural Concepts
Value
Aggregation OP
Product
Process
Business
Process
Process
Element
Task
Complex
Tas k
Elementary
Task
Resource Perspective
Financial
Resource
Mat erial
Resource
SC
Entity
Entity
Responsiv eness
Reliability
Flexibility
Assets
Costs
Customer Facing
Long Term Facing
Internal Facing
Meas ure
value
timepoint
period
normalized
value
Metric Dependency
Increase Reduce
Strategic
Tac t ical
Operational
description
ty pe= {qualitativ e,
quantitativ e}
method
AggregationDisaggregation
Sub OU
0..n
SC
Mark et
Customer OP
1..n
1
0..n
1..n
0..n
Temporal
Relationship
Resource
0..1
0..n Associated HR
0..n
Asso
ciated
HR
Vertical Integration
1
1
0..1
Goal Component
0..n
Level
1..n
0..n
0..n
1..n
0..n
1
1
0..n
SC
Information
Entity
Performance
Dimens ion
1
Influenc e
1
IR Component
1.n
1..n
0..n
2..n
2..n
2..n
0..n
0..n
2..n
2..n
0..n
0..n
0..n
0..n
0..n
0..n
1
1..n
Related Goal
Related IR
name
responsable
Sub SC
Supply Chain
1
1
1
1
1
1
1
1
11
1
1
1
0..n
0..n
Organizational
Perspectiv e
Goal
description
Metric
definition
unit of measure
f requency
normalization
criteria
target
allowed tolerance
0..n
0..n
Performance
Attribute
Hierarchical
Relationship
Information
Resource
Organizational
Unit
{or}
{or}
Figure 1: SCOntology. UML diagram.
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Table 1: SCOntology. Main concepts description.
SCOntology
View
Concept Name Description
Business Process
A structure of activities designed for action with a focus on end customers and on the dynamic
management of flows involving products, information, cash, knowledge and/or ideas (Lambert et
al., 1998).
Financial Resource Money, credit, etc. associated with a Process.
Information Resource Information involved in a Process.
Material Resource Physical thing that participates in a Process.
Performance
Information
Information involved in the evaluation of a SC Entity.
Process
Activity or structure of activities intended to achieve a result, which entails the utilization of
time, material, space, expertise or other resources.
Process Element Business Process component activity. In the SCOR model, it represents a level three process.
Product Individual or group of material resources resulting from a Process.
Resource Physical or conceptual means involved in a Process, as personnel, equipment, material, etc.
Resource Perspective
A view of a Resource focused only on those aspects or characteristics that are of interest to a
Process.
Functional View
Task
Process Element component activity. In the SCOR model, it represents a level four or a higher
level process.
Aggregation
Hierarchical relationship that exists among an information resource, and other information
resources of lower aggregation level.
Disaggregation
Hierarchical relationship existing among an information resource and other information resources
of higher aggregation level.
Goal A desired situation or general purpose toward which efforts are directed.
Hierarchical
Relationship
Relationship that exists among information resources of different degrees of granularity.
Level
A management-based grouping associated with the scope and time horizon of decisions, actions
or plans.
Metric Dependency Conditioning relationships between performance metrics.
Management View
Vertical Integration
Specifies the way the information integration is tackled according with the hierarchical
relationships among the information resources that are involved.
Measure
Value that results from a measurement done by means of a given metric, as well as its normalized
value.
Metric Method that allows evaluating a particular Performance Attribute of a SC Entity.
Performance Attribute Measurable property of SC Entities.
Performance View
Performance
Dimension
Performance point of view. It is used to qualify Performance Attributes.
Customer OP View of an Organizational Unit corresponding to a customer role of a Supply Chain.
Organizational
Perspective
A given view that an Organizational Unit presents with respect to a SC in which it is involved.
Organizational Unit
It might be a company, corporation, firm, enterprise or institution, or a part of it, having its own
function(s) and administration, which supplies and/or acquires products or services.
SC Market
Group of customers (Organizational Units with the role of customers in a given SC) that share
some characteristics.
Supply Chain
The network of business units, form original suppliers to end-customers, which transforms raw
materials into final products, besides other value-adding companies such as logistics providers.
SC Structural View
Value Aggregation OP View of an Organizational Unit corresponding to a value incorporating role in a Supply Chain.
