Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement

 
 
Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement
Prilla, M. (2010): Models, Social Tagging and Knowledge Management? A fruitful Combination for Process Improvement. In:
Proceedings of 2nd Workshop on Business Process Management and Social Software in Conjunction with the Business Process
Management Conference 2009.




                  Models, Social Tagging and Knowledge Management –
                   A fruitful Combination for Process Improvement

                                                       Michael Prilla

                                           Information and Technology Management
                               Institute for Applied Work Science, Ruhr University of Bochum
                                        Universitaetsstr. 150, 44780 Bochum, Germany
                                                     michael.prilla@rub.de



                     Abstract. Process Models are the tools of choice for capturing business
                     processes and communicating them among staff. In this paper, an approach
                     focusing support in creation and usage as well as the dissemination of process
                     models in organization is described, intending to improve business processes.
                     To accomplish this, the approach makes use of social tagging as an approach to
                     integrate process models into knowledge management (KM). In the paper, the
                     empirical foundation of the approach is described and a corresponding
                     prototype implementing a tagging mechanism for process models is discussed.
                     Topics: New possibilities for the design of business processes by social
                     software (1), phases of the BPM lifecycle affected by social software (2), use of
                     social software to support business processes and new kinds of business
                     knowledge representation by social production (3).



              1    Introduction: Processes, Models and Knowledge Management

              Process models are well-established tools in business. They capture business
              processes as well as related knowledge and are used for a multitude of purposes [6].
              However, the active usage of process models in organizations is usually limited to a
              small group of people and models are usually not well known as resources in
              organizations [22]. This paper argues that the dissemination of models and their active
              use by more users can help to get input from those both interested and competent
              enough to improve processes: people involved in the conduction of processes [24].
                 The value of models aside from being expert tools for the documentation, creation
              and maintenance of processes in organizations is widely neglected. It can be found in
              models capturing knowledge related to processes, mediating its acquisition [15] and
              helping to solve related problems [17]. Nevertheless, because of poor findability and
              acceptance of models [20], they are scarcely used. Additionally, modelling as a
              knowledge intensive task [22] can obviously benefit from KM providing relevant
              information and a context for understanding [17].
                 Therefore, research questions concerned with the work presented here are which
              needs are imposed by the current situation of neglected process models, how these
              needs can be diminished and how the support needed can be implemented.
Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement
2   Michael Prilla


   Overcoming scarce usage and supporting model creation mean shifting attention
towards models and intertwining them with other content. In this paper I argue that
this can be done by semantic integration of process models into KM. In a previous
analysis, formalized semantics were identified to not suit the needs of this purpose
[22]. Therefore, I use social tagging for models and other content in order to abstract
from content types and focus on relevance instead in KM.
   To reach the goals described above, models as the best way to capture processes
[4], [10] have to be considered an important factor in process improvement. This is an
observation backed up by earlier findings on the role models play in business process
improvement [12]. I argue that the approach presented here provides a step towards in
making models artefacts of everyday use and therefore helps to improve business
processes. The approach contributes to the improvement of business processes in
multiple ways. First, social tagging provides access to processes for all stakeholders
and thus disseminates models in organizations. Second, by making people aware of
models, it increases the chance that those formerly excluded will give valuable
feedback to business processes. Third, it supports the creation of models by providing
relevant information and therefore improves the quality of models and processes.
   The concept of the approach has been described in [20] and basic requirements of
it have been presented in [22]. This paper focuses on an empirical study to analyze
tasks and respective requirements. As an outcome of that, the paper presents a
prototype of process model tagging, which is tailored to the needs found in the study.
In what follows, section 2 gives an overview of the approach‟s background. In section
3, the empirical study is described and the resulting fields of support are analyzed for
requirements. Section 4 then describes the prototype. The paper concludes with a
discussion of related work (section 5) and an outlook to further work.


