A Practical Framework for Business Process Management Suites
Selection Using Fuzzy TOPSIS Approach
Ahad Zare Ravasan
1
, Saeed Rouhani
2
and Homa Hamidi
3
1
Department of Industrial Management, Allameh Tabataba’i University, Tehran, Iran
2
Faculty of Managment, University of Tehran, Tehran, Iran
3
Department of Information Technology Management, MehrAlborz University, Tehran, Iran
Keywords: Business Process Management (BPM), Business Process Management Suite (BPMS), Business Process
Management Suite Selection, Functional Requirements, Fuzzy Technique for Order Preference by
Similarity to Ideal Solution (FTOPSIS).
Abstract: Nowadays, there is a growing interest in Business Process Management Suites (BPMSs) implementation in
organizations. In order to implement a BPMS in an organization successfully, it is essential to select a
suitable BPMS. Evaluation and selection of the BPMS packages is complicated and time consuming
decision making process. This paper presents an approach for dealing with such a problem. This approach
introduces functional, non-functional and fuzzy evaluation method for BPMS selection. The presented BPM
lifecycle based approach breaks down BPMS selection criteria into two broad categories namely functional
(process strategy development, process discovery, process modeling, process design, process deployment,
process operation and analysis) and non-functional requirements (quality, technical, vendor,
implementation) including totally 48 selection criteria. A facile Fuzzy Technique for Order Preference by
Similarity to Ideal Solution (FTOPSIS) is customized for BPMS selection based on identified criteria. The
proposed approach is applied to a local Iranian company in oil industry in order to select and acquire a
BPMS and the provided numerical example illustrates the applicability of the approach for BPMS selection.
The approach can help practitioners assess BPMSs more properly and have a better software acquisition
decision.
1 INTRODUCTION
Many surveys implied that the gap between
Information Technology (IT) and business is
growing and there are also increasing reports that IT
not meeting business needs (Cho and Lee, 2011).
Therefore, there is a need for better communication
and understanding between IT and Business needs.
To overcome this gap, many companies emphasis on
the importance of business processes and the role of
IT. Business Process Management (BPM) has been
emerged as a new breed of process-centric
approaches for companies that consider processes to
be fundamental business assets (Davenport, 1993).
Elzinga, et al., (1995) defined BPM as systematic,
structured approach to analyze, improve, control,
and manage processes with the aim of improving the
quality of products and services. Also, Business
Process Management Suites (BPMSs) are an enabler
of business innovation because of the dramatic
potential for improving the performance and agility
of companies (Cho and Lee, 2011). These systems
simplify the development of process models and
automate the process flow during process execution
(Van Der Aalst and Van Hee, 2004). This approach
can improve the ability of enterprises to cope with
challenges like shorter product lifecycles, rising
customer expectations, globalization, increasing cost
pressure, and advancements in IT (Weske, 2007).
The major drivers for BPM software adoption can be
expressed as optimization of processes, increased
productivity for process workers, the ability to
model business processes, support for compliance
efforts, standardize processes across divisions and
regions, the ability to provide real-time visibility
into key, processes, and the ability to change
processes quickly and easily (Richardson, 2010).
Despite considerable investment in the area of
BPMSs, most reviews report as many as 60–80% of
BPM initiatives having been unsuccessful
295
Zare Ravasan A., Rouhani S. and Hamidi H..
A Practical Framework for Business Process Management Suites Selection Using Fuzzy TOPSIS Approach.
DOI: 10.5220/0004872302950302
In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 295-302
ISBN: 978-989-758-029-1
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
(Abdolvand, Albadvi, and Ferdowsi, 2008; Karim,
Somers and Bhattacherjee, 2007). It is therefore not
surprising that some businesses are not convinced
that the BPM approach could bring significant
tangible and measurable benefits (Vergidis, Tiwari
and Majeed, 2008) and that the risky nature of BPM
has motivated investigation of its critical success
and failure factors (Al-Mudimigh, 2007; Trkman,
2010). Top management commitment, careful
software selection that fits business processes,
process management and improvement, change
management, people management and development
are among the most important BPM critical success
factors (Al-Mudimigh, 2007; Trkman, 2010).
