A Guidance System for Business Process Flexibility
Asma Mejri
, Sonia Ayachi Ghannouchi
and Ricardo Martinho
Laboratory RIADI-GDL, ENSI, Mannouba 2010, Tunisia
High Institute on Management of Sousse, Tunisia
School of Technology and Management, Polytechnic Institute of Leiria, Portugal
Center for Health Technology and Services Research (CINTESIS), Portugal
Flexibility, Guidance, BPM, Emergency Care Process, BPMS, Paradigm.
During the last decades, flexibility has gained a strong presence, in a variety of disciplines, mainly in the
BPM field. The real challenge for BPM consists in providing modeling paradigms and BPMSs with adequate
information and features to deal with the often conflicting requirements of flexibility. In this setting, we focus
on providing a guidance approach for enhancing business process flexibility. Our purpose is therefore to
perceive which modeling paradigm(s) and/or business process management system(s) (BPMS(s)) are the most
adequate to the specific organization needs in terms of flexibility. This approach was implemented in a plug-in
named BPFlexGuide. To evaluate this approach, we have studied the emergency care (EC) process. Users
interested in the EC process were guided to use the AristaFlow BPM suite BPMS. The results of this study
would help designers to choose the best paradigms and BPMS that best fit their needs on flexibility.
In the past decades, flexibility has gained a strong
presence in various fields, notably in the BPM dis-
cipline. Flexibility is a must, because continuously
changing conditions compel organizations to rapidly
and flexibly adapt their business processes (BPs).
Thus, the real challenge for BPM consists in provid-
ing modeling paradigms and BPMSs with adequate
information and features to deal with the often con-
flicting requirements of flexibility. Indeed, several
paradigms have emerged.
In this paper, we are going to select the most pop-
ular paradigms which are the rule-based, constraint
based, case handling and adaptive process manage-
ment. The adaptive paradigm represents one of the
paradigms that enable users to make structural pro-
cess changes to support the handling of exceptions,
the evolution of BPs and user support in exceptional
situations (Schonenberg et al., 2008). A constraint-
based paradigm makes it possible to execute both al-
lowed and optional scenarios in BPs (Pesic, 2008).
A paradigm is called rule-based if the logic of its
control flow, data flow and resource allocation is ex-
pressed by means of business rules, which are recog-
nized as powerful representation forms that can po-
tentially define the semantics of BP models and busi-
ness vocabulary (Sun et al., 2006). The case han-
dling paradigm supports flexible and knowledge in-
tensive BPs (Van der Aalst et al., 2005). Each of
these paradigms has its specific characteristics which
are adjusted to specific organization’s needs.
On the other hand, users have to be aware of how
their flexibility needs can be addressed by the afore-
mentioned paradigms, and then which BPMSs bet-
ter match these (often combined) paradigms to exe-
cute and manage BP models and corresponding in-
stances. Moreover, process engineers, who often de-
cide which BPMS to adapt to their organizations, do
not know upfront most known BPMSs nor their (flexi-
bility) characteristics. Even if they could collect some
information from the Internet it would be very diffi-
cult to come up with a scoring mode that could easily
perform a match between their BPs’ flexibility needs
and the best choice for a BPMS. We propose in this
paper the BPFlexGuide guidance system for choosing
the best-suited BPMSs and BP modeling paradigm to
an organization’s BPs.
With our system, process engineers will be able
to input their organization’s needs in terms of BP
flexibility, and take a ranked and properly scored list
of recommended BPMSs and modeling paradigms.
They can also benefit, with our system, from fully
characterized BPMSs in terms of flexibility, which
will allow them to analyze and improve decision mak-
ing regarding particular characteristics that can only
be observed in some of their BPs. To accomplish
these main objectives of our BPFlexGuide guidance
Mejri, A., Ghannouch, S. and Martinho, R.
A Guidance System for Business Process Flexibility.
DOI: 10.5220/0006316902100217
In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2017), pages 210-217
ISBN: 978-989-758-250-9
Copyright © 2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
system, we performed the following main research
Compare existing BPMSs regarding flexibility:
This includes weighting the different flexibility
Measure the ability of existing BP modeling
paradigms to deal with flexibility;
Implement a system that guides the users to
choose the most appropriate BPMS and modeling
Evaluate the system using a flexible process (in
healthcare domain).
The remainder of this paper is organized as follows.