2    Social Tagging for the Integration of Process Models into KM

Knowledge Management aims at “capture, validation, and subsequent technology-
mediated dissemination of valuable knowledge from experts“[3]. This aim makes no
difference between content types. Thus, if knowledge is supposed to be shared, we
should not rely on separate systems for different content, and we should not favour
one content type over the other, be it text or models. The current situation of KM
favouring textual content while neglecting process models and the existence and
usage of specialized management tools for models counteracts this demand. Thus, we
should aim for an integrative solution capitalizing on the potential of models in KM.




             Fig. 1. Potential of process models in KM (adapted from [19]).
Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement
Models, Social Tagging and Knowledge Management – A fruitful Combination for Process
                                                                      Improvement       3

   The potential benefits of process models being visible and accessible in KM
applications is grounded in the distinction of tacit and explicit knowledge [18]. Tacit
knowledge is in the head of people and not codified anywhere, whereas explicit
knowledge is formalized by e.g. writing it down. In Fig. 1, this distinction and the
transitions between knowledge being tacit or explicit are shown with respect to the
potential benefits of models in KM. First, as shown in the upper right corner, models
capture tacit knowledge related to processes. Therefore, neglecting them means
leaving out relevant knowledge. Second (lower left), models should be usable to
acquire process related knowledge. Third, models should be available for users in
order to combine different content types (Fig. 1, lower right), which, as Nonaka [19]
states, is what “can lead to new knowledge”. Neglecting existing model content
hinders this process1. Therefore, the integration of models into KM bears potential for
publicity and improvement of processes in organizations (see also [12]).


2.1      Basic requirements for the Integration of Process Models into KM

Currently, to my knowledge there is no KM system properly supporting process
models as its content. In a prior analysis [22], I found some basic requirements for the
integration of models into KM: First, semantic content description to overcome the
“complexity gap” [22] by providing homogeneous access to different content types
such textual content and process models. Second, semantic content description must
not be implemented at the expense of user effort. Such a mechanism has to provide a
low usage burden while maintaining a high ceiling to provide a sufficient surplus in
content handling. This makes formalized semantics such as Ontologies less applicable
for this task. Third, all stakeholders of processes have to be integrated, bringing
together their perspectives of how process can be improved [24]. Fourth, such
functionality has to be integrated into daily work tasks, meaning that these tasks must
be tightly integrated into existing tools and give users a benefit for their sharing
behaviour [9]. In [22], these requirements are analyzed and as the result of that, social
tagging is proposed as a mechanism fulfilling all requirements.


2.2      Social Tagging for Process Models

The approach to integrate process models into KM proposed here is based on the
mechanism of social tagging. Tagging means assigning unrestricted keywords to all
kinds of content. It becomes social when tags are shared among users and different
users are allowed to tag the same content unit. The key learnings from social tagging
applications are that they provide an easy to use mechanism and the bottom-up
integration of relevant stakeholders [8] with proper means of semantic content
description [7] and make all content accessible despite its immediate popularity.


1   It should be noted that the analysis given above can also be done with similar results for
     systems managing business process models, which prefer models over textual content and are
     usually used by only a small number of people.
Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement
4      Michael Prilla


   Our analysis showed that tagging mechanisms are in applicable to process
modelling tools and impose mediocre technical challenges [20]. Comparing the
characteristics of tagging to the requirements described in section 2.1 shows that
tagging can fulfil each of them. However, questions such as which demands a
resulting approach has to cover and how tagging can be applied to process models
remain unanswered. The remaining paper will be focused on this question.


3       Model Knowledge Usage in Practice: An Empirical View

To analyze the daily practices and KM needs of people using models, a series of six
interviews with practitioners was conducted2. The participants worked in different
business such as call centre organization, public energy supply and software
development. All participants had a graduate degree and their age varied from 36 to
53. With the exception of one interviewee, they had more than ten years of experience
in using models, making them viable candidates for the interviews.
The interviews covered the entire lifecycle of models, including their creation, the
integration of knowledge into models, their exchange, their understanding by users
and their reuse. Afterwards, the interviews were transcribed and a catalogue of codes
was developed out of the resulting material. The interviews were then analyzed
according to patterns of support needed in the work with models and seven fields of
support were identified. In this section, these fields are described and analyzed.


