1heim.ifi.uio.no/~petterog/Kurs/INF5190/INF5190_NTAX_v0.7.doc · Web viewTable of Contents. 1 Introduction 3. 2 Theory 4. 2.1 Two types of knowledge 4. 2.2 Knowledge Management

INF5190 Concepts and Principles in Knowledge Management

Spring 2006 Page 1 of 27

UNIVERSITY OF OSLOFaculty of Mathematics and Natural Sciences

INF5190 – Concepts and Principles in Knowledge Management

Spring 2006Applying Knowledge Management for improving software lifecycle processes in the Norwegian Tax Administration

Written by: Petter ØglandHani MuradSturla BakkeAnne Berge Bjørnseth

Delivered: 12.05.06


Table of Contents1 Introduction..................................................................................................................32 Theory..........................................................................................................................4

2.1 Two types of knowledge......................................................................................42.2 Knowledge Management in an Actor-Network Theory perspective...................52.3 Knowledge Management in a Total Quality Management perspective...............6

2.3.1 Knowledge generation.................................................................................72.3.2 Knowledge codification...............................................................................82.3.3 Knowledge transfer......................................................................................9

2.4 Organizational theory........................................................................................102.5 Cultural theory...................................................................................................11

3 Method.......................................................................................................................123.1 Interviews and observations..............................................................................123.2 Text analysis......................................................................................................12

4 Case description and analysis....................................................................................134.1 Organizational analysis......................................................................................134.2 The NTAX software lifecycle model................................................................14

4.2.1 Knowledge generation...............................................................................144.2.2 Knowledge codification.............................................................................164.2.3 Mechanisms of knowledge transfer...........................................................16

4.3 Main ANT-concepts in a KM perspective applied within the organisation......174.3.1 Heterogeneity and negotiations.................................................................174.3.2 Inscriptions................................................................................................174.3.3 Translation.................................................................................................18

5 Discussion..................................................................................................................195.1 Two ways of understanding...............................................................................195.2 Knowledge generation.......................................................................................19

5.2.1 Knowledge evaluation...............................................................................205.3 Knowledge codification.....................................................................................20

5.3.1 The preservation-level of Opera’s knowledge sources..............................205.3.2 Knowledge map.........................................................................................21

5.4 Knowledge transfer............................................................................................225.4.1 Socialization..............................................................................................225.4.2 Internalization............................................................................................225.4.3 Externalization...........................................................................................225.4.4 Combination..............................................................................................23

6 Conclusion.................................................................................................................24References..........................................................................................................................25



1 IntroductionThe report is written as part of the assessment in INF5190 – “Concepts and Principles in Knowledge Management”. The project group has chosen to look at the software lifecycle for one of the major processes at the Norwegian Tax Administration (NTAX), namely the self-declaration process for private citizens. The report’s primary focus is to investigate to which extent the concepts of Knowledge Management (KM) can give insights on the software lifecycle model, and how such insights may be used for process improvement.

In our understanding of KM, based on the INF5190 lectures and the course literature, we tend to see KM as partly an information technology induced management philosophy and partly a management philosophy drawing upon insights from total quality management (TQM). While process improvement seems to be one of the major drivers for installing Knowledge Management, we have, however, found little indication of there being a clear bridge between the specifics of quality management and knowledge management.

Using an organization, such as NTAX, as a case for investigating the practical aspects of KM and TQM relate thus seems to give context to important research questions, from the perspective of information management, quality management and knowledge management.

In the next chapter we will try to provide a perspective on KM within in the context of quality management and information infrastructure theory. The purpose of this exercise is to differentiate between two distinct views on knowledge that seems to be one of the core ideas of KM, namely tacit knowledge and explicit knowledge, although will argue for Kuhn’s way of differentiating between the two rather than the way of Nonaka.

This sets a framework for empirical research, and in the third chapter we give a short description of the methods we have applied when researching NTAX. Results from the case analysis are then presented in chapter four. The results include an analysis of how the knowledge processes of knowledge generation, knowledge codification and knowledge transfer are implemented in the software lifecycle. We try to differentiate between two perspectives on knowledge by applying TQM and ANT separately.

The fifth chapter contains a discussion of case analysis, where our emphasis has been to use aspects of KM as a way of synthesizing parts of the case analysis that came either from a control perspective or a design perspective. The type of problems one tries to solve puts an constraint on what will be a natural and efficient epistemology. However, as KM aims at handling all aspects of knowledge, both social knowledge and technical knowledge, we try to use this framework for giving a more holistic view on process improvement within the software lifecycles at NTAX.

We chose to conclude the report by commenting on whether we felt the approach gave an added perspective on process improvement, and also give some recommendations for further process improvement at NTAX.



2 TheoryOur intent with this chapter is to describe knowledge management within a wider philosophical context that includes a perspective on technical and social knowledge representing two distinct types of knowledge, suited for solving two different types of problems. We continue by elaborating on what we see to be the characteristics of knowledge management within each of these two domains, and then conclude the theory chapter with one section on organizational aspects and one section on cultural aspects.