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2.3.1 SC Structural Concepts
The structural view includes Supply Chain concepts,
along with the ones representing the various
organizations which participate in a SC, and the
roles these enterprises assume in different SCs. The
main concepts of this perspective, such as Supply
Chain, Organizational Unit (OU) and Organizational
Perspective, are described in Table 1.
To reflect the fact that a given Organizational
Unit (factory, warehouse, retail store) can participate
in various SCs, the Organizational Perspective (OP)
concept was included. It captures the different
viewpoints that an OU presents with respect to the
various SCs in which it participates. In a given SC,
an OU could assume either the role of a customer or
the one of a value aggregation node. Therefore, the
Organizational Perspective concept is specialized
into Customer OP and Value Aggregation OP.
Supply Chains are usually differentiated
according to the characteristics of the delivered
product/s and the diverse target markets. These ideas
are captured by the association of the Supply Chain
class with one or more Products and a SC Market.
The Product class denotes individual or groups of
goods having common characteristics. The SC
Market concept represents a group of buyers of a
particular good or service, and it is composed of
Customer OPs.
2.3.2 Functional Concepts
The functional view is concerned with activities or
processes performed in the SC and the means
involved in them. The most important definitions are
depicted in the Functional View section of Table 1.
As seen in Figure 1, Processes are hierarchically
decomposed, as the basic structure of the SCOR
model suggests, in at least three levels of detail,
ranging from Business Processes (higher level) to
Process Elements and Tasks (lower level). These can
be Complex or Elementary, depending on if they are
composed of other tasks or not.
Processes can be associated with several
Organizational Perspectives and they can participate
in various SCs. This is due to the fact that a given
process could cross various functional areas and/or
companies (when they are integrated) and, at the
same time, it could also be executed to achieve
results on different SCs. For instance, a Warehouse
Delivery process can be done in the same way,
involving the same resources and methods, for
certain pharmaceutical and food product SCs.
Additionally, the execution of a given Process
may depend on the temporal ordering defined among
the Processes, represented in the model by temporal
relationships.
Resources are also included in this view. Despite
they are not functional in nature, resources are
integrated in this perspective because they are
closely related with functions. They not only are
essential assets (as materials, equipment, personnel,
etc.) associated with Processes, but also their
availability can restrain the capacity to execute the
Processes in which they participate. Resources can
be physical or conceptual things and may assume
different roles depending on the Process in which
they participate. Therefore, in order to consider only
those Resource characteristics that are of interest in
a given context, the Resource Perspective class is
defined.
2.3.3 Management Concepts
The management view comprises management
information about the SC. The most relevant
concepts are defined in Table 1 and shown at the
bottom left section of Figure 1.
Management information has different degrees
of granularity due to various reasons, like error
minimization, data availability, etc. In general, the
information used at higher decision levels is more
aggregated than the one employed by lower level
activities. However, these information pieces are
generally interrelated and it is very important to
capture their links. With this aim, SCOntology has
incorporated the Hierarchical Relationship concept,
which makes explicit the participation of
information in diverse Aggregation or
Disaggregation relationships. The Vertical
Integration concept denotes the manner in which the
integration is performed in each Hierarchical
Relationship.
The Goal concept is a useful management
concept incorporated into the ontology. It has been
established at different decision levels (Strategic,
Tactical or Operational) for the proper management
of SCs. Since it is essential to control Goals by
means of appropriate Metrics, the attainment of a
certain Goal can be monitored by, at least, one
Metric. In addition, a particular Goal could be
aggregated from or disaggregated into other goals.
For this reason, specific links between the Goal
concept and the Hierarchical Relationship one are
included in the ontology (see Figure 1).
2.3.4 Performance Concepts
The performance perspective groups those notions
associated with performance evaluation. The main
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concepts are introduced in Table 1. They are also
shown at the upper left section of Figure 1.
Supply chain entities (SC Entity in Figure 1),
being elements that participate in SCs, could have
performance attributes to be assessed.
It should be noted that a performance attribute of
a certain SC entity can be evaluated by means of one
or more metrics, each one having its own values. On
the contrary, a Metric can only be associated with
one SC Entity and one Performance Attribute. In
order to prescribe which attribute and which SC
Entity can be appraised with a given metric, the
generic concept of metric should be specialized in
particular metrics that assess the SC performance.
The values assigned to a certain Performance
Attribute of a SC Entity in relation to a given Metric
are represented in the ontology by the Measure class.