3.1        Observations from Practice: Seven Fields of Support

In the interviews with practitioners, a detailed set of requirements complementing the
basic ones described in section 2.1 could be identified. In this set, the abovementioned
problems of lacking support in model creation and usage, neglected content and
inadequate support for the acquisition of knowledge are present as cross cutting
concerns. The set consists of seven fields of support: creating models, ensuring
understanding and quality of models, using models together, using models for
communication with others, finding and contextualizing models, connecting models
with other content and facilitating and extending model usage. In what follows, these
fields are described including sub-tasks, observations and resulting requirements3.

Table 1. Support field „Creating Models“

    Task                           Observation                       Requirement
    Information   research   and   Hard to find matching content     Provide a means to match available
    integration                    and competent partners needed     content in KM, the current model
                                   during the modelling process.     and expertise.
    Model reuse                    Hard to find similar models for   Provide a means to find models by
                                   reuse.                            content similarity.

2   To ensure anonymity, I will refer to the interviewees as I1 to I6 in this section.
3   Please note that for the sake of brevity, the description of the analysis can only cover a choice
     of observations and requirements here.
Models, Social Tagging and Knowledge Management - A fruitful Combination for Process Improvement
Models, Social Tagging and Knowledge Management – A fruitful Combination for Process
                                                                      Improvement       5

    The first field identified is model creation (Table 1). In the interviews, respondents
mostly reported on information research and its integration into models for the
preparation of modelling as well as model reuse during the modelling process. For the
first task, interviewees described the process of modelling as preceded by collecting
information on the respective processes and that their sources for this are people
working in processes and documents describing the process. They stated that it was
often hard to find the right people or content for the preparation and model reuse:
“(…) for a co-worker in a subsidiary, there is no occasion in which he becomes aware
of models, (…) diagrams drown in the depths of IT” 4 (I2). From a requirements
perspective, model creation and reuse need to be supported by mechanisms to find
relevant content and people. This results in the need to match content available in KM
systems, models and a description of users‟ expertise. Integrating this into everyday
work means coupling such mechanisms with modelling tools.

Table 2. Support field „Ensuring Understanding and Quality of Models“

Task                            Observation                          Requirement
Ensuring Understanding          Hard      to   find    relevant      Provide a means to retrieve
                                information when encountering        information        relevant      for
                                problems in understanding.           understanding.
Assuring Quality                Relevant people for approval         Provide a means to distribute
                                hard to reach.                       models     for    expert    approval
                                                                     according to their content.

In the interviews, participants put an emphasis on means to ensure both
understanding and quality of models for their later use (Table 2). For better
understanding and higher quality of models, they combined models with additional
textual descriptions, named model elements carefully and tried to get their models
approved by stakeholders: “(…) the quality of a model is closely related to the
amount of people that have talked about the model” (I3). However, they felt badly
supported by existing tools in this task: “It would be nice if we could find additional
content for models” (I5). They reported that they had a hard time to reach acceptance
and find people to approve models. These observations result in two requirements.
First, the understanding of models should be fostered by providing relevant content to
users encountering these problems. Second, for approval a mechanism to reach people
both competent and willing to give feedback on a model should be available.

Table 3. Support field „Using Models together“

Task                            Observation                          Requirement
Model exchange                  Task-specific         distribution   Provide a central repository for
                                hinders availability.                models         with      task-specific
                                                                     notifications.
                                Hard to share and sustain            Provide a means for context
                                descriptions of models.              descriptions sticking to models.