2.1 Two types of knowledgeKuhn (1962) argues that scientific knowledge evolves in two directions. The normal way of accumulating knowledge is by solving puzzles according to rules defined by the current paradigm of doing science within a given discipline. Every now and then, however, this paradigm may be challenged, and new ways of understanding the world may evolve.

The way Kuhn describes the process of doing scientific research is strikingly similar to how Argyris and Schön (1978) suggests how to create organizational learning through what they call the model of “double loop learning”.

Figure 1 – Double loop learning (Argyris & Schön, 1978)

An organization may learn through the methods of quality management, i.e. identifying errors and opportunities for improvement, and work of ways to improve the system based on such insights, as would correspond to “single loop learning”. However, from time to time it may strike the organization that the whole system should have been designed in a completely different manner, so by challenging the current assumptions and beliefs, the variables governing the single loop learning may be adjusted. This external perspective on the system is referred to as “double loop learning”.



Jashapara (2004: 135) suggests total quality management (TQM) and business process engineering (BPR) as a possible way for understanding or implementing double loop learning. In the appendix B of ISO 9004:2000, it is suggested that double loop learning should be a natural way of operating any ISO 9001:2000 certifiable quality management system, where the inner loop learning is handled by methods for creating continuous improvements (“kaizen”; Imai, 1983) while the outer loop is handled by “breakthrough management” (Juran, 1964).

What seems to us to be not all that clearly stated in the quality management literature, and knowledge management literature, is the way the inner loop and outer loop of double loop learning seem to correspond to two different ways of understanding the world. In our understanding, the difference corresponds to the “two cultures” of natural science and social science (Snow, 1964), meaning that the two cultures deal with two different concepts of knowledge, corresponding to whether the purpose of the research is to predict and control nature or whether it is to “understand” a culture from an anthropological point of view, i.e. to understand the language of the tribe in terms of observing what they tend to do.

Kuhn explains his gradual understanding of scientific discovery to start with the understanding of hermeneutics (Lee, 1991). A similar approach may be used for explaining Deming’s image of the organization as a learning system. In fact, Sherkenbach (1986: 35) uses a model similar to figure 1 to illustrate the Deming philosophy of organizational learning by illustrating process improvement within the current system as the inner loop feedback mechanism between supplier and producer, following the usual methods of statistical process control, while the outer loop feedback mechanism corresponds to consumer research.

In this presentation we consequently try to distinguish between knowledge processes related to the social science of the outer loop, using Actor-Network Theory (Latour, 1987) as a possible framework, while applying the traditional methods of statistical quality control (Deming, 1992) for analyzing the knowledge processes within the inner loop.

2.2 Knowledge Management in an Actor-Network Theory perspective

Within the science and technology field it is of importance to be able to formulate and understand information, innovation and knowledge management processes, and hence ANT was created; in order to better understand not only what kind of knowledge that exists and gets distributed in an organization, but also how, and by that exploring how a knowledge network is created (Monteiro, 2000). ANT is, although it is called a theory, more of a material/knowledge-semiotic method that gives us a powerful linguistic tool to describe KM processes and relations.

Rather than looking at knowledge as something that is contained by someone or something, it is possible or even feasible to recognize knowledge as a network, or network of contextualized data and information, and that this network may consist of



both knowledgeable and may be not so knowledgeable humans, non-humans like i.e. information processing and storing kinds of software, a web of experience, an urge to tell and a yearning to know. In all, a suitable network for the creation and transformation of knowledge from tacit to explicit and back, in addition to tacit to tacit and explicit to explicit. In an environment of learning in multiple directions and contexts, we form networks of knowledge, where we teach and learn, show and tell, exchanging a mix of tacit and explicit knowledge in a both structured and unstructured manner, with all the influencing factors that are comprised of earlier experience, education, familiarity with the tools needed to understand and manage a task, relations to others and so on. We might say that the tools for facilitating KM to a certain extent resembles Information Infrastructures as it is described by Hanseth and Braa (2000) and Monteiro (2000) as open networks, linked to others networks indefinitely, and as such, not necessarily easy to control.

It may help, though, to look at infrastructure as Dahlbom does, as a “regulating skeleton, providing framework and guidelines for the activity”, and even if the immaterial nature of knowledge makes it seemingly incompatible in relation to a physical infrastructure, the more important aspects of an infrastructure is in fact immaterial; agreements, standards and metrics. An important element in Information Infrastructures is the idea of gateways, which is a method for combining two, or more, initially incompatible actors (standards). In an ANT perspective this could be regarded as translation, and in KM as a tool for knowledge distribution. According to Dahlbom, the stable infrastructures of the information society would be its educational institutions, research organisations, legal systems, habits and so on, as a shared resource. (Dahlbom, 2000:217-220), and by sharing, knowledge is created and distributed.

2.3 Knowledge Management in a Total Quality Management perspective

Although the best definition of Total Quality Management (TQM), in a European context, may be the evaluation critera for the annual quality awards (EFQM, 2006), when discussion the knowledge management principles underlying the ideas of quality management, we chose to focus on the ideas put forward by Shewhart and Deming.