These values can be obtained by actually doing a
measurement, by benchmarking, or can be set as part
of a SC design process; nevertheless, each value is
always associated with a Metric.
The Performance Attribute concept is specialized
in the following classes: Reliability, Flexibility,
Responsiveness, Costs and Assets, following the
guidelines of the SCOR model. In turn, performance
attributes are categorized through the Performance
Dimension concept, which characterizes them
according to their scope. The SCOR model identifies
two, the Internal Facing and the Customer Facing
perspectives, which are focused on short-term
assessment issues. The Long Term Facing
perspective has been added to SCOntology to
include a performance perspective concerned with
the evaluation of actions performed to achieve future
results, related with strategic and tactical issues.
Additionally, this proposal acknowledges that
some performance evaluation frameworks, like the
one proposed by Brewer and Speh (2000), based on
the Balanced Scorecard idea (Kaplan and Norton
1992), identify links between pairs of different
Performance Dimensions. These relationships
indicate, in a qualitative manner, that if changes take
place in a given performance dimension, they are
expected to entail modifications in another one. This
notion is included in the ontology as an Influence
association between Performance Dimensions. For
instance, the Long Term Facing dimension
influences both the Internal and Customer Facing
ones, whereas the Customer Facing dimension
affects the Internal Facing one.
2.3.5 Application Example
With the purpose of illustrating the main concepts of
the ontology, a simple case study is presented.
Figure 2 shows a partial view of SCOntology,
capturing some of the notions under analysis along
with the instantiation of these concepts in order to
represent a SC associated with a furniture enterprise
and its corresponding evaluation. The constituents of
this SC are the ‘Oak Wonders’ enterprise, the
‘InWay Trucking’ company and various retailers.
Oak Wonders (OW) produces and distributes oak
home furniture: tables, beds, sofas, cabinets,
wardrobes, etc., both in a standard format and in a
tailored made one. It has outsourced the delivery
transportation business and made a long-term
contract with InWay Trucking (IWT), which is a
3PL that specializes in the haulage of different types
of products, such as apparel, footwear and furniture.
IWT is the linkage between OW and the retailers.
The business process configuration of this
furniture SC and its associated evaluation methods,
depend on the product line that is managed. Thus,
from an OW viewpoint, the processes involved in
supplying standard furniture to retailers include the
storage of final products. On the contrary, no stock
is kept for tailor made furniture. Similarly, metrics
used to evaluate the performance of business units
and processes are not the same for standard and
custom built furniture. Due to these reasons, it is
important to distinguish SCs according to their
associated product and service.
This example focuses on one particular SC
whose objective is to furnish small and medium size
national retailers with standard wardrobes. This
information is represented in Fig. 2 by the ‘Standard
Wardrobes SC’ instance as well as by its links to the
‘Standard Wardrobes Family’ and to the ‘Middle
and Small Size National Furniture Retailers’ objects.
All of the previously described companies are
modelled by instantiating the Organizational Unit
concept. Additionally, but limiting the analysis to
only those elements associated with the standard
wardrobes family of products, OW is composed of
three OUs: one manufacturing plant and two
distribution centers (the north and the south ones).
Each of these OUs has a perspective involved in the
standard wardrobes SC which is linked to the
‘Standard Wardrobes SC’ object.
With the purpose of exemplifying the application
of the ontology to the evaluation of this particular
SC, the ’Number of Monthly Stockouts’ metric is
proposed as a specialization of the Metric concept.
This metric is an adaptation of the ‘Number of
stockouts’ one, which was described in the first
section of this contribution. The metric is
appropriate for appraising an environment where
A SUPPLY CHAIN ONTOLOGY CONCEPTUALIZATION WITH FOCUS ON PERFORMANCE EVALUATION
407

standard products are sold from stock. It is defined
as the ‘Number of requested items that are out of
stock per month’ and represents a method that
allows evaluating the responsiveness of an
organizational perspective, as indicated by its
associations.
The ‘Number of Monthly Stockouts’ metric is
instantiated, resulting in the following objects:
‘Wardrobes Manufacturing Plant Metric’, ‘North
Distribution Center Metric’, ‘South Distribution
Center Metric’ and ‘Retailer Metric’. As seen, these
metrics are involved in the evaluation of the
responsiveness of specific OPs. Each of them has its
own target value and an allowed tolerance.
