ENHANCING COLLABORATION IN BUSINESS PROCESS
MODELLING
Nikos Karacapilidis and Emmanuel Adamides
IMIS Lab, MEAD, University of Patras, 26500 Rio Patras, Greece
Keywords: Collaborative Business Process Modelling, Argumentation, Simulation, Knowledge Management
Abstract: Business process modelling is widel
y considered as the most critical task in the development of enterprise
information systems that address the actual needs of a company. As business processes cross functional and
sometimes company boundaries, the coordinated inclusion of diverse perspectives and knowledge sources is
necessary. Towards this end, this paper presents an information systems framework that aims at the
exploitation of personalised knowledge through a structured process of collaborative and argumentative
business process model construction. By integrating an argumentation system that is specific to business
process modelling with a discrete-event modelling simulation tool, we provide the appropriate infrastructure
to increase the productivity and effectiveness of process design and re-engineering efforts. The paper
presents the design rationale, the structure and the functionality of the proposed framework through a
comprehensive example of collaborative work towards building a model of a typical business process in a
manufacturing company.
1 INTRODUCTION
To respond to the e-business challenge,
organizations need to gain a better understanding of
their business models and the existing information
technologies and applications. As noted in
(Jayaweera et al., 1999), new ways of working, new
forms of organization and new business models are
emerging to efficiently and effectively carry out e-
business transactions. Intra- and inter-organizational
collaboration is certainly an issue that needs to be
carefully addressed in the above transformations. At
the same time, information technologies are
progressively getting more business-centric, in that
they promote a more situational understanding of
communication and organizational changes
(Hirschheim et al., 1995). The aim of these
developments is to achieve an easier mapping of the
business processes into an information system, while
ensuring a rapid, reliable and low cost information
supply.
Towards this end, the first and most critical step
is to
model the existing organisational processes
with as much accuracy as possible. The modelling of
business processes, however, is a highly complex
task that has to clearly define, enable and manage
sources of information from both within the
organization as well as beyond its boundaries. In
addition, it has to address the totality of related
issues, such as process development and
deployment, execution, administration, monitoring
and reporting. Moreover, it has to reflect the
organization’s strategy and its relationships with
other organizations by integrating entire business
processes not only within the specific organization,
but also with their customers, suppliers and business
partners. Due to the above complexity, business
process modelling needs to be supported by
advanced information technology in its multiplicity
of aspects, such as the collection and dissemination
of information and knowledge produced by diverse
sources, the evaluation of alternative schemes, the
construction of shared meaning, and the feedback
learning processes (Clases and Wehner, 2002;
George et al., 1992). Since most processes cross the
boundaries of a single function, they can only be
considered in their entirety by exploiting the
collective cross-functional knowledge and
experience through an apparent process of
constructive discussion and collaboration among the
parties (managers) involved, as well as through
mechanisms that organize and maintain the shared
context of the issue. Modelling is a decision-making
process itself; as knowledge and experience reside in
a diverse set of organizational assets (including
employees, structure, culture and processes), a
403
Karacapilidis N. and Adamides E. (2004).
ENHANCING COLLABORATION IN BUSINESS PROCESS MODELLING.
In Proceedings of the Sixth International Conference on Enterprise Information Systems, pages 403-410
DOI: 10.5220/0002634604030410
Copyright
c
SciTePress
consistent approach for synthetic, problem-specific
use of tacit and codified knowledge for its
accomplishment is required. This advocates the
synergy between the decision support and
knowledge management processes of the
organization. Decision-making processes generate
new knowledge. For instance, the evidence that
justifies or challenges an alternative to a specific
business modelling problem, and the practices to be
followed or avoided after the evaluation of the
decision provide a refined understanding of the
problem. On the other hand, knowledge
management activities, such as knowledge
elicitation, representation and distribution influence
the creation of the decision model to be adopted,
thus enhancing the decision making process (Bolloju
et al., 2002).
A series of methodologies and systems has been
suggested in the literature to address the issue of
collaborative business modelling. The majority of
them concentrate on static, conceptual or activity,
models for visualisation purposes (e.g. CM (Sierhuis
and Selvin, 1996), or on how to combine simulation
models developed by different parties (e.g.
Sarjoughian et al., 2000; Miller et al., 2001). Only a
limited number of efforts has been reported towards
the collaborative development of business process
simulation models, which pay particular attention on
the collaboration process itself and its associated
social and knowledge construction dynamics
(Taylor, 2001).