Section 2 presents basic concepts, including flexibil-
ity in BPM, a summary on Regev et al.s BP flexibil-
ity taxonomy and most relevant related work. Our re-
search method is described in Section 3 and in section
4 we reveal our main elements and artifacts derived
from this method. The BPFlexGuide implementation
details with ProM are presented in Section 5, and in
Section 6 we apply our approach to a case study. Sec-
tion 7 concludes the paper.
Guidance addresses the issue of guiding either users
and/or developers, practitioners and/or academicians,
and/or modelers during the different steps of the BPM
life-cycle. The concept of guidance has hence been
researched in the BPM community in the context of
proposing principles and guidelines, providing rec-
ommendation systems or decision support systems.
In (Mendling et al., 2010), authors propose a set of
seven process modeling guidelines. These guidelines
directly aim to bring support to process modelers. In
(Thomas et al., 2014), authors propose a set of ten
principles that characterize BPM as a research domain
and guide its successful use in organizational practice.
On the other hand, authors propose recommen-
dation systems, in (Barba et al., 2013), (Schonen-
berg et al., 2008), (Setiawan et al., 2011), (Conforti
et al., 2015), (Huang et al., 2012), (Koschmider et al.,
2011), (Mertens et al., 2014). For example, in (Barba
et al., 2013), the recommendation system is based on
a constraint-based approach for planning and schedul-
ing the BP activities and considers both the control-
flow and the resource perspective. Recommendations,
in (Schonenberg et al., 2008), are given in order to as-
sist users in selecting activities, during process exe-
cutions, by giving recommendations on possible next
Authors, in (Conforti et al., 2015), propose a rec-
ommendation system that supports process partici-
pants in taking risk-informed decisions, with the goal
of reducing risks that may arise during process execu-
tion. A system for supporting users at modeling time
was presented in (Koschmider et al., 2011). It pro-
vides information that facilitates the decision for the
right recommendation which is based on the user pro-
file. Consequently, users can follow up recommenda-
tions that are ranked, based on different criteria. In
order to provide guidance to users during process ex-
ecution, a recommendation system was proposed in
(Mertens et al., 2014). Their main contribution con-
sists of a robust process engine that can deal with
changes that are held in very dynamic and complex
environment, at run-time.
Other research efforts were engaged in developing
decision support systems. For instance, authors, in
(Cingil et al., 2012), have developed a decision sup-
port system that includes a relational database to keep
the predefined relations, its descriptions, the inputs
for weights, its grades and calculated scores. Besides,
authors have proposed in (Yao and Kumar, 2013) a
clinical decision support system that provides deci-
sion support, in order to get adaptable clinical path-
ways. These pathways are selected during BPs exe-
cution and are based on rules that encapsulate med-
ical knowledge and patient conditions that are con-
stantly changing. In most of these approaches, the
focus on flexibility and user assistance can be ob-
served. But, they do not support, in a straightforward
way, BP flexibility. Moreover, the need for increased
attention to flexibility, the competing paradigms and
the wide variety of BPMSs has been recognized by
both academia and industry. Though, to the best
of our knowledge, none of the research works di-
rectly targets the development of a guidance system
that takes into account flexibility and the multitude of
paradigms and BPMSs. Upon the recognition of such
scarcity, there is an urgent need to propose a guid-
ance approach and develop the corresponding tool in
order to guide users to choose the most convenient
paradigms and BPMSs, according to their particular
needs in terms of flexibility. An overview on our guid-
ance approach will be the main focus of the next sec-
In this section we describe our research approach,
which is based on two steps: (1) a general classifica-
tion of BPMSs and process modeling paradigms; (2)
A Guidance System for Business Process Flexibility
the proposal of a guidance procedure that foresees in-
puts from users regarding their needs in terms of BP
flexibility, and later guiding them to choose the best-
suited BPMS for their organizations.
Figures 1 and 2 present the main activities devel-
oped within these major two steps. These activities
can be summarized as follows:
Classification of BPMSs
Identification of flexibility criteria: we began
by identifying a set of criteria that we derived
from Regev et al.s taxonomy, in order to eval-
uate flexibility within BPMSs. From this activ-
ity we have specified eleven Flexibility Criteria
(FC) (detailed in the next section);
Development of the questionnaire ”‘Evalua-
tion of Business Process Management Systems
(BPMS)”’: here, we developed a questionnaire
for BPMS developers and researchers to an-
swer, based on their advanced knowledge of
the BPMSs they develop and research upon.
