INTEGRATING CURRENT PRACTICES AND INFORMATION
SYSTEMS IN KM INITIATIVES
A Knowledge Management Audit Approach
Oscar M. Rodríguez-Elias, Cesar E. Rose-Gómez
Division of Graduate Studies and Research, Institute of Technology of Hermosillo
Ave. Tecnológico, Hermosillo, Son., Mexico
Aurora Vizcaíno
Informatics Higer School, University of Castilla-La Mancha, Ciudad Real, Spain
Ana I. Martíenz-García
Computer Science Department, CICESE Research Center, Ensenada, B.C., Mexico
Keywords: Knowledge Management, Knowledge Audit, KM Audit, Knowledge Flow Analysis, KM Process
Improvement.
Abstract: Researchers and practitioners in the field of knowledge management have observed the need of performing
studies to understand the context and specific knowledge workers needs before proposing strategies or
systems that may not be entirely useful for organizations, resulting in costly and unsuccessful knowledge
management projects. Different approaches have been proposed to face this problem, such as process
engineering techniques to integrate knowledge management in business processes, and also knowledge
audits to identify the knowledge and knowledge problems in organizations. This paper draws on the idea of
the knowledge audit to propose a methodology for knowledge management audits, which integrates process
engineering techniques and the main tasks of knowledge audits. The methodology was developed based on
one of our previous works, literature review, and our own experience in field studies. The methodology, its
constitutive phases and main tasks, together with some aspects about its use in field studies, including
benefits and weaknesses, are described.
1 INTRODUCTION
Although the Knowledge Management (KM) field
has being in the interest of practitioners and
researchers for more than a decade, many KM
initiatives are still being unsuccessfully
implemented. The reasons for KM failures have
been under investigation from different perspectives,
and different authors have written their opinions on
this respect. For instance, Stewart (2002) analyzed
different KM initiatives and found that much of
them tend to fail because a lack of understanding of
the real needs of organizations. In recent years,
researchers in the field of KM have getting more
attention towards the need for understanding the real
necessities not just of the managerial positions of
organizations, or of the organization as a whole
entity, but the particular requirements of knowledge
workers at all the levels of an organization. For
instance, Karl Wiig (2004) has developed a whole
theory on the need for people focused on KM.
Based on the observations of other authors, we
can state that for KM to be effective, organizations
must start looking for what it is really important for
their knowledge workers (Wiig, 2004), as well as
identifying means to integrate KM into the daily
work processes (Scholl, König, Meyer, & Heisig,
2004) and into the daily working tools (Davenport,
2007). All this is particularly true for small
companies, which often do not have the resources to
71
Rodríguez-Elias O., Rose-Gómez C., Vizcaino A. and Martíenz-García A..
INTEGRATING CURRENT PRACTICES AND INFORMATION SYSTEMS IN KM INITIATIVES - A Knowledge Management Audit Approach.
DOI: 10.5220/0003100100710080
In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2010), pages 71-80
ISBN: 978-989-8425-30-0
Copyright
c
2010 SCITEPRESS (Science and Technology Publications, Lda.)
engage themselves in costly and time consuming
KM efforts (Wong, 2005). As has been observed by
Sparrow (2001), before implementing a KM
initiative, small firms have to see the implications of
KM into their current processes. This implies to
understand the particular context of such
organizations in terms of the KM practices that they
could be actually applying, trying to harnes those
current practices, and their current working tools by
integrating those as part of the KM efforts. In this
scenario, a KM audit should be the first step towards
the implementation of KM, particularly in small
companies.
In this paper, we describe a KM audit approach
developed to study and understand knowledge needs
in organizational processes, with a focus on the
identification of the current practices and the
Information System (IS) that migth be contributing,
either explicitly or implicitly, to KM activities. The
remain of this paper is organized as follows: first, in
Section two we introduce the foundations for the
methodology, which is described in Section three.
Then, in Section four we present some scenarions in
which the methodology has been applied, together
with the main results of such studies. Afterwards, in
Section five we discusses about some lessons we
have learned during our work, and about the work to
be done; to finally conclude in Section six.
2 TOWARDS KM AUDIT
In this paper, we are proposing KM audit as an
extension of the concept of Knowledge Audit (KA).
Hence, we will first depict on the Knowledge Audit
concept and on the works we have studied to
develop our proposal.
2.1 Knowledge Audit
According to Lauer & Tanniru (2001), a knowledge
audit (KA) is to understand the processes that
constitute the activities of a knowledge worker, and
see how well they address the “knowledge goals” of
the organization.
Liebowitz, Rubenstein-Montano, McCaw,
Buchwalter, & Browning (2000) define a KA as a
tool that assets potential stores of knowledge. By
discovering what knowledge is possessed, it is then
possible to find the most effective method of storage
and dissemination. It can then be used as the basis
for evaluating the extent to which change needs to
be introduced to the enterprise.