The approach proposed in this paper extends the
latter stream of research by presenting an IS
framework for distributed and asynchronous
collaborative process simulation modelling. It aims
at strengthening the abovementioned synergy of
knowledge management and decision making by the
integration of argumentation and experimentation in
the process of understanding how an organisation
works and how it can be better supported by
information technology. The need for argumentation
is ubiquitous in most collaborative decision making
problems that can be solved through debate and
negotiation among a group of people. In such
contexts, conflicts of interest are unavoidable and
support for achieving consensus and compromise is
required. Each decision maker may formulate and
put forward his own (part of a) business model that
fulfils some goals at a specific acceptance level.
Moreover, he may have arguments in favour or
against alternative solutions, as well as preferences
and constraints imposed on them. Depending on the
role and the goals of each decision maker, subjective
estimates of the problem should be taken into
consideration. Independently of the model used for
the necessary decision making, argumentation is
valuable in shaping a common understanding of a
complex issue, such as a business process in its
entirety. It provides the means to decide which parts
of the information brought up by the decision
makers are of any use or should be discarded.
Furthermore, it has been shown that argumentation
may stimulate the participation of decision makers
and encourage constructive criticism (Karacapilidis
and Papadias, 2001).
On the other hand, in-vitro experimentation is the
missing part of many process design tools, not
paying the necessary attention to the phase of
process evaluation under different scenarios. In
conjunction with a discourse-based decision support
environment for business modelling, a simulation
model can map organizational knowledge onto
appropriate graphs, thus quantifying the problem
under consideration and providing a clearer
understanding of which alternative solution seems to
be more prominent at the moment. Moreover, it can
provide the means for an individual to conceptually
define a proposition and perform experiments with
(before asserting it as a dialogue item in the
modelling process). Taking into account the current
state of a discourse organized in an intelligent way,
individuals may thoroughly contemplate on their
next move to assure that it will have the best impact
to the ongoing discussion.
The remainder of this paper describes the
structure and operation of a platform that integrates
simulation and argumentation into a knowledge-
based tool for collaborative business process
simulation modelling. The paper concentrates on the
modelling phase. More specifically, Section 2
discusses related works highlighting their
contributions on the business modelling area, while
Section 3 illustrates the proposed integrated
framework. Section 4 presents the features and
functionalities of our approach by means of an
illustrative example. Finally, Section 5 concludes
the paper and outlines future work directions.
2 RELATED WORK
Real-life business process modelling may be
undertaken by a group of people, who represent
different units of the same or different organizations.
In this way, the diversity of perspectives and the
completeness of the model are augmented. However,
different people usually have different and probably
contradicting perspectives. Argumentative discourse
provides the means to accommodate different views
in the underlying process of considering,
coordinating and evaluating activities. Reaching a
high quality team decision requires thorough and
accurate understanding of the problem, marshalling
ICEIS 2004 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION
404
a realistic and acceptable range of alternatives and
careful consideration of the positive and negative
consequences that are associated with each
alternative considered (Hirokawa, 1992). In
addition to a well structured discourse output that
clearly addresses “know-what”, “know-why”,
“know-how” and “know-who” issues, the
precautionary manipulation of competing or even
conflicting problem interpretations, interests,
objectives, priorities and constraints leads to the
objective evaluation, synergy, stimulation and
construction of new knowledge. In this respect,
maximum exploitation and enhancement of the flow
of the underlying organizational knowledge are two
crucial requirements for efficient and effective
decision making in building a business process
model.
From the knowledge management perspective,
we can distinguish two different strategies towards
increasing the quality of business processing
modelling. The first addresses the codification of
knowledge by providing richer modelling
formalisms, whereas the second is focused on the
rigorous exploitation of personalised knowledge
(Hansen et al., 1999). In the context of the first
perspective, approaches originating from the area of
information systems development, such as the life-
cycle and the structured paradigm, or even
Prototyping and Rapid Application Development,
have been extremely criticized in that they do not
provide a sound understanding of business processes
and organizational change. To remedy this, new
methodologies emphasizing what people do while
communicating, how they create a common reality
by means of language and how communication
brings about the coordination of their activities (van
Reijswoud et al., 1999), have been proposed. These
have been basically founded on the
Language/Action perspective (Dignum et al., 1996)
and the Speech Act Theory (Searle, 1969), and
consider the utterance of various types of
communicative actions as the backbone of the
business process models.
More specifically, the Business Design Language
(Medina-Mora et al., 1992), based on the
Conversation for Action theory (Winograd and
Flores, 1986) that was conceptualized as an interplay
of requests and commitments during a collaborative
process, has as its basic modelling unit the so called
four-step action workflow protocol. SAMPO
(Auramäki et al., 1988) views organizational
activities as a series of speech acts that create,
maintain, modify, report and terminate
commitments, aiming at detecting the principles
needed in the set-up and control of commitments,
the inconsistencies in the coordination of
commitments and the possibilities for organizational
development that simplify communication and
control mechanisms. Business Action Theory
(Goldkuhl, 1996) has been proposed as a generic
model of business communication that explains
business processes as action and interaction, and can
be used as an interpretative framework for business
process reconstruction, evaluation and redesign.