A good starting point for discussing KM within the context of TQM is perhaps by looking at the ISO 9000 model for designing quality management systems (figure 2). Although the figure appears to consists of a single loop, the system model can be thought of two consist of two loops or two types of logic as illustrated by the box indicating “measurements, analysis and improvement” having input from processes and products on one hand (single loop feedback) and input from customers on the other hand (double loop feedback).

In fact, if we identify the customer box on the left hand side of the diagram with the customer box on the right hand side of the diagram, the structure would topologically be possible to be described as a torus, i.e. a topology of double loop learning that is identical to the Argyris model in figure 1 or the Kuhn model of how science evolves.



Figure 2 – The NS-ISO 9000:2000 quality management framework

As we have already presented Statistical Process Control (SPC) as a tool for knowledge management as a previous INF5190 presentation (Øgland, Bakke, Murad & Bjørnseth, 2006), in this presentation we will just summarize some of the main insights from the presentation.

2.3.1 Knowledge generationAccording to Davenport and Prusak (1998: 52), knowledge generation refers to: “…, the specific activities and initiatives firms undertake to increase their stock of corporate knowledge”. They characterize the importance of knowledge generation in this way: “…since it is axiomatic that a firm’s greatest asset is its knowledge, then the firm that fails to generate new knowledge will probably cease to exist.”(ibid.: 67). Davenport and Prusak (ibid.) divide knowledge generation into five modes; acquisition, dedicated resources, fusion, adaptation, and knowledge networking. Here we will rather concentrate on the difference between acquisition and production of knowledge, and how these concepts relate to the ISO 9001:2000 model.

Acquisition of knowledgeAcquisition refers to the dimension of knowledge generation where the knowledge is acquired by the organizations as well as that developed within it. In chapter 6 of ISO 9001:2000 there are requirements related to people having sufficient competence for performing tasks, and that the competence shall be documented.

Producing knowledge



The main process for generating knowledge with the ISO 9001:2000 model is by recording problems and areas from improvement. Although there are requirements all over the model aiding to define a consistent model that will make learning and improvement possible, the main issues are related to chapter 8 in the ISO model where there focus is on applying (knowledge) metrics.

2.3.2 Knowledge codificationKnowledge codification involves codified material such as texts and computer systems that organize and contain knowledge of an organization. The purpose of knowledge codification is: “…to put organizational knowledge into a form that makes it accessible to those who need it” (Davenport and Prusak 1998: 68).

Making a quality system in compliance with the ISO 9000 requirements and recommendations would be a typical example of a system for codifying, storing and managing knowledge for the purpose of improving organizational performance. As the focus of the system is on quality (conformance to standards), the process of codifications runs mostly through the processes of quality control.

In order to perform quality control of processes and products, the standard way of doing this would be by identifying metrics for all critical aspects of the organization and use statistical process control (SPC) for monitoring whether the processes are stable and under control (Deming, 1992).

In other words, codification starts by identifying what may go wrong or what we would like to improve, and then select metrics that are useful from this perspective. In chapter 4 of ISO 9001:2000 there are also requirements dealing with how to create a map to illustrate how the processes connect.

This may be useful for understanding how processes are related when we want to understand the root causes for something going wrong or what to predict the effects of improving related processes. What seems to correspond the most directly with the concept of knowledge maps (or topic maps) in knowledge management, however, is the quality management idea of using Ishikawa fishbone diagrams for mapping out the ontology of how things can go wrong.

The idea behind the Ishikawa fishbone diagram is that of indicating the five different “topics” that have proved useful for analyzing problems in industry; man, machine, materials, methods and metrics, catalogue problems as they occur (“occurrence”) and draw lines in order to make ontological “association”. In other words, the Ishikawa diagram, developed in the 1960s, should probably be seen as a prototype for what is now described as “topic maps”.

The main difference between the Ishikawa diagrams and the more general topic maps, however, is that the Ishikawa diagrams relates to the ontology of problems and errors while general topic maps can be used for organizing explicit knowledge in general.



2.3.3 Knowledge transferDavenport and Prusak (1998:101) state that knowledge transfer involves two actions; transmission and absorption. The goal of knowledge transfer is to improve an organization’s ability to work, so these two actions only provide value if they lead to change in behavior. However, as TQM in the context of ISO 9000 relates to the systematic aspects of knowledge transmission and absorption, we have added sections later in this theoretical section on organization theory and cultural theory.

Nonaka (1995:19) provides a model with four different modes of knowledge conversion with the basis in the terms tacit and explicit knowledge as the two main types of human knowledge.

Table 3 – Nonaka’s model of knowledge conversion

As one of the fundamental ideas in “The Knowledge-Creating Company” (Nonaka & Tackeuchi, 1995) is to explain innovation and develop processes in Japanese companies as compared to those of the West, focusing on the “tacit” culture of the East, his framework seem suitable for explaining why Quality Circles has been and still is an important aspect in Japan while it only lasted as a short-term fad in the 1980s in the West.