The KA is used to provide a sound investigation
into the organization’s knowledge health. It
examines knowledge sources and use: how and why
knowledge is acquired, accessed, disseminated,
shared and used (Hylton, 2002).
According to literature, Perez-Soltero, Barcelo-
Valenzuela, Sanchez-Schmitz, & Rodriguez-Elias
(2009) have identified that the benefits that an
organization might obtain by carrying out a KA
include the following:
Providing scientific evidence to determine if the
potential value of the company’s knowledge is
maximizing.
Offering evidence and formalized accounting of
existing knowledge within the organization as well
as how it moves through the company.
Detailing in the knowledge inventory “what
knowledge exists and where it is in the
organization”, which is crucial to determine the
abundance and worth of corporate knowledge.
Allowing for the creation of a map detailing
internal and external knowledge and its flow,
besides formal and informal social networks. This
facilitates to identify the inefficiencies that take
place when there are duplicate efforts, knowledge
voids and bottle necks in the knowledge flow.
Helping the company to identify and plan the
knowledge required to support its goals, tasks, and
activities.
Allowing for the measurement of the relative
worth of knowledge entities as perceived by
initiators and users (e.g. employees).
Offering measurement and the valuation of the
efficacy of the company’s capacities and
competences with respect to knowledge and KM
when compared to clients, partners, and even
competitors.
It facilitates the measurement of the effectiveness
and efficiency of knowledge capture by the
company and the success with which the captured
knowledge is used to support the interests of
outsiders such as partners and clients.
Allowing hidden knowledge to become visible,
knowledge assets to become more tangible and,
therefore, facilitates activities focused on
accounting for them and their measurement.
Making it easier for KM initiatives to become
more efficient and effective.
Producing independent and objective indicators
based on knowledge values that can be used to
plan and implement KM projects. Such measures
being far richer than measures that only focus on
the success or failure of particular KM initiatives.
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
72
Additionally, Rodríguez-Elias, Martínez-García,
Vizcaíno, Favela, & Piattini (2009) have identified
that some of the benefits a company might obtain by
studying the knowledge involved in their processes
include the followings:
Identify knowledge related problems.
Increase the information of the knowledge and
knowledge sources involved in the processes.
Identify tools that can be integrated within the
KM initiative.
Identify requirements in order to acquire or
develop new tools through which to improve the
knowledge flow.
Analyze the effects of including KM strategies in
the processes.
Improve the assignment of human resources.
From all the above, we can observe that
understanding knowledge needs may get great
benefits to an organization, so we agree that this
understanding should be an important first step
towards the development of KM initiatives.
2.2 The Knowledge Audit Process
According to (Liebowitz, Rubenstein-Montano,
McCaw, Buchwalter, & Browning, 2000) a KA can
be realized following three main steps:
1. Identify what Knowledge Currently Exists in
the target area, which include: a) determine
existing and potential sinks, sources, flows, and
constrains in the target area, including
environmental factors that could influence the
target area; b) identify and locate explicit and
tacit knowledge in the target area, and c) build a
knowledge map of the taxonomy and flow of
knowledge in the organization in the target area.
The knowledge map relates topics, people,
documents, ideas, and links to external resources
in respective densities, in ways that allow
individuals to find the knowledge they need.
2. Identify what Knowledge is Missing in the
target area, which include: a) perform a gap
analysis to determine what knowledge is missing
to achieve business goals, and b) determine who
needs the missing knowledge.
3. Provide Recommendations from the KA to
management regarding the status quo and
possible improvements to the KM activities.
We believe that in spite of the benefits of a KA,
it is not enough since it is also required to identify
the mechanisms, activities, and processes that
companies are using to manage what they know.
That means, it is also required a KM Audit.
2.3 The KM Audit
Most literature on KA assumes that such activity is
carried out in companies which want to implement a
KM strategy, and that currently don’t have one.
However, even when a company would not have
explicit KM practices, they use to perform KM
activities even when they are not aware of it. At least
this fact has found to be true in different field studies
(Aurum, Daneshgar, & Ward, 2008; Meehan &
Richardson, 2003).
Lauer & Tanniru (2001), state that the goal of a
KM audit is “to understand the processes that
constitute the activities of a knowledge worker, and
see how well they address the knowledge goals of
the organization”. Thus we define a KM audit as the
identification, analysis and evaluation of the
mechanisms, activities, processes and practices
being followed to manage the knowledge that a
company already has, or to create or acquire the
knowledge that this requires to fulfil its goals.