Careful BPMS selection is an important factor to an
extent which would be unlikely to achieve expected
benefits without using a proper BPMS. The timing
and selection of the BPMS, just like traditional
information systems, can be problematic and even
improper solutions have the potential to inhibit
implementation of new processes in an organization.
The BPMS industry is one of the fastest growing
sectors in the computer software industry which now
includes hundreds of BPMS solutions in the market.
BPM markets at $ 2.3 billion in 2010 are anticipated
to reach $ 5.5 billion by 2017 (Curtiss and Eustis,
2011). The number of BPMS vendors and the range
of their systems’ functionality have further expanded
in recent years (Hill, Cantara, Kerremans and
Plummer, 2009). Hence, due to limitations in
available resources, the range of functionality in
BPMS, and the diversity of alternatives, selecting a
BPMS that meets closely the specific needs of an
organization is a time-consuming and complex task.
This is a challenge especially for small and medium-
sized businesses with limited know-how about such
systems (Eikebrokk, Iden, Olsen, and Opdahl, 2010)
which calls for some methods or models for
enhancing the selection process.
The dominating school of thought assumes that
IT tools are operational business resources and
therefore should be chosen according to the specific
characteristics, contents, and requirements of the
business processes to support. However, having a
review on BPMS literature, authors have found no
related widely used framework for evaluating and
selecting BPMS packages. Till now, practitioners
selected needed BPMSs, based on some important
factors, while overlooking other aspects of system or
vendor. Previous experience suggests that businesses
tend to focus on well-known software vendors and
already used IT solutions or adhere strictly to
industry best practices, which do not sufficiently
match to the individual requirements of each process
(Sadiq, Indulska, Bandara and Chong, 2007;
Trkman, 2010). Neglecting system features in
system selection phase, can lead to future problems
in customization efforts which can extend project
total time and cost.
To sum up, following a holistic framework for
assessing BPMS can help IT managers to deal with
this problem and diminish the need for future
customizations. It is noticeable that each software
selection framework needs its own criteria and its
computation procedures. BPMS is a state of the art
issue and there is no specific and certificate based
framework for BPMS selection. What is therefore
needed is a holistic framework for assessing BPMSs
from a variety of functional and non- functional
perspectives. This paper, as a potential contribution
to BPMS literature, is intended to provide such a
framework and hence our goal is to develop a
practical and holistic evaluation framework that is
applicable to BPMS selection efforts. In practice, the
results of this paper would enable IT managers to
achieve a comprehensive understanding of BPMS
selection criteria and help them to make a better
system acquisition decision.
2 LITERATURE REVIEW
This section includes a review of software selection
methods and factors, and then BPMS selection
criteria are provided with regard to the nearest
relevant literatures.
2.1 Related Works
Software selection problem is a particularly difficult
software acquisition process and many contradictory
criteria must be considered to reach a decision. In
this era, the literature lacks studies that consider the
evaluation of both the functional and non-functional
suitability of the alternative BPMSs using various
criteria. Therefore to study the generic requirements
and methods, the literature of selection of enterprise
software and systems is reviewed in this section.
Recently, Jadhav and Sonar (2009, 2011) reviewed
several criteria, techniques, tools and methods for
evaluating and selecting software and systems. Their
research covers many findings from past research
and outlines efforts that have been made in the field
of software selection. Enterprise software packages
are pre-written by a vendor to provide a set of
standard functions usable by a wide variety of
companies, regardless of size or industry.
Commercial off-the- shelf (COTS) is the other term
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that refers to enterprise software, such as accounting,
e-commerce, human resources (HR), customer
relationship management (CRM), supply chain
management (SCM), and enterprise resource
planning (ERP) systems.
