Verifying the Usefulness of a Classification System of Best Practices
Meshari M. S. Alwazae, Erik Perjons and Harald Kjellin
Department of Computer and System Sciences, Stockholm University, Isafjordsgatan 39, Stockholm, Sweden
Keywords: Knowledge Management, Knowledge Transfer, Best Practice, Classification System.
Abstract: Transfer of best practices (BPs) within an organization can significantly enhance knowledge transfer.
However, in order to manage a large number of BPs within an organization, there need to be some structure
for how to classify the BPs. In this paper, we present a best practice (BP) system for classifying BPs and
evaluate how easy the system is to use for classifying best practices. The research approach applied was
design science, which is characterized by designing an artifact in this case a BP classification system, and
evaluating it. The evaluation was carried out by asking Master’s students to collect two BPs from
organizations and subsequently having them classify the BPs according to the BP classification system.
They were also asked to motivate their choices during their act of classification. The results of the
evaluation are promising: the BP system could be used for classifying BPs since students utilized all
possible values of the BP system during the act of classification. Also, it was easy for the students to justify
their classifications, which might be interpreted as an ease of using the BP classification system.
1 INTRODUCTION
The importance of managing organizational
knowledge, including the needs of knowledge
transfers within an organisation, has been receiving
research attention during the last two decades (Cross
and Baird, 2000; Davenport et al., 1998; Desouza
and Evaristo, 2003; Dinur et al., 2009; Hansen,
2002; Zack, 1999). The studies of the factors that
enable transfer of best practices (BPs) within an
organization can significantly enhance the
perception of knowledge transfer if knowledge
sharing is critical to an organization’s success. Other
directions of research into BPs include examining
whether these practices will actually work
sufficiently in the adopting organizations (Davies
and Kochhar, 2002; Zairi and Ahmed, 1999).
As its heart, BP aims to reuse best ways to solve
a problem or handle an issue. It is about gaining the
benefits of previous experiences to define possible
ways to conduct activities and solve problems
(Axelsson et al., 2011). Organizations use BP to
avoid making the same mistakes, while learning
from others’ experiences in order to produce equally
superior results. BPs should also be easily copied
and transferred throughout the organization. The
logic behind this is that any practice that has been
proven over time to be effective or valuable for one
organization might bring similar successful
outcomes while implemented in another (Fragidis
and Tarabanis, 2006). For instance, a central
committee of managers evaluated BPs at Ericsson
(Watson, 2007). Those managers met quarterly to
decide which of the practices were best suited to be
shared throughout the organization, and, thereby,
converting all departments’ practices. This gave
Ericsson a competitive advantage in their production
processes through a high degree of standardization.
In order to manage a large number of BPs in an
organization, there needs to be some structure for
how to classify the BPs. Such a structure will
support the users to easily find appropriate BPs as
well as providing its users with an understanding of
how BPs are related to other BPs. Such a structure
will also provide the identified BPs with context, an
important feature for successful implementation of
BPs. Furthermore, such a structure will also provide
an organization with an understanding about which
areas within the organization have a limited number
of BPs. The organization can then analyze this lack
of BPs in certain areas and decide if additional BPs
are needed. In this paper, such a structure is called a
BP classification system.
The goal of this paper is to present a BP
classification system for categorizing BPs and
evaluating how easily the system can be used to
405
M. S. Alwazae M., Perjons E. and Kjellin H..
Verifying the Usefulness of a Classification System of Best Practices.
DOI: 10.5220/0004549604050412
In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge
Management and Information Sharing (KMIS-2013), pages 405-412
ISBN: 978-989-8565-75-4
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
classify BPs. The BP system was presented in
Alwazae et al. (2013) but not evaluated. In this
paper, the focus is on evaluating the BP system.
The structure of the paper is as follows. In
section 2, we present the research approach and in
section 3 we discuss the designed artifact, i.e. the BP
classification system. Section 4 describes the
evaluation of the system, while the analysis and
discussion is described in section 5. Related research
is discussed in section 6 followed by a conclusion in
section 7.
2 RESEARCH APPROACH
The research approach used is design science
(Hevner et al., 2004). It is characterized by the
design of artifacts (e.g. constructs, models,
frameworks, methods, prototypes and IT systems).