For a KM initiative to be successful, it is
important to identify not just the knowledge we want
to manage, but also to identify the mechanisms and
activities that the actors of a process currently
perform to manage their knowledge. In fact, one of
the current concerns in KM practitioners and
researchers is to identify the manner in which KM
strategies can be integrated to the common working
processes, harnessing at most as possible the current
working practices and technological infrastructure
(Davenport, 2007; Scholl, König, Meyer, & Heisig,
2004). This situation is particularly important for
small companies, since they probably would not
have the resources for engaging themselves in a
costly KM project requiring big changes in their
current working processes and technological
infrastructure (Sparrow, 2001; Wong, 2005).
Based on literature review and our own
experience, we consider that a KM audit should
include:
A Knowledge Audit as has been described
previously.
Identify the Knowledge Goals. A knowledge
goal is a goal that gives direction to KM, and that
it is exclusively concerned with knowledge
processes, such as knowledge acquisition,
creation, sharing, etc. (Lauer & Tanniru, 2001).
Identify the Current KM Practices being
performed by actors of the organizational
process, and how they aid to the accomplishment
INTEGRATING CURRENT PRACTICES AND INFORMATION SYSTEMS IN KM INITIATIVES - A Knowledge
Management Audit Approach
73
of the knowledge goals. It is important to
identify both, formal and informal KM practices.
If a company has already implemented a KM
initiative, then we could be trying to improve
that previous initiative by harnessing what has
been functioning well, and improving what is
being functioning badly. As well, even when a
company would not have formal KM practices,
their employees might follow KM activities
implicitly, even when they might be unaware that
they are doing KM.
Identify the Mechanisms being used by the
actors of the organizational process as KM
facilitators, and the manner in which they
influence, positively or negatively, the
accomplishment of the knowledge goals. If we
want to include current KM practices, we should
think on using the current mechanisms that the
actors of the process use to manage their
knowledge.
Identify the Working Tools being used within
the process and that may be being used, or might
have the potential to be used as KM tools.
Identify the Problems affecting the well
management of the important knowledge for the
organizational processes.
2.4 Knowledge Audit Methodologies
Several researchers and practitioners have made
proposals for performing KA. For instance,
Liebowitz, Rubenstein-Montano, McCaw,
Buchwalter, & Browning (2000) have proposed a
KA methodology based on a set of key questions
oriented to aid in the identification of the knowledge
that currently exists, and that missed in a target area.
The answers to those questions should provide
insights to propose recommendations for possible
improvements of KM activities.
Hylton (2002) has developed a methodology for
KA focused on auditing the knowledge that people
need to do their jobs efficiently. This methodology
follows three main steps: 1) a survey for collecting,
collating, analyzing and measuring corporate
knowledge data and information via the voice of the
knowledge people; 2) a knowledge inventory to
stock-taking and measurement of tacit and explicit
knowledge to determine the actual and potential
knowledge wealth, and 3) the building and
development of a corporate knowledge map of the
structure and flow of knowledge, highlighting who
has what knowledge and how they disseminate and
share knowledge in the corporate knowledge
community.
Choy, Lee, & Cheung (2004) developed a KA
methodology of three phases: pre-audit preparation,
in-audit process, and post-audit analysis. The pre-
audit preparation stage is focused on providing
orientation to the KM strategy, and performing a
cultural assessment; the in-audit process stage is
carried out through structured interviews to capture
process-critical knowledge; while post-audit analysis
is performed through the use of knowledge
inventory, knowledge maps, and social network
analysis. The main contribution of this work is that it
is proposed as a mean for evaluation whether a
company is prepared for starting a KM initiative.
Perez-Soltero et al., (2007) have followed a KA
methodology which focuses on the core processes of
an organization. That means, the core processes of
an organization are choose to be analyzed, where
core processes are defined as “collection of cross-
functional activities that are essential for external
customer satisfaction and achieving the mission of
the organization” (p. 9). This methodology consists
of ten steps: 1) Acquire organizational strategic
information and identify organizational processes; 2)
Identify organization’s core processes and establish
measurement criteria; 3) Prioritize and select
organization’s core processes; 4) Identify key
people; 5) Meeting with key people; 6) Obtaining
knowledge inventory; 7) Analyzing knowledge flow;
8) Knowledge mapping; 9) Knowledge Audit
Reporting; and 10) Continuous Knowledge Re-
auditing.
From the analysis of different KA
methodologies, Perez-Soltero and his colleagues
(2007) have observed that most of them attempt to
audit everything, no matter if what it is audited is
significant or not to the organization. Thus, the
approach of focusing on the core processes of an
organization is a better way to perform a KA which
focuses on the most important knowledge. However,
one weakness of their methodology, and also a
weakness of the other KA methodologies we have
studied, is that they do not consider, at least
explicitly, focusing on the current KM practices and
technological infrastructure as the basis for
proposing KM solutions. That is why we have used
our own approach, but considering the main
proposals we have studied in the different KA
methodologies found in literature.