We also selected these BPMSs taking into ac-
count their prominence in literature, as well
as their ability to support BP flexibility. We
could then analyse the answers to the question-
naires and classify BPMSs accordingly, regard-
ing their support on flexibility and modeling
Proposal of a guidance procedure
User’s BP flexibility needs: here we have to
identify flexibility needs from the users of our
BPFlexGuide system. This step implied efforts
of mapping the well-known flexibility taxon-
omy of Regev et al. into a set of questions to
be understood by general users without a pro-
found knowledge of BP flexibility;
Similarity study: here we compare the obtained
answers from the users’ needs questionnaire
and the previous classification of BPMSs, in or-
der to derive a score in terms of flexibility;
Specific classification: we then classify and
sort the BPMSs and modeling paradigms with
an algorithm (detailed in the next section),
and present the associated recommendations to
In the next section, we provide the results and cal-
culations derived from each of these research activi-
Figure 1: Overview of step 1 of our research method.
Figure 2: Overview of step 2 of our research method.
We present in this section the main elements on which
our research is based. These include the identification
of flexibility criteria for evaluating BPMSs, the de-
sign of the questionnaire and obtained answers, and
the calculations and developed algorithms to assess
the BPMSs to users’ needs regarding BPs flexibility.
4.1 BP Flexibility Criteria
We began by identifying a set of criteria that we de-
rived from Regev et al.s taxonomy, in order to eval-
uate flexibility within the selected BPMSs. We have
specified eleven Flexibility Criteria (FC), which con-
cern the following questions:
FC1: To which extent do the BPMS modelers de-
scribe the process control flow?
FC2: To which extent does the BPMS support de-
scriptive modeling and execution of process activ-
ENASE 2017 - 12th International Conference on Evaluation of Novel Approaches to Software Engineering
FC3: To which extent does the BPMS support de-
scriptive modeling and execution of the precondi-
tions of the activities?
FC4: To which extent does the BPMS sup-
port descriptive modeling and execution of
data/information exchanged between process ac-
FC5: To which extent does the BPMS support de-
scriptive modeling and execution of roles associ-
ated to process activities?
FC6: Does the BPMS support changes to pro-
cess models which will affect all new process in-
FC7: Does the BPMS support changes at the in-
stance level, and that will only affect certain se-
lected instances, in order to accommodate excep-
tional situations?
FC8: Can the BPMS support incremental change
and/or revolutionary change?
FC9: How would the duration of change that
the BPMS support be characterized: temporary
and/or permanent?
FC10: Is the BPMS able to deal with immediate
and/or deferred change?
FC11: Can the BPMS support planned / ad-hoc
It is important to mention that all FCs have the same
weight. We have specified for each FCs a scale in or-
der to get consistent results. FC1, FC2, FC3, FC4 and
FC5 range from 0 (not descriptive) to 5 (very descrip-
tive). FC6 and FC7 can be 1 (yes) or 0 (No). FC8,
FC9, FC10 and FC11 can take 1 (if it satisfies one
of the characteristics describing this criteria) , 0 (if it
doesn’t satisfy none of the characteristics) or 2 (if it
doesn’t satisfy both characteristics).
4.2 Questionnaire for BPMS Providers
The questionnaire has been designed in order to
evaluate flexibility in BPMSs from a provider point
of view. The questionnaire was specifically de-
signed to seek responses from the most senior person-
nel responsible for the development of the selected
BPMSs. We had it filled out by eight senior devel-
opers/researchers that provides us with answers for
eight BPMSs (or modeling tools): DECLARE, ES-
ProNa, Jrules, AristaFlow BPM suite, Philhamon-
icFlows, jBPM, ProdProc and FLOWer. Most of the
BPMSs from which we got answers were developed
in the context of research projects. Others were de-
veloped by professional developers from the industry.
Table 1 contains the responses for each BPMSs. Ac-
cording to the questionnaire’s results, Table 2 summa-
rizes the answers to the following question: <What
is (are) your BPMS(s) underlying modeling/execution
paradigm(s)?”> From Table 2, we can conclude that,
from the selected BPMSs, most of them support
constraint-based modeling (5 out of 8) and also 5 out
of 8 are mono-paradigm oriented. We can also ob-
serve that 2 out of 3 multi-paradigm systems combine
the constraint and rule based paradigms.