From the point of view of ISO 9001:2000, the idea is to have all management knowledge explicit in terms of probability distributions for making decisions, and by the process of doing so, knowledge can be codified as information to be transferred according to the traditional way of mathematical communication theory (Weaver & Shannon, 1949).



Table 4 –Mathematical theory of communication (Weaver & Shannon, 1949)

The significance of going from knowledge management theory to information management theory when dealing with knowledge transfer of quality related issues is that quality management can be dealt with in objectivist ontology.

In order to deal with issues that can’t be explained by numbers, tables and graphs, we need additional theory, such as the organizational theory and the theory of cultures.

2.4 Organizational theoryMintzberg (1983) defines five structures; the professional bureaucracy, the simple structure, the machine bureaucracy, the divisional structure and the adhocracy. These are structures that describe general configurations of organizations.

Mintzberg (1983) define nine organizational design parameters, categorized in four main groups. We have found three of these useful for the purpose of understanding the aspects of knowledge management needs in the type of organization we are looking at. The groups are:

Design of individual positions – the design parameters in this group covers job specializing, formalizing or work and training and indoctrination.

Design of “super-structure” – this covers the grouping of and the size of each unit. Design of communication between units covers fields like system for planning

and controlling, and also coordinating communication. The group called “system of decisions” covers two parameters called horizontal

and vertical decentralization. This has to do with where, or at what level decisions are made. It is about power structures.

These four groups are then used for analyzing the what Mintzberg see as the five different configurations:

Simple structure – suitable for a “one-man firm” and such. Machine bureaucracy – typically for the industrial workplace (e.g. a factory). Professional bureaucracy – organizations based on professional skills.



Organizations in divisions – an incompletely configuration but with clear terms on single fields, suitable for large and complex companies.

Adhocracies – the innovative organization.

In order to determine a configuration, many factors have to be considered, such as situational factors. Mintzberg split these factors into categories such as; age and size, technical system, environment and power. In our KM analysis, however, we only plan to use some of the most basic aspects of Mintzberg ideas.

2.5 Cultural aspectsBy identifying the structural configuration of a given company, one would perhaps expect that much of organization culture is also explained as one would expect culture to evolve and adapt to fit the structure. However, in a constantly globalizing society additional cultural factors may be taken into account for understanding knowledge flow and development. In particular, we would like to see how the organization culture manifests itself or evolves in order to meet the hetrogenity among “customer” (tax payers).

Although globalization and hetrogenity may play a vital role in international business, for the processes we investigate within the tax administration, we do not expect it to play a vital part for understanding and improving the software lifecycle processes, but we would nevertheless like to add a perspective on the cultural issues as managing culture appears to be one of the most striking features of KM vis a vis TQM, e.g. through the emphasis on the interplay between tacit and explicit knowledge.



3 MethodOur approach for collecting knowledge and understanding NTAX has consisted; interviews, observations, textual analysis and project discussions.

3.1 Interviews and observationsAs one of the project members had been working as a quality manager within the IT function of NTAX and was still a part of the organization, we considered his knowledge from previous interviews and observations to be sufficient for the level of understanding that was needed for performing the analysis that was needed within the scope of the project. His previous interviews, observations and document controls had been following the framework of Action Research (Coghlan & Brannick, 2001), meaning that many of the interviews, observations and actions were done from the perspective of a change agent and thus biased in order to motivate organizational learning and improvement.

During the course of the project, however, he interviewed the current IT quality manager and made some questions to the head of the IT department and the some of the people working in software development and IT security issues.

3.2 Text analysisIn our treatment of text and documents we have used a qualitative approach. By this we mean that we focused on the documents as ”artifacts produced under certain material conditions”, where the authors are one, or several persons, that has access to materials not everyone has access to. One can say that the ”text is an artifact capable of transmission, manipulation and alternation” (Hodder 1994:394), hence ”products of a system within which they are defined and made meaningful” (Manning and Cullum-Swan 1994:464). The main sources for our textual analysis are Opera’s different web sites (Opera URL1), and the Opera brochure (2005) received from the PR executive.



4 Case description and analysisWe start by giving a short description of NTAX from the organizational perspective, in order to identify two major substructures we call the professional bureaucracy and the machine bureaucracy, and thus motivating a more narrow inspection of the software lifecycle models that are within the machine bureaucracy although bordering on the professional bureaucracy.

4.1 Organizational analysisThe diagram below gives a simplified description of how the Directorate of Taxes is organized.

Figure 1 – Simplified organization chart for NTAX

Consistent with the Mintzberg models in chapter 2, we chose to describe the tax administration to be a mixed configuration consisting of two different parts. The left hand side of the organizational chart represents the professional bureaucracy, mainly consisting of lawyers. The employers in this part of the organization don’t work here very long, so there is a challenge in transferring knowledge from one specialist to the next.