From the analysis of the different KA
methodologies; we observe that three main stages
should be carried out in a KM audit:
1. An information collection stage.
2. A processes analysis stage.
3. A reporting and solutions proposal stage.
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
74
The main differences between the KA
methodologies are on the techniques used to carry
out each of these stages, and the focus of each one of
these. From the literature review and our previous
research work, we have adapted a methodology for
knowledge flow identification (Rodriguez-Elias,
Martinez-Garcia, Vizcaino, Favela, & Piattini,
2005), in order to be used as the basis for performing
KM audits, also considering some of the strengths
we have identified in the KA methodologies just
described.
3 A KM AUDIT METHODOLOGY
The KM audit methodology being proposed is based
on a previous methodology, which was designed to
aid in the analysis of organizational processes from a
knowledge flow perspective (Rodriguez-Elias et al.,
2005). It was defined to assist in three main areas: 1)
to identify, structure, and classify the knowledge that
exists in the process studied, 2) to identify the
technological infrastructure which supports the
process and affects the knowledge flow, and 3) to
identify means with which to improve the
knowledge flow in the process. In a wide sense,
KoFI was designed to propose KM solutions based
on the results of a KM audit to specific
organizational processes.
KoFI is orientated towards helping to analyze
specific work processes, particularly knowledge
intensive process. Thus, it considers the focus on
core processes proposed in the Perez-Soltero et al.
(2007) KA methodology. The process followed to
apply the methodology is iterative, since each stage
may provide useful information for the preceding
stages.
The KoFI methodology has three main phases:
knowledge-focused process modelling, analysis of
the process (which include identification of
knowledge sources, topics, and flows, and
knowledge flow problems), and analysis of the tools
affecting the knowledge flow.
In order to adapt this methodology to be used as
a KM audit methodology we have extended it. This
extension includes an explicit phase for data and
information gathering; an analysis phase, which is
performed following the original analysis phases of
the KoFI methodology, and a reporting and solution
proposing stage. The figure 1 provides a general
view of the extended methodology.
Data and Information Gatering
Structured interviews
Document analysis
Observation
Process Analysis
Process modeling
Knowledge flow analysis Identification of:
Knowledge sources
Knowledge topics
Knowledge flows
Knowledge flow problems
Identification and analysis of KM tools and
practices
Reporting and solution proposing
Report writing
Requirement specification
Prototype development and evaluation
Figure 1: Stages of the KM audit methodology.
In the following subsections we will briefly
describe each of the stages of our proposed
methodology, together with some techniques and
guidelines to carry out each stage. We will focus on
the elements that aid to identify the role that current
practices and Information Systems plays in the KM
activities.
3.1 Information Gathering Phase
This stage is perhaps one of the most important of
the whole methodology, since if we do not obtain
the correct data it will be highly probable that the
results of the following stages will be useless.
Unfortunately, we have observed that having a
rigorous formal and detailed data gathering protocol
could be very difficult to develop and to adapt it to
specific organizations needs. So, we have followed
some general guidelines, which are adapted
according to the particular situation of each
organization, and according to what we observe
during each particular case. These general guidelines
are as follow:
1. If the researchers have no prior information
about the process to be studied, perform longs
interviews to the main actors of the
organization. These interviews should be made
to obtain information useful to identify which
processes should be analyzed, and who is the
people we should talk to first.
2. Identify the people related to the process, the
responsible of it, the people who might serve
information to the process, the people who
might use information from the process, and the
INTEGRATING CURRENT PRACTICES AND INFORMATION SYSTEMS IN KM INITIATIVES - A Knowledge
Management Audit Approach
75
people who perform the activities required for
the process.
3. Perform semi-structured interviews to key
people. This key people are those who might
have a general view of the process, and which
might have a better idea about how the process
and its main activities should work. These
interviews should be carried out to obtain
information about the main activities, and
products (inputs, outputs, and internal products)
of the process, and to start identifying the main
knowledge required and generated during the
process, the knowledge sources, and the
working tools that might be supporting or
affecting the flow of knowledge. Liebowitz,
Rubenstein-Montano, McCaw, Buchwalter, &
Browning (2000) provide a set of sample
questions that can be used as a basis for
defining the interviews protocol.
4. If there are many people performing similar
roles into the process, interview just one or two,
and use that information to create a
questionnaire to perform a survey with the rest
of the people, in order to identify similarities
and differences.
5. Identify documents with information about the
processes, if they exist to use them to compare
them to the information obtained from the
interviews, and to complement it.
6. Perform sessions of observation to validate that
the people are really performing the process in
the form they have told. Document any
differences or additional information to
complement or adequate the gathered data.