4.3 Match between Users’ BP
Flexibility Needs and BPMSs’
Announced Flexibility
We aim at comparing the elements of the users’ needs
in terms of flexibility in BPs and the elements of the
responses of the questionnaire presented in Table 1.
Our study is based on a similarity metric in order to
measure distance, more specifically the overlap met-
ric. According to (Raj Kumar, 2012), the overlap met-
ric simply tests for equality between two values, so
that different values get distance 1 whereas equal val-
ues get distance 0:
Definition the overlap distance
(x, y) = 1 when x 6= y
(x, y) = 0 when x = y
4.4 Algorithm of Specific Classification
of BPMSs
In order to calculate this similarity score for each
BPMS, we follow the methodology that includes the
following steps: (1) Compare the users’ flexibility cri-
teria with the different BPMS flexibility criteria. (2)
Attribute a calculated similarity score for each crite-
rion. The score is 0 or 1, where 0 indicates no similar-
ity and 1 indicates identical elements. (3) Sum all the
criteria to obtain a similarity score SIM for the con-
sidered BPMS. The next step consists in comparing
the calculated scores for each BPMS in order to sort
Algorithm 1. We consider two sets S and U. S is
the set of the different BPMSs. Each S
consists of
the values taken by the flexibility criteria for a given
BPMS. U is the set of the criteria entered by the user.
Let n be the number of studied systems, NCR be the
number of studied flexibility criteria.
Furthermore let S = (S
, S
, S
, ..., S
U = (FCU
, ..., FCU
A Guidance System for Business Process Flexibility
Table 1: Responses of the questionnaire for each BPMS.
DECLARE ESProNa JRules AristaFlowBPM suite PHiharmonicFlows ProdProc jBPM FLOWer
FC1 2 3 4 4 2 2 5 1
FC2 5 3 4 5 3 4 5 2
FC3 2 4 3 3 5 4 3 2
FC4 2 3 1 5 5 3 5 2
FC5 2 3 2 5 4 3 3 2
FC6 0 0 1 1 1 1 1 1
FC7 1 1 1 1 1 0 1 1
FC8 1 1 1 2 1 0 2 2
FC9 1 1 1 2 1 1 1 1
FC10 1 1 1 2 1 1 1 1
FC11 1 2 1 2 1 0 2 1
Table 2: BPMS classification according to their modeling paradigms.
BPMS / Paradigm Constraint based Rule based Case handling Adaptive Process management Total
DECLARE yes yes 2
EsProNa yes 1
Jrules yes yes 2
AritaFlow BPM suite yes 1
Philharmonic Flows yes 1
ProdProc yes 1
jBPM yes 1
Flower yes yes 2
Total 5 3 2 1
= (FC
, FC
, FC
, ..., FC
We define the similarity score for each system as
follows: SIM
i j
where sim
i j
= d
, FC
) Next, we do
the sorting of the S
according to the calculated simi-
larities. SORT
= sort
where i [1, n]
4.5 Algorithm of Classification of
We consider the following steps in order to calculate
the paradigms flexibility measurement score for each
Calculate for each BPMS the similarity score
(SIM) (as done in the algorithm for classification
of BPMSs).
Sum the similarity scores if the BPMS belongs to
the paradigm.
Compare the flexibility measurement scores of the
different paradigms.
Algorithm 2. Here we consider an additional set P of
considered paradigms. Let n be the number of studied
systems, m the number of studied paradigms, NCR be
the number of studied flexibility criteria.
Furthermore let S = (S
, S
, S
, ..., S
U = (FCU
, ..., FCU
= (FC
, FC
, FC
, ..., FC
P = (P
, P
, P
, .., P
Each S
belongs to one or more paradigms. We
define the paradigms’ flexibility measurement score
(PFMS) for each paradigm as follows:
i f S
0 otherwise
Next, we do the sorting of the S
ing to the calculated similarities. SORT
where j [1, m]
The approach conducted in this research work is sup-
ported and tested by a corresponding tool implemen-
tation. Therefore, we did not develop a tool from
scratch. Whereas, we expanded it upon an existing
open-source solution which is the ProM tool, in its
latest version 6.4 (Verbeek et al., 2010a).