On the other half of the organizational char we have what we will characterize as the machine bureaucracy, with clear lines between the leaders and the workers, and no questions about there the powers of decision lay. Here the matter of knowledge management is taken care of by a conglomeration of computer based systems.

In the professional bureaucracy, expert knowledge is mostly tacit, and difficult or impossible to write down and put into procedures. Judgments and decisions made by specialists vary from case to case, and often the experts discuss among themselves how to interpret and handle difficult cases.


Directorate of TaxesBjarne Hope

CEOCEO

Declaration Department Collection Department Administration Department IT Department

Internal Audit

Machine bureaucracyProfessional bureaucracy


In the machine bureaucracy, on the other hand, knowledge about administrative and technological tasks may be tacit, but should, according to Weber (1979) at least, be put into procedures and managed in a rational manner, like a machine.

On the organizational chart we have also identified the internal audit. The purpose of the internal audit is to make independent investigations to sure that the quality management system is performing correctly, and that the organization is constantly improving. From the viewpoint of Knowledge Management, one could perhaps say that the internal audit at NTAX fulfills the role of the Knowledge Manager of the organization.

4.2 The NTAX software lifecycle modelAlthough there are different lifecycle models for the various systems being created and maintained at NTAX, the generic picture as shown below.

Figure 5 – Generic NTAX software lifecycle model (Skattedirektoratet, 1998)

mainIn order to We want to understand the knowledge

4.2.1 Knowledge generationAcquisitionIn Opera’s case acquisition is the main approach to get hold of knowledge. Every day Opera receives a large number of open job applications and CVs. They have well-established procedures to assess these CVs and to select good candidates from them. The chosen candidates are tested for six hours, before they are eventually hired. This process indicates that Opera have specific demands concerning knowledge and that knowledge is of great value for them.

Another way for an organization to acquire knowledge is to rent it. This means renting a knowledge source, as for example a consultant. (Davenport and Prusak 1998) Some years ago, during “peak” times, it occurred that Opera rented consultants. They were rented for



short periods to solve specific problems. Opera experienced however that the consultants gave wrong or inadequate solutions. Furthermore, the management in Opera realized that using external consultants could be a risk in the sense that they were sharing business-specific information. The management also saw that bringing in experts did not necessarily add new knowledge to the organization. Therefore, Opera decided to appoint people rather than renting human resources in order to acquire knowledge.

Dedicated resourcesOpera has no dedicated R&D department. On the other hand, they encourage their employees to do continuous training and education. It is scheduled that any employee can spend a certain number of hours (during working hours) to get to know new technologies or solutions. In addition, employees can attend optional lectures and workshops in order to maintain and update their competency. Moreover, they have some collaboration with the Research Council of Norway.

FusionMost of the work in Opera is performed in teams. Each team is composed of employees, often from different departments, with various skills and interests. According to Opera, the process of forming a team is an informal process. It is the employees themselves that request who they want to work with. Nevertheless, we would expect that the management has some kind of a final word in the composition of the teams. AdaptationOne of the biggest success factors for Opera is the adaptation to the W3C web standards. The knowledge they have obtained regarding these standards, create a very valuable platform for expansion for Opera as there an increasing number of employees who are familiar with it.

Knowledge networkingAs we have mentioned earlier, Opera offers a web-based community, the My Opera Community, for their users, where the users can contribute with opinions and knowledge and interact with each other and with Opera’s employees. In this case, Opera has created a community of knowers.

In addition, Opera participates on international IT-conferences. Here they can interact with and learn from other participants in the IT-business, and in that way they can generate new knowledge.

Partnership is third example of knowledge networking in Opera’s case. Opera has formed several partnerships with technology providers such as Adobe, IBM, Google and Nokia. Opera believe in working together with other providers, so that they can overcome obstacles and reach new levels of user benefits. (Opera URL2)



4.2.2 Knowledge codificationIn Opera, the employees have a lot of knowledge concerning all phases of software development. As far as we have identified in Opera, the following infrastructures, tools and documents can more or less be regarded as knowledge codification sources:

Working routines: documents that describe what the employees shall do. E-mailing and e-mail lists: are regarded as the most efficient and most used tools

for exchanging knowledge within Opera. Intranet: is used for resources like calendars, news within the organization, and

vacations. Different Wikis: where people exchange informal messages in any topic. The Bug Tracking System (BTS) (Opera URL3): enables the QA-department, as

well as the users, to register bugs and add comments to what they find in Opera’s browser. 15 000 bugs are reported and stored in this system every year.

Project Management System (PMS): is a tool used to store all information related to a project.

my.opera.com (My Opera Community URL): Community for users of the Opera-browser.

WAR room: is established when launching a new project. Portals: in some situations, a project group establishes their own portal, in order

to easily display updated information related to the project only. For example, the mobile product line utilizes this with the so-called “mobile portal”.

Opera does not have any knowledge map in their organization. They regard themselves as a relatively small organization where everybody knows everybody. That means that every employee knows where he/she can find knowledge.