In the literature, the primary selection process for
enterprise software uses the method of eliminating
potential solutions and Multi Criteria Decision
Making (MCDM) techniques in the selection
process of enterprise software. Software evaluation
is a multi-criteria decision-making problem that
refers to making preferred decisions from the
available alternatives, and this problem has usually
been solved by Analytical Hierarchy Process (AHP)
(Colombo and Francalanci, 2004; Wei, Chien and
Wang, 2005). Another approach to the evaluation
and selection of software and systems is a weighted
scoring method that was applied by Perez and Rojas
(2000) and Le Blanc and Louis (Le Blanc and Louis,
1989). To deal with the linguistic and verbal
evaluation of human decision makers in the selection
of software and enterprise systems, fuzzy multiple
criteria decision making (FMCDM) has been used in
various studies for evaluating software (Cochran and
Chen, 2005; Lee, Shen and Chih, 2004). The reasons
of FMCDM popularity in software selection are at
first: the tendency of selection stockholders in
general expression, second: the different software
approaches would be explicable with same verbal
evaluation and third: the FMCDM can conduct
group decision making which happen is software
selection.
Beside the software selection studies as a total
problem, some researchers have focused on
requirement selection and prioritization as a
beginning of software engineering. In recent years, it
is proved that an automated measurement,
evaluation and selection framework is necessary and
feasible to ensure trusted and repeatable decisions
for the general problem of software component and
package evaluation and selection (Becker and
Rauber, 2010). Another observation based on the
review of the literature (Jadhav and Sonar, 2009) is
that although the functional criteria for software
selection are altered for different software packages,
other criteria related to the quality, cost and benefits,
vendor, hardware and software requirements, the
opinions of different stakeholders about the software
package, and the output characteristics of the
software package are universal and can be used for
evaluation of any software package. Furthermore,
many of these methods consider only the traditional
non-functional criteria, but do not offer a process
that includes functional and non-functional
requirements and a customized approach for BPMSs
selection, especially.
2.2 BPMS Selection Criteria
BPMS is the leading integrated composition
environment (ICE) to support BPM and enable
continuous improvement. BPMS as an ICE usually
has integrated management and administration
consoles, a common security model, a common
meta-model, integrated installation procedures and
documentation, shared technical support, and a
consistent look and feel in the UIs (Gartner, 2010).
In addition, functionality within a BPMS is not
duplicative. Although there may be multiple engines
and servers within the suite, they address distinct
needs and interoperate. A well-integrated suite
"feels" like a single product to the individual using
it, regardless of his or her role, because of its
architectural and meta-model cohesion. Finally,
BPMS artifacts move fluidly across the phases of
BPM life cycle.
According to Abecker, et al., (2002), there are
four major classes of BPM supporting software
systems. Visualization tools are a simplified variant
of tools for creating graphical process models.
Modeling tools extend the capabilities of
visualization tools by emphasizing formal
correctness and supporting the analysis of process
models. Therefore, these tools assist in managing the
relationship between activities, data, and resources
of a company. Simulation tools assist in predicting
performance indicators like required time and costs.
Thereby, these tools provide a foundation of further
optimization. Workflow management systems assist
during modeling, execution, and monitoring of
automatable business processes (Carstensen and
Schmidt, 2003)
.
2.2.1 BPMS Functional Criteria
In order of determining BPMS selection criteria, in
this research, BPM life cycle (Koster, 2009) has
been considered as the base of functional
requirements category. Hence, the BPM life cycle
has seven phases, therefore the functional criteria for
BPMS is decomposed into seven areas based on this
cycle as process strategy development, process
discovery, process modeling, process design,
process deployment, process operation and analysis
(see Table 1). To verify the proposed functionalities
in each category, they have been checked and
approved by five experts in BPM filed. These
experts were BPM project managers with more than
APracticalFrameworkforBusinessProcessManagementSuitesSelectionUsingFuzzyTOPSISApproach
297
5 years experiences on BPM related implementation
projects in global/ local organizations. The major
issue in proving the necessity and sufficiency of
these criteria is the conformance of them with the
ISO 10244: 2010 qualifications as goal of BPMS
implementation.
Table 1: Functional criteria for BPMS according to BPM
lifecycle.