The starting point is a spreadsheet-based (MSEx-
cel) document that contains the results of the ques-
ENASE 2017 - 12th International Conference on Evaluation of Novel Approaches to Software Engineering
Figure 3: BPFlexGuide architecture.
tionnaire (which were presented in Tables 1 and 2). In
order to allow for further implementation in the ProM
tool, it has to be transformed to a data structure that
conforms to the eXtensible Event Stream (XES) for-
mat (Verbeek et al., 2010b). XES is an XML-based
format for storing structured data such as event logs
and the standard input format for ProM (as of Version
6). The conversion is performed in the first stage us-
ing Disco1: another import and data-exchange ProM
plugin (G
unther and Rozinat, 2012). As shown in
Figure 3, this XES document serves as an input to
our BPFlexGuide. When starting BPFlexGuide, an
internal repository of all the BPMSs’ flexibility crite-
ria is constructed. This is done when extracting the
BPMSs’ flexibility criteria for each BPMS from the
XES document. The BPMSs’ flexibility criteria have
been implemented as classes. The configuration of all
the BPMSs and the paradigms is then conducted.
Next, the user can pick, from a list, the flexibility
criterion which best fits her/his needs on flexibility.
The provided user interface allows configuring user
needs on flexibility (based on the taxonomy of Regev
et al. (Regev et al., 2006)). Her/his choices are then
We have implemented the algorithms presented in
the previous section. The result of the execution of
these algorithms is the ranking of the different BPMSs
and of the modeling paradigms. Finally, these results
are shown to the user. In case the same ranking is
obtained for two BPMSs, the user picks one of them.
Adopting BPM technology in the healthcare sector
is starting to address some of the characteristics of
healthcare processes, including their high degree of
flexibility (Lenz and Reichert, 2007). Hence, health-
care domain requires high flexibility (Kirchner et al.,
2013). Therefore, this section shows the result of the
BPFlexGuide plugin applied to the EC process. The
goal of the case study was to elicit flexibility needs of
an EC process and to help users to select most ade-
quate paradigms and BPMSs that best suit the needs
in terms of flexibility.
6.1 Eliciting Flexibility Needs in the
Emergency Care Process
In this work, we are going to consider the EC process
which initiates with the patient registration and ends
with her/his discharge of the emergency department
of Farhat Hached hospital. The EC process was ana-
lyzed and modeled at first in (Kirchner et al., 2013),
using the BPMN language.
The main technique used to elicit flexibility needs
on the EC process was interviews. The target group of
the respondents of these interviews was professionals
who are working in the EC process. Table 3 resumes
the answers of the respondents towards the taxonomy
of Regev et al.. Regarding the abstraction level of
modeling, when asking physicians this question ”¡Do
changes affect all the patients or only one patient?”¿.
They held that the changes concern neither only one
patient nor all the patients. Regarding the dimensions,
our study focused on the five known dimensions de-
fined in the Regev et al.s taxonomy which are the
functional, operational, behavioral, informational and
organizational dimensions. Interviewees believe that
it would be useful to know about the functional per-
spective. For instance, it would be important to intro-
duce or remove some activities of the EC process.
Concerning the operational dimension, intervie-
wees think that a change in the process level does not
require the review of the implementation of applica-
tions of information technology that are used in the
emergency department. Respondents answered that
changing the order of activities can affect changes in
the EC process. Thus, they affirm that it is very useful
to focus on the behavioral perspective when modeling
the EC process. For the informational perspective, re-
spondents believe that it would be very important that
changes concern the emergence of new types of in-
formation or data that can be exchanged between the
different actors involved in the EC process. Concern-
ing the organizational perspective, interviewees see
that it would be useful that the changes also concern
the roles associated to process activities. Concern-
ing the properties of change, according to intervie-
wees, changes in the model concern the entire model
in some cases. For instance, the model could be to-
tally changed through the effective implementation of
A Guidance System for Business Process Flexibility
Table 3: Flexibility needs of the EC process, according to
Regev et al.s taxonomy.
Criteria Responses
FC1 2
FC2 0
FC3 3
FC4 4
FC5 3
FC6 0
FC7 0
FC8 2
FC9 1
FC10 1
FC11 2
the disaster plan.
Changes can also concern a part of the model.
This can occur, for example, in the cases of conta-
gious or mental diseases. Regarding the duration of
change, changes in the EC process should be tempo-
rary. They should occur in a limited interval of time
(even for months). Because of patient’s needs of im-
mediate care, the changes should be immediate. They
should not be delayed in time. In addition, intervie-
wees believe that the plans must be developed and
must be planned well in advance. However, actions
can occur at unexpected times. To sum, regarding
the anticipation of change, both planned and ad-hoc
change has to be provided.