4.2.3 Mechanisms of knowledge transferThe management in Opera is fully aware of the importance of maintaining knowledge within the organization. Work groups are often composed of people with the same competency in order to make sure that the knowledge remains in Opera in case people are leaving. Cross-co-operations between departments and functions are regarded as a good way to provide a variety of tasks and to exchange knowledge.

Shannon and Weaver 1949/62

Nonaka’s model for knowledge conversion section 2.3.4 is the basis for the following analysis.

SocializationIn Opera, socialization is the most used method for transferring tacit to tacit knowledge. As mentioned earlier, Opera’s working environment can be characterized as very social with young people from different cultural backgrounds. So far, the management is relying on social interaction among employees as the easiest and most efficient way of



exchanging knowledge. Opera arranges “A night at the Opera” every Friday afternoon where the employees meet up and get to know each other in a different setting than in the daily office or workspace. In addition, they have tried to establish a light and open place of work with some comfortable lounge suites in the corridors. The management emphasizes that all employees have a friendly and open attitude, and they refer to each other with first names.

Externalization Externalization is the type of knowledge transfer that involves transferring explicit to tacit knowledge. Opera arranges workshops where employees get “hands-on-practice” by solving tasks in teams. They have also tried to run some video conferences with co-workers staying in other geographical location (like countries in Asia and the USA), but the method was not regarded as efficient nor convenient.

InternalizationWhen it comes to internalization, which comprises how to transfer explicit to tacit knowledge, project evaluations are important. Opera admits they do not have any formal standards or routines for running evaluations.

CombinationThe combination mode is how to transfer explicit to explicit knowledge. In Opera’s situation, this is a process that must be supported by a technical infrastructure. Existing technical tools are listed and described in the previous section “Knowledge codification”.

4.3 Main ANT-concepts in a KM perspective applied within the organisation

4.3.1 Heterogeneity and negotiationsA rather central aspect of Actor-Network Theory is the concept of the heterogenous network, meaning that such a network consists of actors (and actants) that are physically different, working together, creating a solid network capable of facing eventual resistance that might rise against it, and doing so through successful negotiations leading to a state where knowledge is the product of heterogeneity in action, where all the the heterogenous elements, both physical artefacts and immaterial entities such as organisation, work and is fitted together (Law, 1992). Just as the bigger Actor-Networks such as the Internet [the mother of all Actor-Networks], or the state of societal order, is the result of negotiations among a heterogenous web of actors unifying in creating the network, so is the actor-network that operates at a workplace, in this case, NTAX.

4.3.2 InscriptionsResults might be regarded as a sort reciprocal inscription, in that members of the organization make efforts to accomplish certain goals. In that sense, a potential achievement will have an impact on how they perform their work. In order to be able to measure their efforts during the work process, standards, metrics and routines have to be established. Another inscription is that knowledge itself is built into these metrics, standards and routines



4.3.3 TranslationIn a process of going from tacit to explicit knowledge, unstructured explicit knowledge, or from coincidental to scientific thinking, the members of the organisation will have to re-interpret distributed knowledge in alignment with one's needs, which in turn translates into a more general need eventually leading to a unified solution (Hanseth and Monteiro, 1998), all through the process of translation, which, in turn is based on a medium or standard into which it is inscribed (Callon, 1991), building the actual network unifying the actors, and which is done through the process of negotiation. At NTAX this could, as an example, typically be done through the language of statistics.



5 Discussion

5.1 Two ways of understandingIn this chapter we want to return to the idea about two epistemologies corresponding to the two cultural traditions of literary critique and natural science. As mentioned in chapter 2, we see the idea behind literary critique and storytelling in general to be an aid for discussing meaning and direction, while the idea behind natural science being that of finding out what is true or not when the direction of research (“paradigm”) is given.

While the distinction between the type of knowledge to be found within the traditions of literary critique and natural science may to a certain extent correspond to Nonaka’s distinction between tacit and explicit knowledge, as also pointed out by Kuhn (1962: 44), but we feel that the distinction between science and meta-science is missed in Nonaka’s argument. On the contrary, what seems to us to be a natural way of reading Nonaka is to think of tacit and explict knowledge as two ways of representing same level knowledge, like the practice on riding a bike and a manual on how to ride a bike. The way the concepts are used by Kuhn would, it seems to us, be more like the science of riding a bike on one hand and the sociology (or history) of scientists studying how to ride a bike on the other hand.

From out point of view, this distinction between science and the sociology of scientists seems to have an interesting parallel in production improvement and customer research. In public organizations, such as the Norwegian tax administration, the word “customer” may perhaps not be the most natural way of describing the tax payer, but in the terminology of ISO 9000:2000, the receiver of products (or services) from any process is named the “customer of the process”.

One important aspect of designing quality management systems according to the ISO 9000 standards, is to have systematic ways for working towards the goal of satisfying the customers. We will now describe some of the elements of Actor-Network Theory as a framework for understanding customers from an anthropological point of view.

In the remains of this discussion, we will look at the processes of knowledge management from this perspective of the knowledge management system and the sociology of the knowledge managers.