Finally, DEMO (Dynamic Essential Modelling of
Organizations) provides a domain-independent
theory that describes and explains the
communicational dynamics of an organization
together with a modelling facility based on it (van
Reijswoud et al., 1999). DEMO considers the
business transaction as its key concept and views the
functioning of an organization from three levels,
namely the documental level, where the organization
is considered as a system of operators producing,
forwarding, storing and deleting documents, the
informational level, where the organization is
regarded as a system of processors that send, receive
and transform information, and the essential level,
where the organization is conceptualized as a
network of interrelated business transactions, which
in turn are composed of interrelated communicative
acts.
The above methodologies concentrate on the
representation of knowledge, but they do not
consider the knowledge creation process which is a
far more important issue. No matter how a richer
modelling formalism is used, if the process-related
knowledge is limited or incorrect, the model does
not correctly represent the real process.
On the other hand, IS infrastructure to support
people working in teams has been the subject of
interest for quite a long time. Such systems are
aiming at structuring group decision-making
processes and helping group members in reaching a
shared understanding of the issue by supporting
knowledge elicitation, knowledge sharing and
knowledge construction. Moreover, they exploit
intranet or internet technologies to connect decision-
makers in a way that encourages dialogue and
stimulate the exchange of tacit knowledge.
Representative systems falling in this category are
QUESTMAP (Conklin, 1996), EUCLID (Smolensky
et al., 1987), JANUS (Fischer et al., 1989), SEPIA
(Streitz
et al., 1989), QOC (Shum et al., 1993),
SIBYL (Lee, 1990), and BELVEDERE (Suthers,
2001). One can also add here attempts to use
Microsoft’s Netmeeting as a platform for combining
a chat-based dialogue with a simulation tool to
facilitate developer-client interactions during the
modelling process (Taylor, 2001), as well as
attempts to use tools of this category in connection
with static models (e.g. QUESTMAP in CM
(Sierhuis and Selvin, 1996)).
ENHANCING COLLABORATION IN BUSINESS PROCESS MODELLING
405
With respect to business process modelling, all
the above works provide limited knowledge
management and decision-making support. Business
process modelling is a social process, and as such it
results in the formation of groups whose knowledge
is clustered around specific views of the problem.
Aiming at providing an integrated approach, this
paper presents a web-based system that provides
teams engaged in business process modelling with
the appropriate means to collaborate towards the
solution of the underlying issues. In addition to
providing a platform for brainstorming and
capturing organizational memory, our approach
augments teamwork in terms of knowledge
elicitation, sharing and construction, thus enhancing
the quality of the resulting model. This is due to its
structured model-specific language for conversation
and its mechanism for evaluation of alternatives.
Taking into account the input provided by the model
builders, the system constructs an illustrative
knowledge graph that is composed of the ideas
expressed so far, as well as their influence
connections. Moreover, through the integrated
simulation environment, discussants are able to
evaluate the model under construction by using
different performance measures.
3 THE OVERALL FRAMEWORK
Adopting the general systems view of an
organisational process, we consider entities,
activities, resources and decisions as the basic
building blocks used in collaborative business
process modelling (BPM). The architecture of our
framework is illustrated in Figure 1. The Discourse-
Based BPM Graph module provides users with the
appropriate structured and task-specific interface to
express their beliefs towards the construction of a
business process model in a modelling tool-
independent way. More specifically, users are able
to put forward positions regarding the activities that
are to be considered, their topology, the decision
points needed, and the resources involved.
Discussion about activities may be further extended
by placing positions conveying information
regarding their processing time, cost, requirements
for queues which may exist in front of them etc. In a
similar way, discussions about resources may be
further refined with the supply of information
regarding their type (i.e., consumable or not), the
activities they are used in, etc. For each of the above
BPM objects, users may also provide links to related
data and knowledge sources, such as MS Office or
Adobe Acrobat documents, html or xml files, etc.
Figure 1: The proposed BPM framework.
For the graph items, users are able to assert
arguments speaking in favour or against them. For
instance, a user x may insert an argument that further
validates his position about a certain decision point;
the same user may also put forward an argument
against an alternative decision point, which has been
earlier submitted by a user y. Argumentation may be
carried out in multiple levels, upon users’ wish. The
procedures that are responsible for the construction
and maintenance of the discourse graph build on the
functionalities of Hermes (Karacapilidis and
Papadias, 2001), a fully implemented web-based
system that supports argumentative discourse and
decision making.