6.2 Applying our Guidance Approach
to the EC Process
After eliciting the roles and causes for changes in
the EC process, and deriving the associated flexibility
needs, we used this information to advise on a possi-
ble BPMS/tool to be used. Our BPFlexGuide offers a
classification of the selected paradigms: constraint-
based, rule-based, case handling and adaptive pro-
cess management. This classification could be gen-
eral (i.e. taking into account all the dimensions) or
specific (taking into account one of the three dimen-
sions of the taxonomy of Regev et al.). Regarding the
specific classification, the constraint-based paradigm
was retained as the first one that is the most suitable
for the EC process users’ needs which are presented
is the previous section. The second paradigm is the
rule-based paradigm. The case handling paradigm
was held as the third paradigm. Finally, the adaptive
process management paradigm was classified as the
last one.
Using the BPFlexGuide plugin, we have entered
the flexibility needs of the EC process. The goal of
the case study was to help process participants and de-
cision makers to choose the most appropriate BPMS
that best fit their needs on flexibility.
The plug-in provided, as output, a ranking of the
most suitable BPMSs that can be adopted. Specifi-
cally, the BPMSs had also been ranked according to
the three dimensions of the taxonomy of Regev et al..
We notice that the different BPMSs got various rank-
ings. As a result, EC process modelers were guided to
use the ADEPT2/ AristaFlow BPM suite BPMS first,
jBPM and ESProNa second. In this work, we model
the EC process using the AristaFlow BPM suite. The
AristaFlow BPM suite allows thus for a high degree
of flexibility during process execution. It provides a
complete set of high-level change patterns for defin-
ing ad-hoc deviations. Users may dynamically add
new activities or jump forward in the flow of control.
We provided in this paper a framework for guid-
ing users to choose the most appropriate BPMSs and
paradigms that fit best their needs on flexibility. In
this sense, it can be used to help practitioners (i.e. pro-
cess analysts, designers, engineers and users) and aca-
demics to select the BPMSs and paradigms according
to their BP flexibility needs.
The proposed approach included the use of a ques-
tionnaire for BPMS providers, the classification of
these BPMSs according to a flexibility taxonomy,
as well as the BPFlexGuide tool that could suggest
matches between flexibility needs of a process and
the most suited BPMSs. We validated our approach
by choosing the EC process. The reason for choosing
this kind of BP is in fact due to its important need of
The obtained results from our BPFlexGuide tool
for this case study indicated that the constraint based
paradigm is the most adequate modeling paradigm,
and the recommended BPMS was the AristaFlow
BPM suite. Consequently, we modeled the EC pro-
cess with AristaFlow BPM suite BPMS. We consider
that the obtained model offers in fact a high degree of
We can conclude that these evaluation results are
then promising. The advantages of such an approach
consist in providing better quality models and more
precisely models enabling flexibility. Although vali-
dation of our approach was achieved by using a flex-
ible emergency care process, we intend to apply it to
other BPs and organizations with different flexibility
needs. Examples include, for instance, organizations
from the engineering and industry fields or higher ed-
ENASE 2017 - 12th International Conference on Evaluation of Novel Approaches to Software Engineering
ucation domains. These may imply including other
flexibility needs that are not covered by the BP flexi-
bility taxonomy that we adopted in this proposal.
Many issues are still open and can be subject
of future work. First, we are planning to general-
ize the use of the BPFlexGuide tool also to BPMS
providers, in order to allow them to fully character-
ize their BPMSs through the use of the tool. Inte-
grating other dimensions into the provided process
guidance is technically possible. Besides, it would
be more adequate to accept intermediate values be-
tween 0 and 1. This could be ameliorated using fuzzy
logic. The challenges here include not to overload
BPMS providers and users with flexibility criteria,
and also to score BPMSs according to different BP
flexibility taxonomies. Moreover, we plan to pro-
pose a post-validation approach for the BPMS rec-
ommended by our BPFlexGuide tool. This will im-
ply measuring the flexibility of BPs modeled and ex-
ecuted in that recommended BPMS, by counting the
number of changes that a user needs to perform in
those processes (using that BPMS) to achieve the de-
sired flexibility.
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A Guidance System for Business Process Flexibility