Functionality (Supporting)
Process strategy development
Value chain overview
Link the organization’s objectives with the high-level
business processes
Process discovery
High level process mapping
Process mining tools and recommendations
Process modeling
Different business process modeling languages
Interoperability between different modeling languages
Capability of defining Performance Indicators for
process
Process design
Creating executable business process models
Programming languages for implementing services
Designing user interfaces
User management
Process deployment
Workflow resource patterns
Distributed business process execution engines
Process operation
Optimized execution according to some measurable
criteria
Exception handling
Technical monitoring and control
Active and passive business monitoring
Business balance control
Analysis
Modeling time testing
Log data analysis
Visual data representation tools
Activity-based costing
Defining processes in taxonomies
Suggestions on improvement
2.2.2 BPMS Non-functional Criteria
The non-functional requirements are features of the
BPMS that are not covered by its functional
description, but are related to the capability and
resiliency of the software or solution. Some
researchers and practitioners have developed
categories for the non-functional requirements, from
different viewpoints. Jadhav and Sonar (2011)
classified these criteria as quality, technical, vendor,
output and opinion categories, based on
ISO/IEC9126. Similarly, Sen, et al., (2009) divided
these requirements into quality characteristics,
technical factors and socio-economic factors
(business and vendor). The current research
concentrates on more recent researches of Jadhav
and Sonar (2011) and Sen et, al., (2009) and then
based on them, non- functional criteria for BPMSs
are proposed as Table 2.
Table 2: Non-functional criteria for BPMS.
Category Criteria
Quality requirements
Reliability
Usability
Maintainability
Efficiency
Personalizability
Portability
Technical requirements
Communication protocol
Platforms
Database management
system
Programming language
Documentations
Standard configurations
Security
Vendor factors
Vendor reputation
Training and support
Length of experience
Consulting service
Implementation factors
License price
*
Implementation cost
*
Implementation time
*
Training cost
*
*Cost criteria (Negative criteria)
3 THE FUZZY TOPSIS METHOD
Current research uses triangular fuzzy numbers
(TFNs) for fuzzy TOPSIS because of the ease of use
for decision-makers in doing calculations.
Furthermore, it has been demonstrated that modeling
with triangular fuzzy numbers is an effective way to
formulate decision problems when the available
information is subjective and inaccurate (Moalagh
and Zare Ravasan, 2012). The steps of the fuzzy
TOPSIS method, which were introduced by Onüt
and Soner (2008), and are applied in this paper, can
be summarized as follows:
Step 1: Choose the linguistic values (
mjnix
ij
,...,2,1,,...,2,1,
) for alternatives
concerning the criteria. The fuzzy linguistic rating (
ij
x
) keeps the ranges of normalized triangular fuzzy
ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems
298
numbers that belong to [0, 1]; hence, there is no
need for normalization.
Step 2: Compute the weighted, normalized,
fuzzy-decision matrix by Equation (1)
Step 3: Determine positive-ideal (FPIS,
A
)
and negative-ideal (FNIS,
A
) solutions from the
equations below:
},...,{
1
i
vvA
)}min(),max{(
cij
j
bij
j
iviv
},...,{
1
i
vvA
(1)
)}max(),min{(
cij
j
bij
j
iviv
(2)
b
are the sets of benefit criteria and
c
are
the sets of cost criteria
Step 4: Calculate the distance of each alternative
from
A
and
A
by the following equations:
niVVdD
i
m
j
iji
,...,2,1),
~
(
*
1
(3)
niVVdD
i
m
j
iji
,...,2,1),
~
(
1
(4)
Step 5: Compute similarities to the ideal
solution:
ii
i
i
DD
D
FC
(5)
4 PROPOSED APPROACH
For many companies, the process of selecting BPMS
is a main cause of stress and the final decision often
comes after months of deliberation. Usually, this is
due to the wide variations in available features
across products and the lack of a clear understanding
of which features will best suit the company’s needs.
However, this process can be made easier by
utilizing proposed approach. In this research, fuzzy
TOPSIS has been used to evaluate and select BPMS
with respect to the criteria presented in Table 1 and
2. There are three stages in the evaluation and
selection of the BPMS, based on evaluation criteria:
1) determining BPMSs to be evaluated as
alternatives, and recognizing the criteria to be used
in the assessment process; 2) structuring the fuzzy
decision-matrix and assigning criteria weights; 3)
computing the scores of alternatives with fuzzy
TOPSIS and finally, ranking the evaluation report.