4   The statements of interviewees have been translated from German to English by the author.
6      Michael Prilla


Interviewees reported several means they use for the exchange of models (Table 3)
with others such as email, shared folders and content repositories, which worked
reasonably well but had some shortcomings: “(...) and then it is present somewhere,
because you sent it by email and it is bound to a certain sent-folder” (I1). They stated
that it was difficult to properly describe models to make others aware of their
relevance and that additional text in emails was not sufficient as it is bound to the
email and provides no help if the model is used in practice. Most interviewees
reported that the result of this situation is a lack of transparency concerning which
models are available and thus sharing is difficult. From a requirements point of view,
model sharing should be supported by a centrally accessible repository supporting
users willing to share content to point people to models relevant for specific tasks.
Additionally, the description of model content has to be attached directly to models.

Table 4. Support field „Using Models for Communication with others“

Task                              Observation                      Requirement
Using       Models           as   Lacking awareness of models      Make models as findable in
communication artefacts           as information sources           repositories as textual content is.
                                  Notion of models as technical    Provide a content description of
                                  artefacts.                       models in order to demonstrate their
                                                                   relevance.

Most interviewees regarded models as a means for communication (Table 4). They
reported different variants for this, including models as guidance in discussions and
models as a specification for work processes. They also reported that models were not
as frequently used by people as they intended them to be because people were not
aware of models as relevant information or do not accepted them: “(…) they are
mostly regarded as my artefact” (I2). There are two requirements stemming from this.
First, to make people aware of models, they have to be able to find them as easy as
they can find textual content. Second, in order to show that models contain valuable
content the content of a model has to be made explicit to users.

Table 5. Support field „Finding and Contextualizing Models“

    Task                          Observation                      Requirement
    Searching and Finding         Search engines cannot use the    Provide a means to make a model‟s
                                  content of a model.              content description accessible to
                                                                   search engines.
    Naming and structuring        Model names are not sufficient   Provide a means to give content
                                  for describing models.           descriptions    extending   model
                                                                   names.

Interviewees reported that finding and contextualizing models (Table 5) was hard to
accomplish due to the lacking fit of existing retrieval methods. Rather than searching
models for a long time, they would usually redo a model: “if I can‟t find it quickly, I
stop searching” (I3). Even for corporate naming conventions, they stated that they
were of no help: “these conventions should be adapted continuously, but this is not
done properly, making them hard to use” (I4). The basic requirement stemming from
these observations is that if models are to be found, a retrieval engine has to include a
Models, Social Tagging and Knowledge Management – A fruitful Combination for Process
                                                                    Improvement       7

description of their content, which must not rely on proper naming, as „proper‟ is
dependent on both search intention and context. On the contrary, there has to be a
means to provide context information to a model besides its name.

Table 6. Support field „Connecting Models with other Content“

Task                           Observation                        Requirement
Connecting models with other   Manual linkage of content is       Provide a mechanism handling
content                        costly and erroneous.              models and other content equally,
                                                                  identifying possible relationships
                                                                  and proposing them to a user.

Interviewees reported that for the usage of models by others, they need to relate
models and other content to e.g. create the documentation of their work and make it
accessible to others (Table 6). They also reported that this was poorly supported in
their companies and took a lot of time: “I wish there was a more lightweight way of
linking content to models” (I2). This observation raises the requirement of easing the
linkage of models and other content. For this, a mechanism handling models and other
content equally and identifying possible relationships by their content and proposes
these to a user should be provided.

Table 7. Support field „Facilitating and Extending Model Usage“

Task                           Observation                        Requirement
Extending the user group       Scarce usage of models in          Provide a mechanism pointing out
                               organizations.                     models as relevant sources of
                                                                  information.
Supporting target groups       Specific    models      versions   Provide a mechanism to generate
                               needed for each target group.      views from existing models.