5.2 Knowledge generationAs we noticed from the section on knowledge management and total quality management, viewing knowledge management as a “normal science” (Kuhn, 1962) seem to give clear operational definitions for distinguishing between data, information and knowledge. As all knowledge can be codified as statistical distributions, all the knowledge management processes can be handled as information management processes (Weaver & Shannon, 1949), and all other KM concepts seem to fit into the framework of viewing the organization as a machine. The language of systems thinking and artificial



intelligence seems to be a natural way for describing, analysing and improving the organization from this point of view.

We will also argue that this could perhaps be the best way of approaching knowledge management in the public sector, as public sector organizations are supposed to be a part of the national and international infrastructure, and thus to function predictably as a machine. Even though Nonaka and Tageuchi (1995) point out that Cartesian dualism is less apparent in oriental philosophical traditions, Cartesian dualism being the basis for modernity and scientific thinking, this does not seem to indicate that the way of the machine bureaucracy would be a less natural way for the Japanese. On the contrary, as has been pointed out by Tsutsui (1998), some of the keys for understanding Japanese management seems to be work in better harmony with the ideas of Taylor and Ford than what has been the case in Europe and the US.

What seems to make a difference, though, is the issue of consumer research. Understanding consumers from the perspective of designing, producing and marketing requires sociological, anthropolical and psychological knowledge, depending on the type of product and the type of consumer. Although mass production for mass audiences does not necessarily require as much sociological or anthrological insight as more specialized products or specialized consumer groups would require, the type of knowledge is different. In the case of process improvement of the software lifecycles at NTAX, we have looked at the people responsible for the software lifecycles from the perspective of ANT, in order to see whether this will create knowledge on how to improve the process improvement strategies.

5.2.1 Knowledge evaluationAs we mentioned in section 5.2.1, Opera has several types of networking practices. The Opera community has participants who profoundly discuss every aspect of the browser, hence the standards it is built on. This intensive and knowledge-full community of practice hence tests several ‘best practices’ (for example compatibility and scalability) in a way that increases the robustness of the product. Elements (solutions, algorithms or compatibility choices) inside the browser will be discussed thoroughly, and this is a valuable source of knowledge for Opera. We mentioned two other types of networks in section 5.2.1

5.3 Knowledge codification

5.3.1 The preservation-level of Opera’s knowledge sourcesAs we mentioned in chapter 2.3.3, it is vital in the knowledge codification process to ensure the knowledge’s distinctive attributes. In Opera’s case, there are several different codification sources that support different areas. An important question in regard to this is therefore: to what extent do Opera’s knowledge codification sources preserve the knowledge’s integrity?

In general, a rule of thumb is: “…, some structure for knowledge is necessary, but too much kills it” (Davenport and Prusak 1998:68). Since we have not studied the knowledge



codification sources in Opera, we can not discuss the sources’ level of knowledge-preservation in detail. Still, we may assume that some of the more business-oriented sources like the BTS (Bug Tracking System) and the PMS (Project Management System) have some degree of structure in the knowledge they hold. That is because these systems are of great value to Opera’s debugging activities and project activities respectively.

5.3.2 Knowledge mapThe problem with electronically based knowledge codification sources, which Opera’s sources can be considered as, is that they in most cases only embed explicit knowledge. This can be supported by Davenport & Prusak’s (1998:70) following statement about tacit knowledge: “Tacit, complex knowledge, developed and internalized by the knower over a long period of time, is almost impossible to reproduce in a document or database”. In our opinion, tacit knowledge is extremely important in software development, and thus also in Opera’s case. For example in programming you are dependent on tacit knowledge in order to attack complex problems. An important question concerning this is therefore: If the knowledge codification sources of Opera only contain explicit knowledge, how can the employees in Opera find tacit knowledge in the organization?

As we have mentioned earlier, Opera’s main focus when they appoint people is that they have knowledge. We suppose that Opera also emphasize skills in practicing the knowledge. Evidently, this should indicate that most of the employees have both explicit and tacit knowledge in their working fields. Nevertheless, it is obvious that one can not know everything, and now and then needs to seek knowledge elsewhere in the organization. A knowledge map is helpful in this situation. As we stated in chapter 5.2.2 (analysis), Opera does not have any kind of knowledge map that tells the employees who knows what. The management in Opera thinks that the organization is quite transparent and thus easy to find knowledge across departments. In our view, it might be that the size of Opera not inevitably necessitates a knowledge map. However, we would recommend that they make one as they are characterizing themselves as a “growing company”. They should at least make one for the most critical departments in the company, like the Engineering and QA. Besides being beneficial for the knowledge-seekers, it would also be useful for the management when they consider the composition of project-teams.

On the other hand, it is not obvious how Opera should assemble a knowledge map. Davenport and Prusak (ibid: 73) suggest two methods. Either “…use surveys that ask employees what knowledge they have and where they get the knowledge they need to do their jobs”, or “…follow a trail of recommendations,…” where they talk to a knowledge source in the organization that another person in the organization has recommended and so on. Which of the two methods Opera should choose, is not easy to conclude. There are both pros and cons to the two methods. However, we think that the first method probably is the least time-consuming, and hence maybe the most suitable alternative for Opera.