7. Create models of the process considering the
activities, the roles that people play, the sources
of information and knowledge, the main
knowledge topics or areas, and the relationships
between all these items. This model should be
validated by the interviewed people to use them
as the basis for the analysis phase.
8. Perform all these activities in a cyclic way, until
researchers and practitioners are conform to the
models, and agree that these models really
reflect the process being carried out.
3.2 Knowledge Focused Process
Modelling
A graphical model of the process, which indentifies
the knowledge required or generated, and the
knowledge sources and the working tools that may
be used as knowledge flow facilitators or channels,
is one of the main results of the data gathering
phase, and it is the main source of information for
the analysis phase.
In order to use these models for the next stage, it
is important to explicitly represent the knowledge
and its sources within the model, since integrating
elements in an explicit way into a process model,
greatly facilitates its analysis (Rodríguez-Elias et al.,
2009).
Thus, given the importance of this step, we have
been following a graphical process modelling
approach that explicitly represents the knowledge
and its sources. This approach was proposed in
(Rodriguez-Elias et al., 2005), and it is an adaptation
of the Rich Picture technique (Monk & Howard,
1998). Figure 2 present an example of this approach.
The graphic elements and their possible connections
are described next:
Role
Knowledge source
used in the
process/activity
Process/Activity
List of main knowledge
topics required to fulfill
the process/activity
List of knowledge
topics that a Role
obtains by participating
in a process or activity.
List of main knowledge
topics generated during
the process/activiy
List of knowledge
topics that a Role has
and uses during the
process/activity.
Knowledge source
generated in the
process/activity
List of knowledge
topics obtained from
a knowledge source.
List of knowledge
topics stored in a
knowledge source.
Figure 2: Example of the Rich Pictures notation used.
Activities are represented with a cloud.
Roles are represented with a cartoon of a person,
or any other figure that could better reflect what the
role is.
Knowledge Areas or Topics are listed within
brackets.
Knowledge Sources can be represented with a
rectangle, or they can be also represented with
another figure to differentiate between each type of
source (document, information system, repositories,
etc.).
Connections are represented with lines. Just
roles and activities are connected with undirected
lines, this indicates that the role participate in the
activity. A line directed from an activity to a list of
knowledge topics, indicates that that knowledge is
generated in the activity; if the line is directed from
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
76
the list of knowledge topics to the activity, indicates
that that knowledge is required to perform the
activity. A line directed from a role to a list of
knowledge topics indicates the knowledge that is
extracted from that role, this means, the role has that
knowledge and uses it to carry out the activity; a line
from the list of knowledge to a role is used to
indicate that the role obtains that knowledge by
participating in the activity. A line from a knowledge
source to an activity indicates that the source is used
in the activity, if the line is directed from the activity
to the source, then, that source is created in that
activity; if the line is bidirectional, then the source is
modified in the activity. Finally, a line directed from
a source to a list of knowledge topics indicates that
the knowledge is obtained from the source; if the
line is directed from a list of knowledge to the source
then indicates that the knowledge is stored in the
sources during the activity.
3.3 Process Analysis Phase
The process models are a basis for the analysis phase
composed of four steps, 1) identification of
knowledge sources, 2) identification of knowledge
topics, 3) identification of knowledge flows, and 3)
identification of knowledge flow problems.
One result of these steps is a knowledge map of
the knowledge sources and topics, indicating what
knowledge topics are stored in each source, and the
relationships of these items with the main activities
of the process. To create the map, taxonomies of
knowledge sources and topics are developed, which
are later used as a basis for an ontology that defines
the structure of the map. The map is useful to know
where the sources are, how can these be accessed,
and in which activities are they required or useful.
Additionally, in this stage the main mechanisms
being used as knowledge flow channels are
identified, such as information systems, documents,
key people such as knowledge brokers, knowledge
hubs, etc. Finally, a list of the main types of
problems affecting the knowledge flows is
developed, classifying and describing the problems
and its context. Together with each type of problem
one or more possible solutions are described in order
to latter be used to gather requirements for designing
a KM system or strategy.
3.4 Analysis of KM Support Tools
The previous stage helps to identify the main tools
being used as knowledge flow channels. We
consider that these tools are those that affect
(positively or negatively) to the different KM
activities (capture, storage, dissemination, sharing,
retrieval, etc.). In this stage, we analyse those tools
to evaluate to what level they are supporting the
knowledge flow and the different KM activities. To
accomplish this, we follow a framework proposed in
(Rodriguez-Elias, Martinez-Garcia, Vizcaino,
Favela, & Piattini, 2008).