Moreover, each metric shown in this example is
related to one or more measures that represent the
values of the responsiveness attribute for the
different OPs being evaluated. Additionally, the
measure instances capture further data about the
measurement: the time point when the assessment
was done and the period that was appraised. Thus, it
is possible to trace how a performance attribute was
evaluated, which metric was used, which were its
values in diverse occasions and, in turn, which SC
entity each measure evaluates. For example, it can
be seen that the standard wardrobes manufacturing
OP was evaluated twice, according to the
‘Wardrobes Manufacturing Plant Metric’, to assess
its responsiveness. Its values were 30 and 25
items/month for the October and November periods,
respectively.
Oak
Wonders
Plant November Stockouts
Middle and Small Size
National Furniture Retailers
Standard
W ardrobes Famil y
Wardrobes
Manuf ac t uri n g
Plant
val ue: 5
timepoint: 8/11/2007
period: 01/10/2007 - 31/10/2007
normalized value: "-"
Retailer October Stockouts
value: 25
timepoint: 7/12/2007
period: 01/11/2007 - 30/11/2007
normalized value: "-"
Responsiveness
Instance
Plant October Stockouts
val u e: 30
timepoint: 5/11/2007
period: 01/10/2007 - 31/10/2007
normalized value: "-"
North Dis tri bu ti on Center
October Stockouts
val u e: 8
timepoint: 3/11/2007
period: 01/10/2007 - 31/10/2007
normalized value: "-"
South Distribution Center October
Stockouts
value: 16
timepoint: 4/11/2007
period: 01/10/2007 - 31/10/2007
normalized value: "-"
target= 0
allowed tolerance= 25
Wardrobes
Manufacturing Plant
Metri c
target= 0
allowed tolerance= 10
target= 0
allowed tolerance= 12
South Distribution
Center Metric
target= 0
allowed tolerance= 10
Retailer Metric
0..n
1
Performanc e Attribute
1
0..n
0..n
0..n
Number of Monthly Stockouts
10..n
Organizational
Unit
0..1
0..n
1
0..1
1
SC Entity Metric
Standard
W ardrobes North
Distribution OP
Standard W ardrobes
South Distribution OP
Furniture Retai ler
S tandard W ardrob es
Commercialization OP
InWay Trucking
Standard
Wardrobes SC
definition ="Number of requested items that are
out of stock per month" {readonly}
unit of measure = "Items/month"
{readonly}
frequency = "monthly"
{readonly}
normalization criteria= "-"
{readonly}
target
allowed tolerance
North Distribution
Center Metric
Responsiveness
North Dis tri bu ti on
Center
Standard W ardrobes
Transportation OP
Meas ure
0..n
1
Standard
W ardro bes
Manufacturing OP
SC
Ma rke t
Orga ni zati onal
Perspective
1..n
1..n
1
Supply
Chain
Product
South Distribution Center
Figure 2: Metric specialization and instantiation example.
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408

3 CONCLUSIONS
This paper presents advances in the development of
an ontology, named SCOntology, that contributes
towards the formalization of the SC domain and its
associated evaluation system. SCOntology provides
the basis for the description of the supply chain
structure, its associated processes and evaluation
system. In this way, it could lay the foundation for
the development of a computational performance
evaluation system. It adopts the process hierarchical
decomposition structure of the SCOR reference
model, which is nowadays a de facto standard.
However, it enlarges it with additional concepts that
allow to (i) render a more comprehensive enterprise
model, and (ii) formally describe information
composition or decomposition processes.
Regarding the evaluation system, SCOntology
incorporates several performance evaluation
management tools in a single framework. It allows
the definition of different metrics and performance
related concepts, including the measurement of
performance attributes of distinct types of SC
entities. Besides, classifications of metrics and
performance attributes, relations with the SC’s goals
and their control, as well as important relationships
between metrics and performance dimensions are
some of the features that are incorporated in the
ontology.
Future work entails representing SCOntology in
OWL or in a closely related language. Once the
ontology is fully defined, new defies will be tackled.
One refers to the identification of mechanisms for
collecting and managing the data needed to operate
an assessment system in an actual dynamic
environment. Another is related to the analysis and
handling of performance information from a
temporal perspective. One of the possible solutions
to these challenges is the use of agent technology.
ACKNOWLEDGEMENTS
This work has been supported by CONICET (PIP
5915), UTN, UNL and ANPCyT (PICT 12628).
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