In following sections, this approach is applied to
solve a numerical example.
5 NUMERICAL EXAMPLE
This new approach to the evaluation and selection of
BPMSs is applied to the Iranian Offshore
Engineering and Construction Company (IOEC) in
Iran`s oil industry to demonstrate its applicability
and validity in an actual environment. IOEC is the
first Iranian offshore general contractor to fabricate
and install offshore facilities for the Iranian oil and
gas industry. Today, IOEC is developed into an
Engineering, Procurement, Construction and
Installation (EPCI) contractor at international level,
and is capable of providing offshore and onshore
services for the industry. Due to recent
achievements, the company is in the process of
looking into the possibility of establishing itself as a
holding company. The IOEC management, in
consultation with information systems experts,
decided to adopt a BPMS with the aim of
optimization of processes, gaining ability to
standardize and model business processes, and
achieving the ability to change processes quickly
and easily. According to the research steps described
above, the proposed fuzzy TOPSIS approach was
explained along with applications and BPMS for the
company was selected using the approach.
5.1 Forming Decision-making Team
Expert teams should be formed to evaluate the
functional and non-functional aspects for BPMS
alternatives. The teams consisted of BPM experts in
the company (five people) and one team included
technical managers of company (three people) have
responsibility for evaluation of non-functional
criteria. Concurrently, external consultants of the
company (two people) with BPM and IT technical
skills, helped to evaluate the functional and non-
functional requirements for considered BPMSs. The
Fuzzy TOPSIS technique was introduced to them
(ten people) and they were trained for filling the
spreadsheets of evaluation by verbal and simple
propositions.
5.2 Identification of Alternatives and
Criteria
If there are more BPMS alternatives in the list than
APracticalFrameworkforBusinessProcessManagementSuitesSelectionUsingFuzzyTOPSISApproach
299
expected, a pre-selection process should be used to
reduce the number of alternatives to an acceptable
level (five or four), so that the selection process will
not be too lengthy. Therefore, sequential elimination
methods are only used to separate the strong
candidates among others. As a result, five BPMSs
were considered for evaluation identified in the
paper as BPMS I, BPMS II, BPMS III, BPMS IV
and BPMS V. All of the 48 identified criteria as
shown in Table 1 and 2 were used for the BPMSs
assessment. These criteria were named C1, C2 …
C48.
5.3 Structuring the Fuzzy
Decision-matrix
Linguistic values were used for the evaluation of the
alternatives and weights of the criteria. The
membership functions of these linguistic values and
the triangular fuzzy numbers related to these
variables are shown in Table 3. In applications, it is
often convenient to work with Triangular fuzzy
numbers (TFNs) because of their simplicity and they
are useful in promoting representation and
information processing in a fuzzy environment,
Therefore in the current research TFN is chosen.
Table 3: Linguistic values and fuzzy numbers.
Linguistic
variables
Fuzzy
numbers
Membership Functions
Very low (VL) (0.0,0.0,0.2)
Low (L) (0.0,0.2,0.4)
Medium (M) (0.2,0.4,0.6)
High (H) (0.4,0.6,0.8)
Very high (VH) (0.6,0.8,1.0)
Excellent (E) (0.8,1.0,1.0)
Based on the linguistic variables (Table 3),
alternatives and the criteria were assessed by the
decision-making team, which also assigned
appropriate weights to each criterion by asking
experts in the field of BPMSs. A fuzzy decision-
averages matrix for BPMSs was created, based on
the judgment of experts
5.4 Evaluating BPMS Alternatives
After the fuzzy decision-matrix has been established,
the next step is to compute the fuzzy, weighted
decision-matrix. This matrix is calculated with
Equation (1). Equations (2) and (3) are then applied
to define the fuzzy positive-ideal solution (FPIS,
A
) and negative-ideal solution (FNIS,
A
). Then, the
Euclidean distance of each alternative from
A
and
A
is computed using Equations. (4) and (5).