This framework helps to classify each tool
according to the purpose of the knowledge managed
with it, the people that can be benefited with its use,
the domain and structure of the knowledge managed,
and the KM activities being supported. Thus, one
can specify whether a tool allows managing
knowledge within different dimensions. For
instance, in the case of knowledge use from personal
uses to industry wide use; in the dimension of
domain knowledge, from business knowledge to
technical knowledge; in the dimension of the
structure of knowledge, from highly tacit, such as
skills, to highly explicit and structured, such as
mathematical formulation; and in the case of the KM
activities supported, from a tool that inhibits the
flow of knowledge to a tool that improves it.
3.5 Reporting and Solution Proposing
In this final stage, the information obtained and
generated during the data gathering and process
analysis phases is integrated and structured to
document and report to the process administrators
the state of the process, the findings of the study,
and possible solutions to the problems found.
The report consists of six main sections:
1. Introduction, which includes the next
subsections: purpose describes the purpose and
goals of the study carried out, presents a general
description of the process or processes studied
and their context, and a description of the
people to whom the information might be
useful; methodology, a brief description of the
methodology followed, the time consumed, the
people involved, and any other data useful to
estimate the cost of the study, this section also
includes any limitation of the study that might
be important to take into consideration; main
findings, a brief description of the main
findings and its implications to the process, to
the current KM practices and/or to the possible
solutions.
2. Process Description, this section presents a
detailed description of the current process (or
processes) under study. The process models
generated and validated during the previous
INTEGRATING CURRENT PRACTICES AND INFORMATION SYSTEMS IN KM INITIATIVES - A Knowledge
Management Audit Approach
77
stages are used to document it in this section of
the report. Thus, an important result of the study
is a detailed and validated description of the
current process, including the main knowledge
required and generated during each activity, and
the sources used to store it or to acquire it.
3. Current State of KM Practices, this section
presents a wide description of the current KM
practices observed, and the results of the
analysis of the tools that support the different
KM activities. The description may be
presented organized by KM activity, describing
the current state of each KM activity.
4. Knowledge Base, this section includes a
description of the current knowledge base of the
process which consists of the taxonomy of
knowledge sources and topics, its properties and
relationships. The development of an ontology
can be a useful mean to structure and document
this knowledge base (Perez-Soltero et al., 2009).
5. KM Problems Observed, in this section, the
main problems affecting the management of
knowledge are documented. It is important that
these problems are organized and classified. To
this end we use problem scenarios, a technique
proposed in (Rodriguez-Elias et al., 2005). A
problem scenario is a description of a problem
in form of a story. Each problem scenario is
composed of: 1) a name which briefly describes
the problem, 2) a type of problem in which it is
classified (such as information loss or difficult
to find, knowledge flow bottle neck, etc.); 3) a
description of the problem, which is a story that
describes how the problem occurs, and that
includes its context; and finally 4) one or more
alternative scenarios describing how the
possible solutions could change the problematic
situation. These alternative scenarios are the
basis for the recommendations and solutions
proposed. Additionally, they can be also used
for gathering requirements for designing KM
systems for solving the observed KM problems.
6. Recommendations and Solutions Proposed.
This section is used to sensitize the main
problems affecting the flow of knowledge, to
make recommendations for improving the flow
and the KM practices, and to propose solutions
to the problems observed. If the proposal
considers the development, modification or
acquisition of software tools to face the
problems or to implement the improvements,
this section also includes the general
requirements of such tools.
4 USING THE METHODOLOGY
The development of the proposed methodology has
been done following an action research approach
(Avison, Lau, Myers, & Nielsen, 1999). This means
that we have been using the methodology to study
different processes in different scenarios. The results
and lessons learned in each case have been used to
improve the methodology. This section shall
describe the main results of the application of the
methodology in each field in which it has been used.
4.1 In the Software Development Field
The first application of the methodology was for
studying knowledge needs in a software
maintenance process (Rodríguez, Martínez,
Vizcaíno, Favela, & Piattini, 2004). In this case we
get aware of the importance of considering explicitly
in the methodology the identification of current KM
practices, and the current tools supporting KM
activities. After this, the extensions made to the
methodology were used to make a second analysis
of the same process. In this second analysis, it was
identified one tool being used as the main
knowledge flow channel, and the result of the study
was the proposal of small improvements to that tool
in order reduce the loss of knowledge, increase the
capture of knowledge, facilitates its retrieval, and
improve its flow.
4.2 In the Manufacturing Field
The second application of the methodology was for
studying one of the processes of a manufacturing
firm (Rodriguez-Elias, Morán, Labandera, &
Vizcaíno, 2008). The result of this study was the
development of a knowledge portal for the firm,
which facilitates the identification and access to the
knowledge and information sources available in the
firm, according to the activities that a specific role
has to carry out. This is possible since the portal was
developed following the structure of the knowledge
base defined according to the methodology.