According to Hevner et al. (2004), design science is
originated in engineering disciplines aiming for
creating innovative artifacts for solving practical
problems. Therefore, design science research is an
activity aimed at generating and testing hypotheses
about the future, i.e. artifacts that can, when
introduced, solve problems for an organization
(Bider et al., 2012). Furthermore, for an artifact to
count as a design science solution, it needs to be
generic in nature, i.e. the artifact solution should be
applicable to not only one unique situation, but to a
class of similar situations, cf. Principle 1 of (Sein et
al., 2011).
Hevner et al. (2004) emphasize the importance of
evaluating a designed artifact in design science
research. Evaluating an artifact means evaluating its
ability to solve a practical problem. However,
evaluating an artifact in design science is difficult.
First, in order to evaluate an artifact in an
organization it has to be applied and then evaluated
to determine if the artifact has solved the problem at
hand. Second, the artifact needs to solve the problem
in many different organizations, since an artifact
needs to be a generic solution to qualify as a design
science solution.
Different strategies and approaches have been
presented to manage evaluations of artifacts in
design science. There are two main evaluation
strategies: ex ante and ex post evaluations (Pries-
Heje et al., 2008). Ex ante evaluation means that the
artifact is evaluated without being used in an
organization, while ex post evaluation requires the
artifact to be employed in an organization. An ex
ante evaluation often employs interviews, where
users express their views on the artifact. While ex
ante evaluations are often weak, ex post evaluations
may be considerably stronger. Such evaluations
require that an artifact is actually put into operation
before being evaluated. Furthermore, Sein et al
(2011) have points out that artifacts in the IT sector
are typically developed and shaped by their
interaction within an organizational context. Thus,
design science research needs to interleave
concurrently the activities of creating an artifact,
introducing it into practice, and evaluating it.
In this paper, we have designed a KM system (in
the form of a model for classifying BP), and
evaluate the artifact by using an ex ante evaluation.
The focus of the evaluation is not on the BP
system’s usefulness for an organisation, which will
be a future evaluation. Instead, the focus is on how
easy it is to classify BPs according to the system.
Therefore, this preliminary evaluation should be
seen as the first evaluative step. The goal of this first
step is to enhance the quality of the artifact. Later
steps will include evaluations which investigate if
the BP system is useful for an organisation.
Peffers et al. (2007) have presented a process for
design science research consisting of a number of
activities as described below. We used this process
to describe our work according to these activities:
1. Identify problems and motivation: The first
activity in the design science process according
to Peffers et al. (2007) is to identify a business
problem that motivates why the artifact (i.e. in
our case the BP classification system) needs to
be designed and developed. The business
problem in our research is the lack of support for
managing a large number of BPs within an
organization, including finding appropriate BPs,
relating BPs to each other and increase the
understanding of which areas of an organization
that are lacking BPs.
2. Define objectives of a solution: The second
activity defines desirable requirements on the
artifact that specify how the artifact solves the
problem. These requirements will guide the
design and development of the artifact and will
also form a basis for its evaluation. The main
requirement in our research is to assess how easy
it is to use the system to classify BPs.
3.
Design and develop: The third activity describes
the artifact in focus including how it was
designed and developed. In our research, a BP
classification system was developed based on an
in-depth literature survey of existing BP
frameworks. Based on this survey, presented in
Alwazae et al. (2013), we identified a set of
variables and values for classifying BPs.
KMIS2013-InternationalConferenceonKnowledgeManagementandInformationSharing
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4. Demonstration: The forth activity aims at
showing the use of the artifact in an illustrative
or real-life case, thereby proving feasibility of
the artifact. In this paper, a demonstration has not
been carried out since the focus is on evaluation.
5. Evaluation: The fifth activity determines how
well the artifact solves the problem taking into
consideration solution objectives (i.e. the defined
requirements). In our research, the evaluation
was carried out by asking 20 students to each
collect two BPs from companies, asking them to
classify the BPs, i.e. apply the BP framework on
the collected BPs, and asking them to motivate
each choice of classification.