Subsequently, the similarities to an ideal solution are
solved by Equation (6). Finally, the values of each
alternative (BPMS) for the final ranking are
illustrated in Table 4. A comparison of
521
,...,, DDD
and
521
,...,, DDD
that reflects the
capabilities of BPMSs, its strengths and weaknesses,
can be seen, here. For example, it can be seen that
BPMS IV has a large
i
D
, which shows a large
distance from the negative ideal. It also shows that
this BPMS has appropriate functional and non-
functional capabilities, which enhances the BPM
implementation in the organization.
Table 4: Final computation results.
BPMSs
BPMS I
7.42 5.21 0.412311
BPMS II
7.93 4.78 0.376101
BPMS III
6.89 6.10 0.469795
BPMS IV
5.24 7.28 0.581343
BPMS V
7.10 6.11 0.462272
Based on the values of FC
i
the BPMS IV was
selected to be implemented in the studied case
company. The proposed approach guarantees the
maximum coverage of functional and non-functional
requirements with respect to selection criteria.
6 CONCLUSIONS
First, in this paper, an attempt was done to elaborate
on the importance of BPMS selection in successful
BPM implementation efforts. It was shown that
selecting the proper BPMS in adopting organizations
is a difficult task with parameters that can be
expressed in linguistic values. Such values are
somewhat vague in essence and are subject to expert
judgments which involve uncertainties. Therefore,
the fuzzy TOPSIS technique was employed to deal
with this problem appropriately. The fuzzy approach
is an applicable technique in providing decision
makers with estimated values under uncertainty in
the preference judgments. So, the fuzzy TOPSIS
technique has been applied in proposed BPMS
selection approach. Using this approach, the
different BPMSs can be evaluated and the best
solution be selected for any organization plans to
acquire a BPMS. The proposed framework breaks
down BPMS selection criteria into two broad
categories namely functional (process strategy
development, process discovery, process modeling,
i
D
i
D
i
FC
ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems
300
process design, process deployment, process
operation, and analysis) and non-functional
requirements (quality, technical, vendor,
implementation) including totally 48 selection
criteria.
The proposed approach was then applied to a
local Iranian company in the field of oil industry.
Five BPMSs were considered for evaluation using
the approach and the most merit one is proposed for
the company. The main novel points and merits of
the paper are as follows. First, this paper, as a first
attempt in BPM literature, demonstrated the
significance of BPMS selection in successful BPM
implementation projects. Second, a BPMS selection
approach has been proposed using both functional
and non-functional criteria. Third, fuzzy TOPSIS
based approach for software selection has been
proposed to contribute to the current literature in the
BPMS field. This approach can handle the inherent
uncertainty and imprecision of human decision-
making. Fourth, this paper presents an application of
the proposed approach to a real selection case. The
authors suggest that the proposed approach and
results of the paper can help practitioners assess
BPMSs more properly and have a better software
acquisition decisions.
The proposed approach is a practical and usable
solution for real case problems. But, it suffers from
some limitations. The main limitation of the
approach is that the usability of the model and the
validity of the achieved results were heavily
dependent on experts’ competence and proficiency
in the both BPMS field and IT technical issues.
Another limitation of the study is that the approach
presented here does not consider all the possible
factors and criteria might be associated with BPMS
selection.
Although the provided numerical example helps to
understand the applicability of the approach for
BPMS selection, we believe that room still remains
for future validation and improvement. So, further
research is necessary to fine tune the proposed
approach and assess its validity in others cases.
Applying other MCDM methods in a fuzzy
environment to BPMS selection and comparing the
results of these methods is also recommended for
future research. Also, mathematical models or meta-
heuristics can be combined with the existing
method. Furthermore, since the proposed method
involves a large amount of numerical computations,
a user-friendly intelligent decision support system
(DSS) or an expert system (ES) have to be
developed to save time and efforts in both doing
calculations and interpreting the results of the fuzzy
TOPSIS. Besides, developing a group decision-
making system proves useful, so, the different
opinions of different authorities can be taken into
account. As the proposed approach draws upon the
BPM lifecycle, future works may extend the main
categories of this approach by adding new sorts of
factors especially in functional category based on
organizational survey and customization of unique
internal and executive functional requirements.
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