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Final Report
Knowledge Management
INF 5190, Spring 2006
A analyze over the organization
( An analysis of NTax)
“Norwegian Tax Administration” (NTax)
by
Hani Murad
Sturla Bakke
Petter Øgland
Anne Berge Bjørnseth
Index
Abstract ............................................................................................................................... 3
1.
Introduction ................................................................................................................. 4
2.
Theory ......................................................................................................................... 4
2.2
Understanding KM.............................................................................................. 9
2.3
The Value of Knowledge Management ............................................................ 10
2.4
Data quality ....................................................................................................... 11
3.
Method ...................................................................................................................... 11
4.
The tax administration: Case study ........................................................................... 12
4.2
The organization – short overview ................................................................... 12
4.3
Discussion ......................................................................................................... 14
4.4
Tools in the organization for KM ..................................................................... 15
4.4.1
5.
Is it possible to view SPC (Statistical Process Control) as a KM tool? ........ 17
Conclusion ................................................................................................................ 18
References ......................................................................................................................... 20
List of Figures
Figure 1 Understanding KM ............................................................................................... 9
Figure 2 Data quality as a pivot point for KM .................................................................. 14
Figure 3 measuring noise vs. information Figure 4 measuring information vs. noise - .. 15
Figure 5 spending time...................................................................................................... 16
Figure 6 "Fishbone" model of Ishikawa ........................................................................... 16
Abstract
I don’t think we need an abstract section here since we are not writing a scientific
paper here. Our introduction section gave a brief outline of this report !!!!!!
BUT there is always room for an abstract in any report… what do you think ???
1. Introduction
Our project focuses on studying a Knowledge Management (KM) system within the
Norwegian tax administration. The tax directorate determines and collects taxes to
maintain a good social infrastructure by financing services like health care, education,
transport, etc.
One major strategy put by the tax directorate is that their services and products shall meet
the user’s expectations and needs.
This is aimed to simplify use of the taxation system.
Our aim is to study the way the directorate of taxes uses knowledge for
improving their processes. We narrow the study into focusing on one of the
IT processes, and try to give some suggestions on how to improve the
situation. (their knowledge management system)
(Our translation, Brochure from NTAX)
2. Theory
Knowledge management may be referred to as a procedural methodology integrating
the technical, organizational and behavioral issues associated with enterprise knowledge.
KM is part of a recent trend in business to view knowledge as a valuable asset for any
organization. Companies are defining their own KM strategies for expressing,
developing and distributing their knowledge assets.
Karl Erik Sveiby describes KM as “The art of creating value by leveraging the intangible
assets”. The Gartner Group states it in a more down to earth way: “KM is a discipline that
promotes an integrated approach to identifying, managing and sharing all of the
enterprise’s information assets. These information assets may include databases,
documents, policies and procedures as well as previously unarticulated expertise and
experience resident in individual workers.”[Loshin, D 2001, 8]
Therefore KM can be described as a strategic process to capture the ways that an
organization integrates its information assets with the processes governing the
manipulation of its intellectual assets.
Tacit and explicit knowledge
……..Knowledge codifying, transfer and sharing
For KM to be successful it has to be applied and shared, therefore basic conceptualization
of the concept of knowledge is essential. Most scholars, as Dyer and Nobeoka (2000)
divide knowledge into explicit/codifiable knowledge or information, and tacit knowledge
or know-how (Grant 1996, Kogut and Zander 1997, Nonaka 1994, Polanyi 1966).
Information is seen as easily codifiable knowledge that can be shared between actors,
assuming that ”syntactical rules required for deciphering it are known” (Kogut and
Zander 1997, 386).
By comparison, know-how involves knowledge that is tacit, ‘sticky’, and difficult to
Codify and transfer. It is unarticulated knowledge held in people's bodies and heads and it
forms the basis of creativity. It is not easily captured nor codified (Nelson and Winter
1982).
Therefore, tacit knowledge (knowing how) is embodied in the expert, who makes
judgement and acts without necessarily reflecting explicitly on the principles or rules
involved.
Whereas explicit (knowing-that, by contrast, involves conscious access and the use of
available knowledge in form of training programmes, instructions manuals, etc. (Ryle
1949/1984, pp. 25-61),
When we acquire a skill, we simultaneously acquire a corresponding understanding that
defies articulation thus explicit knowledge is ultimately transferred to tacit knowledge
(Polanyi 1958/1974).
Knowledge sharing thus refers to sharing not only codified information, but also beliefs,
images, personal experiences and contextualised practices (Ambrosini and Bowman
2001, Davenport and Pruzak 1998).
This is essential for Inter-organizational interactions to be useful and successful
Strategies in KM
………Categories of KM Strategies
Four categories of knowledge management strategies are used by multinational
corporations (MNCs).
* Codification strategies involve the transformation of tacit knowledge into explicit
knowledge in order to facilitate flows of organizational knowledge.
* Tacitness strategies keep organizational knowledge tacit in order to prevent flows of
knowledge to competitors.
* Focused knowledge management strategies regulate knowledge flows by controlling
the degree to which knowledge is encoded in forms that match the information intensity
and ambiguity of their knowledge.
* Unfocused knowledge management strategies attempt to regulate knowledge flows by
controlling the overall level of codification of knowledge without special consideration of
the capabilities of specific forms of codification.
Different types of organizational knowledge require matching forms of codification in
order to increase connectivity between different actors in the information flow system
thus improving performance of the organization as a whole
Culture and KM
……. Defenition,Perception and layers of culture
Culture shapes our repertoire of habits and styles, and informs us how to behave in
certain situations (Argyris 1976, Geertz 1973, Swidler 1986).
Schein (1996), describes culture in terms of three dimensions, artifacts, values