3 THE DESIGNED ARTIFACT:
THE BP SYSTEM
In this section, we describe the designed artifact, i.e.
the designed BP classification system (Alwazae et
al., 2013). The BP classification system consists of a
set of features, called variables and possible values
for each variable. The classification is based on the
argument that knowledge and BP are embedded
within a set of contextual dimensions that are critical
for the organization’s ability to organize, utilize and
extract value from the knowledge. The BP
classification system was designed based on a
literature study in which we focused on identifying
candidate papers by means of reviewing literature of
BP. To be a candidate paper, it needed to present
features for a BP system. They ended up with 26
candidate papers and, based on features (i.e.
variables) identified in these papers, they designed a
BP classification system. The variables of the BP
system were 1) degree of cooperation 2)
organizational level, 3) scope, 4) completeness of
description, 5) degree of quantification, 6)
implementation areas, 7) level of formalization.
Each variable had a set of possible values that can
vary depending on knowledge characteristics. Each
variable and value was explicitly defined. Please see
Appendix that includes a full description of each
variable and values.
Some of the advantages for the BP classification
system are that it can facilitate the identification of
an organization’s BPs to re-index their practices in
order to discover which practices are difficult to
classify. It helps to document the organization’s
practices making it easier to search and utilize BPs.
Additionally, it will prevent reinventing the wheel
when similar problems present themselves. Finally,
it decreases repetition of BP documentation since
there will be a repository of BPs to be shared within
the organization (ibid.).
4 EVALUATION
OF THE ARTIFACT:
THE BP SYSTEM
In this section, we describe the approach used to
evaluate how easily the BP system was utilized to
classify BPs. In this section, we also describe the
result of the evaluation. The evaluation was carried
out according to the steps presented below:
Step 1: We conducted the evaluation with 20
students who were attending a Master’s level
Knowledge Management course at the Department
of Computer and System Sciences at Stockholm
University. In this first step, we asked the students to
contact organizations and collect two written
descriptions of BPs from the organizations. The
descriptions needed to be structured according to a
template distributed electronically and in-person to
the students. The template highlighted important
parts of BP: background, problem, goal, method and
solution. The task, as well as the concept of BP, was
presented to the students during a lecture.
Step 2: The next step was to ask the students to
evaluate how easy it was to categorize the BP
according to the system. We created a structured
questionnaire, in which the students classified their
collected BPs according to the values and variables
as well as their motivation behind their chosen
values. This was done in a two-hour seminar. Then,
we examined incomplete answers or missing
answers by cross-referencing their responses with
their original collected BPs. In case of ambiguities in
their answers, students were asked for clarification
and complimentary additions.
Step 3:In this step, we compiled and analyzed the
results from the evaluation. We found that the
students collected BPs from twenty organizations of
varying sizes and which operated in diverse domains
such as IT, manufacturing, banking, governments
etc.
In this evaluation study, we used a convenience
sampling method, as we did not control the choice of
organizations involved in our study. We allowed the
students to choose any organization, whether small
medium or large, and in any domain. The only
requirement was that the organization studied should
focus on KM.
VerifyingtheUsefulnessofaClassificationSystemofBestPractices
407
Table 1: Organizations studied.
Type Number
Organization
IT 13
Manufacturing 9
Public 4
etc. 8
Size
Small 8
Medium 12
Large 14
Interviewee
CIO 2
General Manager 10
Manager 13
Operational level 9
Table 1 presents the details of the organizations
from which the BPs were collected. Due to the
sensitivity of the material presented in this paper, we
do not name these organizations. However, some of
the organizations are major and well-known
multinational organizations.
We are aware of the fact that when one involves
students, the validity of the results may be strongly
jeopardized. To assure the quality of the data
collection, we prepared the Master’s students in
several consecutive steps. We first gave a lecture on
the subject and later, during a seminar, presented the
questionnaire and explained the motivation behind
each of its questions.
5 ANALYSIS AND DISCUSSION
In this section, we present the results of the
classification of BPs and our evaluation. We also
compare the results from the classification carried
out by students with the results from the literature
study presented in Alwazae et al. (2013). Finally, we
present an analysis of the evaluation.
The results of the students’ classification of the
BPs, according to the BP system, are presented in
Table 2, under the heading “Occurrence in collected
BP out of 40”. The results of the students’
classification of their BPs are also compared with
the results from the literature study, see heading
“Occurrence in literature out of 26”. The literature
study was carried out as part of designing the BP
classification system (see Alwazae et al., 2013),
which classified papers and presented the occurrence
of values of each variable that signified the nature of
the BP and is presented in Table 2.
During the students’ classification of their BPs,
they originally encountered difficulties in
understanding the classification system with respect
to choosing the appropriate values for the variables
that suited their practice domain. However, after
refining and explaining the variables and values
presented in the BP system, they could easily
classify their BPs.