On the other hand, the BPM Experimentation
Module builds on a commercial simulation tool,
namely Extend (
www.imaginethatinc.com), and
provides users with the appropriate interface to see
the progressive construction of the model. It should
be noted here that other process modelling and
simulation environments can be easily employed.
The construction of the model is undertaken by a
user (facilitator) who is proficient in the use of the
specific modelling environment. He constructs the
model by taking into account the current state of the
argumentation (Discourse-Based BPM Graph). The
other participants can load copies of the model and
experiment with them at their own pace. This
implicitly provides the means for data and
knowledge acquisition at any instance of the overall
process. Having considered the current status of the
discourse graph, users may contemplate and shape
their tacit or explicit knowledge according to the
model built so far. Then, they may either directly
“load” their input in the discourse or evaluate it
further by using the integrated experimentation tool.
In other words, users are able to make a series of
experimentations by simultaneously considering the
current status of the graph and the contributions they
intend to make. By analyzing the corresponding
results, they are able to explore the potential and the
dynamics of their contribution before putting it in
the graph and “share” it with their peers.
Obviously, the BPM Experimentation Module
can be deployed at any time, thus enabling
participants to get a quantified representation of the
ICEIS 2004 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION
406
current outcome of the discussion. The module
supports an extensive range of graphing and
visualization features for a clear and easy reflection
on the parameters of the model being considered.
The system’s Knowledge Base keeps an archive
of the position-based knowledge submitted so far
during the design and re-engineering of the business
process models of the company. Such knowledge
integrates information about the objects of the
business process model per se (i.e., activities,
resources, topologies, processing costs, etc.) with
information concerning the argumentative discourse
and the experimentations carried out around them.
This is handled through the definition of a specific
BPM ontology. Due to space limitations, this issue is
not comprehensively discussed in this paper. We
only mention here that at the current stage of the
system’s implementation, the above information is
stored in XML (eXtensible Markup Language).
Since XML does not fully support ontology
management issues, we are in the process of
considering alternative solutions. Probably, the most
promising one at the moment is BPML (Business
Process Modelling Language), which is actually an
XML Schema that provides a standard way to model
business processes. BPML has been proven to
enable the efficient handling of business process
modelling issues such as business rules, security
roles, distributed and compensating transactions, and
exception handling (
www.bpmi.org/bpml.esp).
The system’s knowledge base is actually the
place where the organizational knowledge regarding
business processes of the company is developed and
maintained, and serves storage and retrieval
purposes. Storage of positions being asserted in the
overall process takes place in an automatic way, that
is upon their insertion in the Discourse-Based BPM
Graph. On the other hand, retrieval of knowledge is
performed through appropriate interfaces, which aid
users explore the contents of the knowledge base
and exploit previously stored or generated
knowledge for their current needs. For instance,
when a user intends to argue about the modelling of
a particular process block, he may retrieve pieces of
knowledge concerning the performance of this very
block in an already constructed and validated
business process model, thus further justifying his
arguments.
4 AN EXAMPLE OF USE
This section presents the features and functionalities
of the proposed BPM framework through an
example concerning the modelling of a typical
“order fulfilment” process. Three managers, namely
the Sales Manager, the Factory Manager and the
Warehouse Manager, are involved in the above task.
The main window of Figure 2 (top left) illustrates an
instance of the related BPM graph. As shown,
managers have put forward their views (pieces of
knowledge) concerning the activities, resources,
topology, and decision points involved in the
process under consideration, the aim being to
“shape” the model that clearly represent the actual
process of the company. Referring to the activities of
the process, the Sales Manager had initially claimed
that “Order Processing” and “Dispatch from
Warehouse” are two necessary units; then, the
Factory Manager added “Production” as a third one.
The insertion of items related to the resources takes
place in a similar fashion. In the instance shown in
Figure 2, the resources proposed so far are “Office
Employee”, “Warehouse Employee” and “Fork
Lift”. Insertion of items related to the topology of
the model is accomplished through an appropriately
designed interface that keeps a dynamic list of the
activities proposed so far and enables users to easily
specify their order (i.e., to express knowledge of the
form “[activity_1] precedes [activity_2]”). In the
instance shown, the items “[Order Processing]
precedes [Dispatch from Warehouse]” and “[Order
Processing] precedes [Production]” have been
submitted by the Sales Manager and the Factory
Manager, respectively. Finally, insertion of items
related to the required decision points is also
performed through a user-friendly interface. In this
case, users have to specify when a decision should
be made. To do so, they “construct” an item by
employing the temporal relations holding among
activities (e.g., after, before, in parallel, etc.), as
well as logical operators (e.g., AND, OR, NOT, etc.).