and basic assumptions. Joynt and Warner (1996) have a broader view: they include
human nature, relations to nature, activity orientation, human relationships, relations to
time, and space orientation as dimensions of culture. Mead (1948) specifies language,
nationality, education, profession, group, religion, family, sex, social class and
organizational culture.
Culture embodies the collective values and beliefs of an identifiable group— It represents
an important determinant of firm performance (Shane, 1992, 1993; Shane,
Venkataraman, & MacMillan, 1995) Culture has many dimensions or "layers" (Hofstede,
Neuijen, Ohayv, & Sanders, 1990; Hofstede, 2001). Fundamental to cultural studies "is
defining the proper level or layer at which culture should be assessed and understood"
(Lenartowicz & Roth, 1999, p. 783).
Cultural layers affect knowledge flow, distribution and sharing.
……. Family culture within organizational KM
From the perspective of organizations, family represents one layer of culture that affect
performance and profitability (Chrisman et al., 2002).
Zahra et al. (2004) subscribe to the resource-based view (RBV) of the firm (Barney,
1991) and suggest that the cultures perpetuated within family firms potentially promote
and sustain entrepreneurial activities, thereby providing them with a strategic advantage
over non-family firms.
………Globalization and culture
Global and multinational corporations increasingly build their Knowledge repository
using shared information systems that are developed and operated across a multicultural
environment . Teams often consist of professionals from different countries and their
cultural differences may impact the success and development of their projects.
A team's cultural orientation may be expressed by the degree of individualismcollectivism, and group diversity therefore affects several group performance variables.
……. Individualism and collectivism
individualism can be seen as a cultural pattern consisting of loosely linked individuals
who view themselves as independent with their own preferences, needs, rights and
contracts; whereas collectivism refers to a cultural pattern that consists of closely- linked
individuals who see themselves as belonging to one or more collectives – e.g., family,
organizations – and who are motivated by the norms, duties and obligations thus imposed
(Bhagat et al., 2002, 208, Triandis 1994, 1995, 1998). On the basis of a number of
cultural studies (see e.g., Kagitchibisi 1997, Markus and Kitayama 1991, Markus et al.,
1996, Triandis 1995, 1998)
Several scholars, as Bhagat et al. (2002, 208) regard the individualism/collectivism
dimension of cultural variation as the major distinguishing characteristic in the way that
different societies analyse social behaviour and process information.
The perceptions of key issues in KM vary strongly between different cultures depending
on external factors such as economic structure, technological status and national culture
of the environment in which the enterprise is working (Watson et al., 1997). Internal
factors include things like the IS manager’s relationship with the CEO and information
scanning behaviour (Watson, 1990).
…… Key issues in KM
The Society for Information Management (SIM) has periodically surveyed its members
since 1980 (Dicson et al., 1984; Brancheau et al., 1996). The SIM surveys classify
the key issues into four groups (Niederman et al.1991, Brancheau et al.,1996).
The groups are Technology Infrastructure (TI), Business Relationships (BR), Internal
Effectiveness (IE), and Technology Application (TA).
(TI) Issues focus on planning and control for network connectivity, information access
and data
storage. The focus is on the technology components needed to support modern
applications in businesses
(BR) Issues focus on the problems of managing the relationship between the business
enterprise
and the IS function, such as strategic planning, organizational learning, and IS
organization alignment.
(IE) issues deal with the basic activities of the IS function, such as software development,
IS
effectivity measurement and IS human relations. The focus of these issues is on planning
and control of the IS function.
(TA) category includes issues such as end-user computing, collaborative support, and
executive/decision support. These issues are related to the application of specific classes
of information technology to suit the individual enterprise
Coherence between IT strategy and overall business strategy gives
positive bottom line contributions from IT investments (Bergeroon and Raymond, 1995).
...........Culture as an inhibitor/ enrolment to knowledge sharing
Culture is often seen as the key inhibitor of effective knowledge sharing ( McDermott &
O’Dell 2001) . Organizations need often to alter their KM flow systems to fit into their
culture.
By linking sharing knowledge to solving practical business problems, organizations
bridge sharing knowledge to a pre-existing core value therefore applying knowledge
management in a way that matches the organization’s style; They also build on existing
networks people use in their daily work to make knowledge sharing more attractive and
concrete.
The goal of KM is the determination and harnessing of the value of the information
resources within the enterprise. [Loshin, D 2001]
To fully understand the needs and demands of knowledge management we have found it
necessary and useful to focus to organization theory. We all are familiar with Henry
Mintzberg book “Structures in Fives” so it’s natural for us to use this way of analyzing
procedure.
3. Understanding KM
Considering this observation made by Neil Fleming [fle96] as a basis for thought relating
to the following diagram.
Figure 1 Understanding KM
A collection of data is not information.
A collection of information is not knowledge.
A collection of knowledge is not wisdom.
A collection of wisdom is not truth.
The idea is that information, knowledge, and wisdom are more than simply collections.
Rather, the whole represents more than the sum of its parts and has a synergy of its own.
While information entails an understanding of the relations between data, it generally
does not provide a foundation for why the data is what it is, nor an indication as to how
the data is likely to change over time. Information has a tendency to be relatively static in
time and linear in nature. Information is a relationship between data and, quite simply, is
what it is, with great dependence on context for its meaning and with little implication for
the future.
Beyond relation there is pattern [bat88], where pattern is more than simply a relation of
relations. Pattern embodies both a consistency and completeness of relations which, to an
extent, creates its own context. Pattern also serves as an Archetype [sen90] with both an
implied repeatability and predictability.
When a pattern relation exists amidst the data and information, the pattern has the
potential to represent knowledge. It only becomes knowledge, however, when one is able
to realize and understand the patterns and their implications.
A pattern which represents knowledge also provides, when the pattern is understood, a
high level of reliability or predictability as to how the pattern will evolve over time, for
patterns are seldom static. Patterns which represent knowledge have a completeness to
them that information simply does not contain.
Wisdom arises when one understands the foundational principles responsible for the
patterns representing knowledge being what they are. And wisdom, even more so than
knowledge, tends to create its own context
So, in summary the following associations can reasonably be made:

Information relates to description, definition, or perspective (what, who, when,
where).

Knowledge comprises strategy, practice, method, or approach (how).

Wisdom embodies principle, insight, moral, or archetype (why).
Note that the sequence data -> information -> knowledge -> wisdom represents an
emergent continuum. That is, although data is a discrete entity, the progression to
information, to knowledge, and finally to wisdom does not occur in discrete stages of
development. One progress along the continuum as ones understanding develops.
3.2
The Value of Knowledge Management
In an organizational context, data represents facts or values of results, and relations
between data and other relations have the capacity to represent information. Patterns of
relations of data and information and other patterns have the capacity to represent
knowledge. For the representation to be of any utility it must be understood, and when
understood the representation is information or knowledge to the one that understands.
Yet, what is the real value of information and knowledge, and what does it mean to
manage it?
The value of Knowledge Management relates directly to the effectiveness [bel97a] with
which the managed knowledge enables the members of the organization to deal with
today's situations and effectively envision and create their future
3.3
Data quality
The quality of the data may have an important impact on the knowledge being produced.
Poor data quality may lead to incomplete knowledge and poor decisions.
Definition of data (Loshin, 2001: 31): In any data environment, the data owner is
responsible for understanding what information is to be brought into a system, assigning
the meanings to collections of data, and constructing the data model to hold the collected
information. In addition, any modification to the data model any extensions to the system
also fall under duties of the data owner.
4. Method
A series of publications made by the tax directorate were collected and analyzed for the
flow of data between different departments. One of our group members is currently
working at the IT dept. and his inside knowledge of the taxation system is utilized as
well.
In the study we have chosen to focus on the maintenance of the software life-cycle for the
self-declaration system.
5. The tax administration: Case study
5.2
The organization – short overview
We have taken a quick analyzing ( analysis of) overview over the organization NTax by
the terms of Mintzberg. This report is not a work of organizational theory so we won’t
cover all the Mintzberg’s way of analyzing the organization, but we have found it useful
to refer to this in order to understand the kind of knowledge flow, and the kind of
knowledge management problems there are (existing) in the organization.
Mintzberg deals with nine design parameters, grouped in four main groups. We have
found three of these useful for the purpose( of understanding) to understand the aspects of
knowledge managements needs. The ones are:

Design of individual positions - the design parameters in this group covers job
specializing, formalizing of work and training and indoctrination
o This we find interesting because it( describes) will tell you something
about how the organization deals with the knowledge transferring
between people

Design of “super-structure” – this covers the grouping of and the size of each
units.
o This is also an interesting ( angle)angel because it will tell something
about how the departments are organized physically and thereafter
something about ( the organization of their )they organize subunits.

Design of communication between units covers fields like system for planning
and controlling, and also coordinating communication.
o In our view nothing can function nor will it work without proper and
correct communication, analyzing (by) this parameter tell us a bit of how
the mechanisms for coordination(work) are.

This group called “system of decisions” covers two parameters called horizontal
and vertical decentralization. This has to do with where, or (at)on what level
decisions are made. It’s about power structures.
o This group of design parameters is important when it comes to analyzing
organization.
The goal with this (method of analysis)analyzing method is to(determine) determent( the
nature of NTax) what kind of organization the NTax are. Mintzberg separate in five
different configurations. These are the following:

Simple structure – suitable for a “one-man firm” and such

Machine bureaucracy – typically for the industrial workplace (i.e. a fabric)

Professional bureaucracy – organizations based on professionals (skills),

Organizations in divisions – an incompletely configuration but with clear terms
on single fields, suitable for huge and complex companies

Ad hocracies /the innovative organization.
In order to (determine)determent such a configuration you have to consider(many) a lot
more factors, like situational factors – Mintzberg split them into these categories: age and
size, technical system, environment and power. We have chosen(not to) to not discuss
those here and now.
Conclusion of analyze: ( analysis)
We append the organizational chart to illustrate the following:
When it comes to determine(determining) the configuration of the NTax organization, by
the terminology of Mintzberg, we have come to the conclusion that there is a mixed
configuration and one must se(look) upon the organization as (being)parted in two.
The unit that determine(s) rules and regulation we found to be a professional
bureaucracy. These jobs are mainly( occupied) situated by lawyers. The employers
doesn’t( these employees don’t) work there very long so there is an issue of( continuity
in) transferring knowledge to the next one in place.
The unit that works on collecting taxes is more characterized as a machine bureaucracy,
with clear lines between the leaders and the workers, and now question about where the
powers of decision( is located) lays. Here the matter of knowledge management is taken
care of by several computer based systems. We will talk more about this in the chapter
where we discuss the tools for knowledge management.
5.3
Discussion
Good
data
Bad data
Good / right conclusions
Operational efficiency
Betters decision making
Increases ROI
New customer acquisition
Operational inefficiency
Operational efficiency
Customer attrition
Constraints decision making
Restricts system and data migration
Bad / incorrect conclusions
Figure 2 Data quality as a pivot point for KM
By applying the above model to the Tax Directorate system one can see that faults in raw
data acquisition, delay tax returns, human errors and information flow bottlenecks lead
often to bad decisions and delays. On the other side(hand) correct data flow within the
system lead to better and faster implementation of decisions based on properly acquired
knowledge. This makes the system more flexible and open to changes dependent(
depending) on government directives and customer needs.
5.4
Tools in the organization for KM
There are several tools for KM in the organization. We have chosen to describe the
function of one system for statistical purpose, the SPC. This is a statistical software
which measures the dataflow in the organization. The aim is to become more effective.
To comprehend its value and use we have used another and simple example which we
tried to explain to the class in our presentation on Thursday 4th of May.
One of the group members went to a hospital in the Middle East to visit a family member,
where he had to pas a gatekeeper. This gatekeeper kept him staying for a long time,
examining his medical status and purpose of the visit. This took a long time before he
was able to pas on. He was experience what we would call noise, the gatekeeper acted as
a ‘bottleneck’ in his attempt to go on. We feel that this situation must be a problem for
the management, and thought that if they were to measure the time wasted in this process
they probably could become more efficient. That’s where the tool can be used. We aim to
achieve such a situation as illustrated below from ill 3 to ill.4;
Figure 3 measuring noise vs. information Figure 4 measuring information vs. noise -
The goal is illustrated like this:
Figure 5 spending time
We found it’s necessary and useful to look at the theory, illustrated like this:
Ishikawa, 1985
Man
Machine
Goal
Metrics
Method
Material
Figure 6 "Fishbone" model of Ishikawa
In the example with the gatekeeper at the hospital we have suggested some solutions, and
or explanations to the management, i.eg:

Remove the gatekeeper – exchanged the function by a computer

Teach/train the gatekeeper to do the job properly, and also

Such a gatekeeper is part of the culture, live with it!
5.4.1 Is it possible to view SPC (Statistical Process Control)
as a KM tool?
SPC is clearly an information management tool as it takes data as input, i.e. uses the flow
of data from a given process, and can then be used for indicating what parts of the data
are noise ("common variation") and which parts are signals ("special variation").
Whether SPC can be seen as a knowledge management tool relates to what we mean by
knowledge. E.g. if we consider knowledge as information useable for action, then SPC is
clearly a knowledge management tool as the point of the signals is to identify when an
error might have occurred and consequently reading it as a signal for action.
On the other hand, from the point of view of Shewhart and Deming, this does not count
as sufficient for being information, as they believe in the credo that there is no knowledge
without theory and that management is prediction.
In this paper we have tried to argue the similarities and differences of total quality
managmeent (TQM) and knowledge management (KM), suggesting that while the
management philosophies have very much in common, there are some significant
differences
In TQM the concept of quality is the basic unit of analysis
In KM the concept of knowledge is the basic unit of analysis
While the idea of improving quality can be applied to all aspects of the organization,
including the quality of knowledge, perhaps some of the main insights comes from the
new generation of KM, i.e. TNKM where the ideas of Nonaka & Takeuchi about social
knowledge (tacit knowledge shared among several people) produces an epistemology that
is significantly different from the epistemology of Scientific Management and TQM, in
the West, due to the "modern" concept of Cartesian dualism.
We believe that Statistical Process Control (SPC) should be seen as a KM tool, as
indicated by the discussion in section 5, but this also implies that we face a problem in
distinguishing between TQM and KM. We consequently need to elaborate more on the
importance of operational definitions and how this concept is important for Deming and
Shewhart and how it narrows the world of TQM into a world where concepts like tacit
knowledge is not a part of the agenda.
In fact, there should be some parallel’s here in how Polanyi's original definition of tacit
knowledge was conceived as a reaction towards the implementation of popperian science
in the USSR.
6. Conclusion
Anne:
In my contribution to the report I have tried a practical approach across disciplinary. In
order to understand the needs of knowledge management at the NTax organization I have
found it’s necessary to understand and analyze the organization. Since this is neither a
course in nor a work report of organizational theory I have chosen to do so very simple, a
“light analyze”. I have found that the organization has different characteristic units, so
that the needs of and the demands to managing information flows in the organization are
different. The NTax-organization is very big and we have no opportunity to cover the
different need of the whole organization and every tool they use. We have chosen to look
at one tool, the SPC. This statistical tool help improve efficiency processes in the
organization, singling out ‘noise’ from the data flow, illustrated earlier on in the report.
Hani
Culture……
Global business and national organizations including NTax in today’s world cross
political and cultural barriers to make business and deliver their product.
Differences in cultural patterns can both hamper and facilitate knowledge sharing in an
organization.
By reducing communication barriers based on differences in cultural perceptions an
organisation can enhance knowledge transfer and improve its own knowledge
management system.
By focussing more on statistical methods and metrics, NTax can facilitate the transfer of
implicit knowledge to explicit knowledge in its infrastructure, thus getting one step
closer to achieving its objectives.
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