The results show that all values of the variables
were identifiable and utilized, which shows that the
BP system could work as an instrument for
classifying BPs. If only some values were present
and recognized, the BP system would have been of
limited aid in classification.
The results of the students’ classification of their
BPs was compared with the results from a literature
study, see Table 2. The comparison showed many
similarities between literary and student accounts.
This might show a legitimate and sound BP system
for classifying BPs. However, further investigation
needs to be carried out to make more conclusive
statements regarding the system’s valid usability.
The comparison also showed variance regarding
some values such as ‘technical area’, which occurred
8% in literature and 47.5% in industry. Also,
‘informal’ values occurred within 70% of the
literature and only 30% in industry. One way to
account for these variances may be that the students
came from a social-technical department; a large
group of students were collecting BPs from software
companies, see Table 1.
The students were also asked if they considered
some variables or values to be missing. In general,
the students claimed the BP system was exhaustive.
However, some students identified one additional
value pivotal for classifying BP. This value, within
the variable “Scope”, was department specific
(named “Departmental enterprise” in Table 2). The
students classified 8 BPs according to this value.
We define “Departmental enterprise” BPs as
focusing on specific work related tasks within a
department. However, this value does not exist
within the 26 collected papers and explains why this
value was not an option during classification.
We found that when examining organizational
BPs, an unforeseen value was documented, as was
seen with the value “Departmental enterprise.”
Although the students were able to identify a new
value, the identification of a new variable did not
occur. The reason for this could be that the values of
the variables may depend on the context of the
practice and may become more evident in future,
more comprehensive, studies.
KMIS2013-InternationalConferenceonKnowledgeManagementandInformationSharing
408
Table 2: Result of the classification from literature (Adapted from Alwazae et al., 2013) and from industry.
Variable Value
Literature occurrence
out of 26
Industry occurrence in
collected BP out of 40
Degree of
cooperation
Competitive 19 73% 24 60%
Collaborative 7 27% 16 40%
Organisational
level
Operational 17 65% 25 62.5%
Tactical 6 24% 5 12.5%
Strategy 3 11% 10 25%
Scope
Departmental enterprise 0 0 8 20%
Local Enterprises 17 65% 22 55%
Global enterprises 9 35% 10 25%
Completeness of
description
Complete with context 4 15% 12 30%
Basic parts 22 85% 28 70%
Degree of
Quantification
Qualitative measures 19 73% 19 47.5%
Quantitative measures 5 20% 14 35%
Mixed measures 2 8% 7 17.5%
Implementation
areas
Technical area 2 8% 19 47.5%
Business area 18 70% 15 37.5%
Management area 6 23% 6 15%
Level of
formalization
Informal 18 70% 12 30%
Semi-formal 5 19% 16 40%
Formal 3 11% 12 30%
The students were also asked to explain the
motivation behind their choice of values. The
students justified all the chosen values with some
exceptions (only 15 values out of 280 were not
clearly justified). In a majority of the cases (265 out
of 280), we interpreted student motivations as
convincing. For example for the choice of value
"Operational" (for the variable "Organisational
level") a typical motivation was "the BP is focusing
on an operational routine", and for the value
"Management" (for the variable "Implementation
area") a typical motivation was "the BP is supporting
decision making for upper management". From
these results we conclude that it was easy for
students to choose a certain value.
6 RELATED RESEARCH
In literature, there are different BP systems for
different domains. For instance, in the enterprise
architecture domain, The Open Group Architecture
Framework (The Open Group, 2011) and Zachman
model (Zachman, 2008) are well known systems,
while in the quality management domain the popular
systems are ISO 9000 (Peach, 2003) and Six Sigma
(Pyzdek and Keller, 2009). For the IT enterprise
management and IT governance domains, the
Control Objectives for Information and Related
Technology (COBIT) framework is more suitable
(ISACA, 2012). Also, the Information Technology
Infrastructure Library (ITIL) is a popular framework
for IT services (Hendriks and Carr, 2002). The
Balance scorecard is a popular framework
measuring the performance of an organization
(Martinsons et al., 1999). Common among these
frameworks is their summarization of many
experiences describing how work should be
organized between people within a particular context
(Graupner et al., 2009). Although these frameworks
do not directly address how BP is organized,
classified and performed, they can, however, offer
some guidance.