4.3 In the Social Field
A third use of the KM Audit methodology was for
studying the processes followed by an organization
focused on promoting support for elderly people.
Specifically this study was conducted to identify
how to help this institution to disseminate their
activities and to gather more participants. The result
of the study was the documentation of the processes
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
78
of this institution, and the inclusion of
communication technologies, such as social
networks, in the activities of the participants, in
order to increase the promotion of their activities.
An important result of this study was that it helped
us to validate that the proposed process modelling
approach was easy to understand for elderly people
without knowledge in this field, and that had not
interest on learning it.
4.4 In the Academic Field
Currently we are using the methodology as a mean
to teach KM systems design to graduate students in a
master degree program. The students analyze
different processes of a public higher education
institution, and propose solutions to one of the main
KM problems they find. Until now, we have
identified several communication problems between
the different departments, and within each
department. As a result, some students are designing
a knowledge diffusion system for the institution. The
system faces the problem of knowledge diffusion in
several ways: for employees and students to get
aware of what is happening in the institution, and to
help them to inform about the results of their main
activities; and for the institution to inform the
community about its strengths and the knowledge
and technological developments it is creating.
5 DISCUSSIONS AND FINAL
COMMENTS
The case studies in which the methodology has been
applied have taught us the benefits of performing a
KM audit before thinking in specific KM solutions.
In all the studies, there have been found practices
and tools that can be harnessed as part of the KM
initiatives proposed; which was one of the main
requirements for developing the proposed
methodology. However, these projects have also
shown us that performing studies of this type are
really time consuming. Because of the last, we
believe necessary to develop tools to reduce the
effort that this type of studies require. In this
direction, we are currently developing tools for
facilitating the process modelling stage, and the
development of the knowledge base of the studied
processes. Additionally, we have observed that one
weakness of the methodology is the lack of a stage
to evaluate its results, and the benefits of the
proposed solutions. Unfortunately, the literature in
this field is still scarce, and it shows that much work
have to be done yet. Finding a way to perform this
evaluation should constitute part of our further work.
Additionally, it is important to continue validating
the methodology, by applying it in more diverse and
complex scenarios, and compare the results to KM
studies performed in similar domains.
6 CONCLUSIONS
It is a fact that KM is gaining an increasing interest
in almost any sector, either private or public, what is
taking organizations from diverse fields and sizes to
invest in KM as a mean to make them competitive,
and more dramatically, to help them to survive in a
rapidly changing environment. Unfortunately, many
KM initiatives are still being developed without
considering a wide study of the real knowledge
needs of the organization’s processes and
employees, which might provoke for companies or
public organizations to waste their money, time, and
resources in KM projects that might be unsuccessful.
In this paper we proposed a methodology to
perform knowledge management audits as a starting
point in the proposal or development of KM
initiatives. The methodology is focused on
identifying and understanding the knowledge needs
in organizational processes by performing a
knowledge flow analysis following a process
engineering approach. The methodology has been
developed from the results of previous works,
literature review, and its application in field studies,
following an action research approach. The main
case studies in which our proposal has been used
were also presented in this paper. From these field
studies, some observations about the benefits and
weaknesses of the methodology emerged, and have
given us some insights to our future work,
particularly the development of an evaluation stage
to drive the evaluation of the results of the
methodology, such as the KM solutions proposed.
ACKNOWLEDGEMENTS
We want to acknowledge the financial support of
CONACYT and DGEST, in Mexico. Also the
partially support of the ENGLOBAS (PII2I09-0147-
8235) and MELISA (PAC08-0142-3315) projects,
Junta de Comunidades de Castilla-La Mancha,
Consejería de Educación y Ciencia; the PEGASO
project (TIN2009-13718-C02-01), Ministerio de
INTEGRATING CURRENT PRACTICES AND INFORMATION SYSTEMS IN KM INITIATIVES - A Knowledge
Management Audit Approach
79
Educación y Ciencia (Dirección General de
Investigación)/ Fondos Europeos de Desarrollo
Regional (FEDER), and the FABRUM project (PPT-
430000-2008-063), Ministerio de Ciencia e
Innovación, in Spain.
REFERENCES
Aurum, A., Daneshgar, F., & Ward, J. (2008).
Investigating Knowledge Management practices in
software development organizations An Australian
experience. Information and Software Technology,
50(6), 511-533. doi: 10.1016/j.infsof.2007.05.005.
Avison, D. E., Lau, F., Myers, M. D., & Nielsen, P. A.
(1999). Action research. Communications of the ACM,
42(1), 94-97. doi: 10.1145/291469.291479.
Choy, S., Lee, W., & Cheung, C. (2004). A systematic
approach for knowledge audit analysis: Integration of
knowledge inventory, mapping and knowledge flow
analysis. Journal of Universal Computer Science,
10(6), 674682.