Concerning the facilitation and extension of models use (Table 7), the interviewees
stated that models are usually bound to a small group made up by e.g. analysts and
developers. They explained this by the poor acceptance of models and stated that they
needed users to see the relevance of models. Additionally, they reported that they
needed adequate models for different target groups such as clients, developers and
users, but had no tool support for this task: “I don‟t see any need to discuss design
details with a client” (I3). Two requirements result from these observations. First, for
promoting model usage in organizations, people should be supported in perceiving the
relevance of models. Second, it should be possible to generate versions of models for
target groups and provide these versions to them in a KM application.


3.2    Discussion

As can be seen from the analysis above, topics like knowledge acquisition, preventing
the loss of knowledge and supporting the creation and active use of process models
are present in nearly all fields of support. Moreover, the analysis shows the potential
the approach bears for the improvement of business processes. As an example, for
8     Michael Prilla


creating models, it is obvious that if a modeller is provided with relevant information
in preparation and modelling, the quality of the model and the corresponding process
will increase. Other fields of support such as using models for communication or
finding and contextualizing models underpin this – if people in organizations have a
better chance to find models and learn about processes from them, the quality of
processes captured in these models is likely to benefit from their input.


4     Applying Social Tagging in a Modelling Tool

From a technical perspective tagging mechanisms are not hard to integrate into
existing applications due to manageable complexity and their straightforward mode of
operation. After I integrated it in conformance to the requirements [22], it had to be
tailored to the needs of the fields of support described in section 3. To face this
challenge, a series of participatory design workshops was conducted, including
potential users and experts in the field. In the workshops, we iterated through the
fields of support described in section 3. The resulting prototype consists of the
modelling tool SeeMe [13] and the KM application Kolumbus 2 [21]. In what
follows, some features of the resulting prototypes will be demonstrated and related to
the fields of support described above. These features represent a choice of the overall
design and are restricted to the work on the process modelling tool. It should be noted,
however, that tagged process models are analyzed in the KM application, which
possesses a tagging mechanism and corresponding functionality to search and
structure content by tags (see [20] for more details).


4.1    Prototypical Implementation: A Tagging Mechanism for Process Models

The integration of a tagging mechanism into a process modelling tool has to start with
enabling the assignment of tags to process models. Considering the structure of
process models, this has to be done on three levels: elements, groups of elements or
sub-procedures and models. Fig. 2 shows an example for basic tagging support in
process models. In the figure, the element “Action 3.1” is tagged as a single element
and the elements “Action 3.2” and “Action 3.3” are tagged as a group of elements
(indicated by a box around them). While the former is important for the reception of
information from the KM application, the latter provides a means to mark up groups
and share them with others.




                           Fig. 2. Tagging in Process Models.
Models, Social Tagging and Knowledge Management – A fruitful Combination for Process
                                                                    Improvement       9

   Considering the basic requirements described in section 2.1, a tagging mechanism
has to be smoothly integrated into a process modelling tool. Therefore, tagging was
not implemented as an isolated feature to be reached from an extra menu but
integrated into existing dialogues used for e.g. naming elements (Fig. 3).




               Fig. 3. Smooth integration of tagging into the modeling tool.

   An important part of the design was focused to the connection of the modeling tool
to the KM application. The resulting prototype currently supports adding tags to
models and using these tags for storing the models in the KM application (Fig. 4, left
side). The other way round, models and other content can be explored with tag-based
navigation from the application (Fig. 4, right side). This e.g. enables a user to perform
contexualized searches for models. The features shown in Fig. 4 correspond to the
fields of support using models together, using models for communication and finding
and contextualizing models. Work on the next generation of prototypes will include
tag proposals for storing and searching models as well as generating proposals for
adequate locations to store a model to based on its tags.