The literature about BP is mainly descriptive.
Some papers describe the BPs that an organization
has in place. Others are limited to describing the
dissemination of BP without discussing in detail the
necessary context related to the practices (Davies
and Kochhar, 2002). The description of necessary
background components (i.e. context) of BP would
help organizations determine whether a BP is
appropriate for their business or not. For instance,
within the ITIL framework, there is a lifecycle phase
with each phase including a number of specific
processes such as incident management and supplier
management (Nezhad et al., 2010). The descriptions
of these processes are directed to employees and to
be followed in their respective work domains. Such
a context, in this case the phases of the life cycle,
will support the classification of the processes, and
VerifyingtheUsefulnessofaClassificationSystemofBestPractices
409
could be used for classifying other BPs.
7 CONCLUSIONS
In this paper, a BP system for classifying BPs has
been evaluated. The evaluation shows promising
results. First, all values of the variables were used by
students when classifying BPs, which shows that the
BP system supports the classification scheme.
Second, the students could justify their choice of
values, which suggests the BP system is easy to use
for classification. Third, the comparison to the
classification of research papers in the BP area
shows similar classification results. This indicates
comprehensiveness when classifying BPs. Fourth;
the students claimed that the BP system was
exhaustive.
Our next step of further refining and evaluating
the BP system will be carried out according to the
design science strategy presented by Sein et al.
(2011). This artifact will be further developed in an
iterative evaluation process with feedback from BP
experts to provide an integrative perspective of
quality measures or checklist for the usefulness of
BP implementation. Therefore, to introduce this BP
system into practice and evaluating it is a necessary
step for its success.
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APPENDIX
Variable and values definition (Adapted from Alwazae et al., 2013).
Variable
Definition
Value Definition
Degree of
cooperation
Degree of cooperation
means the practice is
focusing on increasing
competitive edge or
increasing collaboration
Competitive
Competitive means that best practice is focus on making a,
practice, a product, or a service more competitive.
Collaborative
Collaborative means that best practices is focusing on
collaborative knowledge sharing for creativity and
ingenuity/innovativeness
Organisational
level
Organisational level means
the level in an organization
that the best practice
focuses on
Operational
Operational means that the best practice focuses on a particular
operational routine or business process
Tactical
Tactical means that the best practice focuses on tactical short-term
goals
Strategy
Strategy means that the best practice focuses on more overarching
strategic long-term goals
Scope
Scope means the area or
extension that the best
practices focusing on
Local
Enterprises
Local Enterprises means that the best practice focusing on one
single organization
Global
enterprises
Global enterprises means that the practice is focusing on a
multinational organization
VerifyingtheUsefulnessofaClassificationSystemofBestPractices
411
V
ariable and values definition (Adapted from Alwazae et al., 2013) (Cont.).
Variable
Definition
Value Definition
Completeness
of description
Completeness of
description means if the
description contains a
necessary context for using
the practice or just basic
parts
Complete
with context
Complete with context means that the practice can be used without
the user being familiar with the context because it contain the
context (that is, when to apply, where to apply, who applies it,
why to apply, and how to apply)
Basic parts
Basic parts means that the user of the practice must be familiar
with the context in order to know how to use the practice, that is, it
mainly includes how to apply it
Degree of
Quantification
Degree of quantification
means the type of valid
measures assigned to the
best practices
Qualitative
measures
Qualitative measures means that interpretive, soft, measures are
assigned to practices
Quantitative
measures
Quantitative measures means that numerical, hard, values are
assigned to practices
Mixed
measures
Mixed measures means that both soft and hard measures are
assigned to practices
Implementation
areas
Implementation area
means the area that a best
practices is aimed to be
applied in
Technical
area
Technical area means that the area of application of the best
practices is technical
Business area
Business area means that the area of application of the best
practices is including some kind of business processes
Management
area
Management area means that the area of application of the best
practices is geared to upper-management and organizational
leadership and governance
Level of
formalization
Level of formalization
means the level of
formalization of the best
practices
Informal
Informal means that the best practices have the form of soft,
informal suggestions
Semi-formal
Semi-formal means that best practices have the form of directing
functional considerations, i.e. business rules, via established
organizational procedures
Formal
Formal means that best practices have the form of formalized
procedure with official adaptation and often embedded in IT
implementation of best practices, such as ERP or BPM systems
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