Two other factors to consider in connection with knowledge maps are what form they should have and where to put them. Davenport and Prusak (ibid.) advocate for electronically based knowledge maps. They argue that an electronic map can be revised and distributed more easily than a knowledge map in a paper document. Furthermore,



Davenport and Prusak mention Lotus Notes and Web browser/intranet systems as widespread tools for making knowledge maps accessible. In our opinion, making an electronically based knowledge map accessible from Opera’s Intranet sounds like a sensible solution in Opera’s case. That is because most of the employees in Opera evidently are used to work with computers, and Opera also has an existing Intranet.

5.4 Knowledge transferThe methods for transferring knowledge is following Nonaka’s model introduced in section 2.3.4.

5.4.1 SocializationOpera has established good conditions for the process of transferring tacit to tacit knowledge, referred to as socialization. Arranging social events and creating a workspace where it is possible have informal talks are major factors in this process. However, it is still important for the management to be aware of the motivation factors and activities that must be in place in order to maintain and improve the existing organizational culture. The company will probably expand during the next few months and years, and it is critical to rely on this way of transferring knowledge. The project group recommends the management to look at the other modes of transferring knowledge (other than socialization) suggested in this chapter.

5.4.2 InternalizationAs identified in the analysis, Opera lacked some activities related to the process of transferring explicit to tacit knowledge, named internalization. When it comes to project evaluations, it is suggested that the management prepare routines for evaluating tools, techniques, competency, main problems and its solutions, shortcomings and economy for every project. Opera has already got PMS (Project Management System) to track information related to projects. It is suggested to continue exploiting this tool in order to evaluate the quality of work performed in the company as a whole. This will make the organization able to “learn from failure” which is an important principle within knowledge management. Not having this principle in place might lead to different groups doing the exactly same mistakes over again. This is wasted resources and it can easily lead to dispersing blames and a destructive attitude instead of looking at it as a way to learn.

5.4.3 ExternalizationExternalization is a very important mode of knowledge conversion, and should be highly emphasized in Opera. For example, how can a programmer in the production department be able to teach other colleagues how to write code efficiently? It seems like Opera’s attempt to arrange workshops is the best way to facilitate this kind of knowledge transfer at the moment. However, it can also be valuable to establish some kind of training programs tailored newly appointed employees. If it is possible, the project group suggests having a contact person (with competency in the selected area) to guide the new co-workers through formal routines, programming methods, demonstrate successful projects, and make sure they get to know the right people across the departments. This activity can



be more efficiently carried though by appointing a group of people at the same time, not scattered throughout the quarter.

5.4.4 CombinationWhen it comes to transferring explicit to explicit knowledge, Opera is facilitating a number of tools. The management states that e-mails are the most efficient and most frequently used way of exchanging messages and ideas. Encouraging people to use discussion forums instead, can be good way to make sure that the information is getting retrievable from a repository later.



6 ConclusionAs a result of the project group’s investigations in the software cycles at the Norwegian Directorate of Taxes, it has been detected a few areas of potential improvements. Today, the tax administration makes limited use of internal metrics for process monitoring, internal benchmarking and process improvement, although they have formal routines that makes it possible to compensate for loss of tacit knowledge due to turnover.

In order to support the knowledge generation in the software lifecycle, we believe the cultivation and nurturing a knowledge-sharing culture and motivation of employees may be more efficiently achieved by applying internal metrics and deriving knowledge from these metrics through the use of methods of statistical quality control. Aligning the knowledge management strategy with the quality management strategy should form the the foundation for establishing and maintaining knowledge generation.

When looking at the existing working environment related to the software lifecycles in the tax administration, it is obvious that socialization is the most used method for transferring knowledge within the organization, although most aspects of the methods are made explicit through documents in one way or another. The need for making everything explicit is consistent with the traditional needs of the bureacracy, while the fact that most of the important knowledge is kept inside the heads of a few IT experts seems to be consistent with the psychology and sociology of information technology intensive environments. Because of this, the project group concludes that it is important to focus on integrating the current software lifecycle quality management system with the technical infrastructure, and thus making the knowledge processes more fully integrated into the logic of the bureacracy.

The technical infrastructure forms basis for the codification of knowledge in the tax administration, which is a central topic in the report. The project group discusses implementation and use of knowledge maps, in the style of Ishikawa fishbone diagrams and Pareto charts, for understanding how problems relate to eachother and how to address the problems in a more systematic manner. The charts and diagrams should be available to all parts of the organization by making better use of the Intranet.



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Documents

1heim.ifi.uio.no/~petterog/Kurs/INF5190/INF5190_NTAX_v0.7.doc · Web viewTable of Contents. 1 Introduction 3. 2 Theory 4. 2.1 Two types of knowledge 4. 2.2 Knowledge Management