       Fig. 4. Tag-based support for searching and opening models in a KM tool.
   Another important part of the design was supporting the modeling process. For
such support, the prototype features contextual content retrieval from the KM
application (Fig. 5). The retrieval is based on tags available anywhere in the model
and matching these tags to similarly tagged content in the KM application.
Additionally, the names of elements are parsed and used as tags for the search. Figure
4 shows this function in the prototype. In the figure, similar content to the tags
assigned to „Activity 3.1“ is displayed and offered to the user. This feature
corresponds to the field of creating models, enabling modelers to find and intergrate
10   Michael Prilla


existing knoweldge on processes in a model. It also applies to the field of ensuring
understanding of models as well as connecting models with other content by
interrelating similar content found by tags with the model currently viewn.




           Fig. 5. Tag-based contextual content retrieval from the KM tool.

   Besides the integration of tagging into a process modeling tool, the mechanism is
intended to combine the tool with a KM application in order to foster the findability
of models and contextually share models with others. Corresponding fields of support
such as facilitating model usage and aspects of these fields not covered in the
description above such as ensuring the quality of models are covered by functionality
implemented in the KM application Kolumbus 2. This system, as described in [20],
[22], also has a tagging mechanism and is able to handle content on this basis.


5    Related Work

There are several research areas related to and influencing the approach presented in
this paper. In the following, some of these areas are briefly sketched. A more detailed
discussion and a comparison to the approach presented here can be found in [22].
Familiar research areas can be found in approaches aiming at the management of
process models by either creating model catalogues [6] or building applications for
maintaining and editing models [25]. Another familiar area can be seen in (semantic)
business process management, which is focused to managing process execution and
monitoring [11], [23]. Additionally, in KM there is an area of research on process
oriented KM, which uses process models for navigational and structural purposes
[16]. As shown in [22], all of these approaches are valuable for the problems they
work on, but these problems differ from the one tackled here and therefore, these
approaches do not provide a solution to the problems described above.
   Recently, approaches using social software in combination with model
management have appeared. In [14], the authors describe an approach using social
networks to support the work with process models by providing recommendations for
processes to people and supporting the collaboration among people and processes.
The approach described in [5] puts forward the idea of tagging process models for
their management, but while the authors provide a solid ground for this idea, they do
not show a system implementing it. What can be learned from both approaches is that
social software can provide benefits in the management of process models and
therefore improve business processes in organizations. The second approach also
Models, Social Tagging and Knowledge Management – A fruitful Combination for Process
                                                                    Improvement       11

shows that tagging process model is worthwhile. It corresponds with an early
description [20] of the approach presented in this paper.


6     Conclusion and Further Work

The basic argument pursued in the paper is that support for creation and usage of
processes models as well as for their dissemination are decisive factors in the
improvement for business processes. I argue that with process models being neglected
content, relevant knowledge of and in processes is lost and therefore, potential for
process improvement is wasted. My work is backed up by an empirical analysis of
process model related tasks and resulting requirements. It covers the whole lifecycle
of process models in organizations and therefore identifies needs and problems in
various aspects.
This paper presents tagging as a lightweight mechanism for semantic description and
shows it that can accomplish the task of integrating process models into KM and
therefore improve work with process. The resulting prototype shows how such
potential benefits can be implemented in prototype aiming to tackle the problem of
business process improvement and the involvement of stakeholders from a different
side than existing approaches do.
   The approach presented here represents a concept of integrating process models
into KM and should not be seen as the only way for that. Rather than that, there is
potential for synergies with existing solutions, including combining it with business
process management systems and other modelling and KM tools. Including such
potential in future generations of the prototypes provides a both a challenge and huge
potential for generalizing the approach and making it applicable in organizations.
   Right now, we are developing the next generation of the prototypes and
experiments to explore its impact on process model usage and process handling in
organizations. This generation will use tags as guidance for storing and finding
processes models as well as mechanisms to match people, content and information
needs in the modelling process. Additionally, the prototype will be tailored to all
needs found in the empirical work. In general, we are confident to make the approach
a successful step towards the dissemination of process models in organizations and
therefore to business process improvement. Concerning its benefits, the approach will
have to prove whether it eases process knowledge acquisition, supports the
acceptance of models and improves the quality of models created with its support.


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