The only such item submitted in our example
declares that a decision point is needed after the
“Order Processing activity and before the
activities “Dispatch from Warehouse” and
“Production”.
As noted in Section 3, users are also able to
argue in favour or against each graph item.
Exploiting this feature, the Factory Manager has
asserted the argument “There are orders that cannot
be fulfilled from stock” to further justify his
previously inserted position about the need of a
“Production” activity. Note that the Sales Manager
has also submitted the argument “We do not
produce to order; we group orders”, which actually
speaks against the need of inclusion of the
“Production” activity in the model under
construction. To defeat this last statement (and
resolve the misunderstanding of the Sales Manager),
the Factory Manager submits the argument “The
model should show how a SPECIFIC order is
fulfilled”. According to the underlying
ENHANCING COLLABORATION IN BUSINESS PROCESS MODELLING
407
Fi
g
ure 2: The interface of the discourse-
b
ased BPM
g
ra
p
h.
argumentation’s formal dialectics (for details, see
(Karacapilidis and Papadias, 2001)), the argument
“We do not produce to order; we group orders” is
now defeated and it is consider as “inactive”.
Graph items corresponding to activities and
resources are accompanied (at the end) by a
“magnifying glass” icon. By clicking on it, users
may both view the existing (more detailed)
information about the item and further refine it. For
instance, by clicking on the icon of the “Order
Processing” activity, the window appearing in the
bottom part of Figure 2 pops up, where pieces of
knowledge related to various characteristics of this
activity, such as its cost and processing time, are
shown. As in the main BPM graph, users may also
submit here arguments and alternative positions. In
the instance shown, the position “As in METHODS
S.A. report” has been defeated by the argument
“The report is based on last year’s salaries”, thus
the only position that stands for the activity’s cost is
to “Use data from METHODS S.A. report inflated
by 8%”. Similar features and functionalities are
provided for resources. The middle window of
Figure 2 pops up when a user clicks on the
“magnifying glass” icon of the resource “Warehouse
Employee”.
The information layout in the windows provided
by the BPM graph module can be modified upon a
user’s wish. There are buttons serving folding and
unfolding purposes, thus enabling one to concentrate
on the model’s part that he is interested in. This is
particularly useful in models of considerable length
and complexity. In addition, information about when
and by whom each graph item has been submitted
can be either shown (as in Figure 2) or hidden.
Based on the outcome of the dialogue shown in
Figure 2, the facilitator constructs the business
process model in the experimentation environment
(Figure 3). This model consists of the building
blocks discussed in the BPM graph as well as of
additional simulation-specific blocks, which may be
the subject of additional dialoguing (e.g., what is the
rate of order arrivals).
5 CONCLUSIONS
We have presented a framework for collaborative
business process modelling that offers a series of
argumentation and experimentation features to the
users involved. Through the interfaces provided,
users are able to deploy and share their knowledge,
the aim being to design the business model that suits
best to the requirements of the company.
Experimentation and argumentation have been
ICEIS 2004 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION
408
Fi
g
ure 3: The BPM Ex
p
erimentation module interface for the
p
rocess shown in Fi
g
ure 2.
considered as two complementary mental processes
that increase the quality of organizational decision
making while, at the same time, contribute to the
creation and maintenance of organizational
knowledge. We argue that the overall approach
provides users with the appropriate means to
overcome motivational (Davenport and Prusak,
1998) and cognitive (Huber, 2001) problems, which
are ubiquitous in team work settings. The BPM
graph and experimentation modules are easily
conceived and motivate participants for creative
knowledge sharing and evaluation.
The proposed framework is currently evaluated
through a series of real cases of process design and
re-engineering. Preliminary results show that its
adoption aids participants to define, understand,
document, analyze and improve business processes
through the visual process representation diagrams.
In addition, the interrelation of a business model’s
components is proven to be simple and easily
comprehensible, while participants may also check
their proposals for validity, correctness and
completeness. More significant, the framework
provides the means for effective communication on
what is the current process and where improvements
are possible, and enables all parties share a common
understanding.
Future work is directed towards the automation
of the inter-process communication (IPC) of the
BPM graph and experimentation modules. This will
be based on Extend’s connectivity abilities through
blocks that utilize the system’s IPC functions,
ODBC (Open DataBase Connectivity), embedded
ActiveX or OLE (Object linking and Embedding)
objects and DLL (Dynamic-Link Library).
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