Davenport, T. H. (2007). Information Technology for
Knowledge Management. In K. Ichijo & I. Nonaka,
Knowledge Creation and Management (pp. 97-117).
New York: Oxford University Press.
Hylton, A. (2002). A KM initiative is Unlikely to Succeed
without a Knowledge Audit. Proceedings of
KMAC2003, the Knowledge Management Aston
Conference, Operational Research Society,
Birmingham. doi: 10.3217/jucs-010-06.
Lauer, T., & Tanniru, M. (2001). Knowledge Management
Audit-a methodology and case study. Australasian
Journal of Information Systems, 9(1), 23-41.
Liebowitz, J., Rubenstein-Montano, B., McCaw, D.,
Buchwalter, J., & Browning, C. (2000). The
Knowledge Audit. Knowledge and Process
Management, 7(1), 3-10. doi: 10.1002/(SICI)1099-
1441(200001/03)7:1<3::AID-KPM72>3.0.CO;2-0.
Meehan, B., & Richardson, I. (2003). Identification of
Software Process Knowledge Management. Software
Process: Improvement and Practice, 7(2), 47-55. doi:
10.1002/spip.154.
Monk, A., & Howard, S. (1998). The Rich Picture: A Tool
for Reasoning About Work Context. Interactions, 5(2),
21-30.
Perez-Soltero, A., Barcelo-Valenzuela, M., Sanchez-
Schmitz, G., & Rodriguez-Elias, O. M. (2009). A
computer prototype to support knowledge audits in
organizations. Knowledge and Process Management,
16(3), 124-133. doi: 10.1002/kpm.329.
Perez-soltero, A., Barcelo-valenzuela, M., Sanchez-
schmitz, G., Martin-rubio, F., Palma-mendez, J. T.,
Vanti, A. A., et al. (2007). A Model and Methodology
to Knowledge Auditing Considering Core Processes.
ICFAI Journal of Knowledge Management, 5(1), 7-23.
doi: 10.1.1.72.8091.
Rodriguez-Elias, O. M., Martinez-Garcia, A. I., Vizcaino,
A., Favela, J., & Piattini, M. (2005). Identifying
Knowledge Flows in Communities of Practice. In E.
Coakes & S. Clarke, Encyclopedia of Communities of
Practice in Information and Knowledge Management
(pp. 210-217). Hershey, PA.: IGI Global.
Rodriguez-Elias, O. M., Martinez-Garcia, A. I., Vizcaino,
A., Favela, J., & Piattini, M. (2008). A framework to
analyze information systems as knowledge flow
facilitators. Information and Software Technology,
50(6), 481-498. doi: 10.1016/j.infsof.2007.07.002.
Rodriguez-Elias, O. M., Morán, A. L., Labandera, J. I., &
Vizcaíno, A. (2008). Improving Knowledge Flow in a
Mexican Manufacturing Firm. Research in Computing
Science: Advances in Computer Science and Artificial
Intelligence, 39, 29-45.
Rodríguez, O. M., Martínez, A. I., Vizcaíno, A., Favela, J.,
& Piattini, M. (2004). Identifying knowledge
management needs in software maintenance groups: a
qualitative approach. In Fifth Mexican International
Conference in Computer Science, 2004. ENC 2004.
(pp. 72-79). IEEE Computer Society Press. doi:
10.1109/ENC.2004.1342591.
Rodríguez-Elias, O. M., Martínez-García, A. I., Vizcaíno,
A., Favela, J., & Piattini, M. (2009). Modelling and
Analysis of Knowledge Flows in Software Processes
through the Extension of the Software Process
Engineering Metamodel. International Journal of
Software Engineering and Knowledge Engineering,
19(2), 185-211. doi: 10.1142/S0218194009004155.
Scholl, W., König, C., Meyer, B., & Heisig, P. (2004). The
future of knowledge management: an international
delphi study. Journal of Knowledge Management,
8(2), 19-35. doi: 10.1108/13673270410529082.
Sparrow, J. (2001). Knowledge management in small
firms. Knowledge and Process Management, 8(1), 3-
16. doi: 10.1002/kpm.92.
Stewart, T. A. (2002). The case against knowledge
mangement. Business 2.0. Retrieved from
http://www.iwp.jku.at/born/mpwfst/06/cogneon/The_
Case_Against_KM.pdf.
Wiig, K. (2004). People-focused knowledge management:
how effective decision making leads to corporate
soccess. Amsterdam: Elsevier.
Wong, K. Y. (2005). Critical success factors for
implementing knowledge management in small and
medium enterprises. Industrial Management & Data
Systems, 105(3), 261-279. doi:
10.1108/02635570510590101.
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
80