Knowledge Management in Public Administration: Critical Success Factors and Recommendations

Academic Paper 2013 74 Pages

Business economics - Economic and Social History


Table of Contents




1. Literature review
1.1. Knowledge and KM
1.1.1. Knowledge
1.1.2. KM in theory
1.1.3. Organisational learning
1.2. KMSs in the public service
1.3. Implementing KMS and IT - Success factors
1.3.1. IS-Impact measurement model (Gable et al., 2008)
1.3.2. CSF in public organisations (Yang and Maxwell, 2011)
1.3.3. Success factors in phases of the implementation

2. Research methodology
2.1. Research purpose
2.2. Research approach - quantitative vs. qualitative approach
2.3. Reliability and validity
2.3.1. Population, target group and sample
2.4. Research question and hypothesis
2.5. Framework data of the tax administration of NRW
2.5.1. Organisational structure of the tax administration
2.5.2. Organisational structure of local tax authorities
2.5.3. Information system
2.6. Research design

3. Data presentation
3.1. Validity and reliability of collected data
3.1.1. Validity
3.1.2. Reliability
3.1.3. Limitations
3.2. Socio-demographic characteristics
3.2.1. Age group
3.2.2. Professional position
3.3. Organisational/human dimension
3.3.1. Organisational requirements according to Nonaka and Takeuchi
3.3.2. Organisational culture
3.3.3. The learning organisation according to Argyris and Schön (1996)
3.3.4. Organisational aspects and processes in tax administration
3.4. Technological dimension
3.4.1. General structuring of information by the management
3.4.2. Information sources and the intensity of use
3.4.3. Knowledge demands
3.4.4. ISYS performance
3.4.5. Practitioners’ handbooks
3.4.6. Wikis

4. Conclusions and recommendations
4.1. Hypothesis I
4.2. Hypothesis II
4.3. Hypothesis III
4.4. Hypothesis IV
4.5. Hypothesis V
4.6. Summary and future research

5. Reflections



Figure 1 Ackhoff’s hierarchy from data to wisdom

Figure 2 Congruence of explicit/implicit knowledge and usage of media, Daft & Lengel (1986)

Figure 3 The knowledge spiral. Source: Nonaka & Takeuchi

Figure 4 Nonaka’s spiral of science of organisational knowledge creation

Figure 5 OL in GSO within external influences. Source: LSE Public Policy Group

Figure 6 Holistic approach of KM according to Lee and Choi (2003)

Figure 7 Fundamental mechanisms, process, and payoffs in public-sector KMS. Mcnabb (2007)

Figure 8 KMS subsystems. Mcnabb (1997)

Figure 9 IS success model, DeLone and McLean (2003)

Figure 10 IS-Impact measurement model, Gable et al. (2009)

Figure 11 CSF in public service environment in accordance with Yang and Maxwell (2011)

Figure 12 Basic organisational structure of the NRW tax administration (own illustration)

Figure 13 Organisational structure of a local tax authority

Figure 14 Data diagram of employees vs. respondent in departments

Figure 15 Data - age group of the sample

Figure 16 Data - professional position of the respondents

Figure 17 Data – elements of the knowledge-creating organisation, according to Nonaka/Takeuchi

Figure 18 Data - organisational culture of the tax administration

Figure 19 Data - organisational culture divided in positions

Figure 20 Data - elements of learning organisation according to Wenger

Figure 21 Data - information structure preparation

Figure 22 Data - Intensity of the use of information sources

Figure 23 Data - knowledge demands and their assessment

Figure 24 Data - assessment of ISYS according to Gable et al

Figure 25 Data – practitioners’ handbook usage

Figure 26 Data – practitioners’ handbook structure

Figure 27 Data - readiness to share knowledge

Figure 28 Data - wikis

Figure 29 Knowledge transfer through communities of practice (own illustration)

Figure 30 Expert - Generalist - Paradox (own illustration)


Table 1 CSF of IT according to Gable et al. (2008)

Table 2 Critical success factors for the implementation of a KMS

Table 3 Cronbach's Alpha

Table 4 Data - knowledge collection and dissemination

Table 5 Data - knowledge manager or KM department

Table 6 Data - inter-service cooperation


About 30,000 people are working for the tax administration of NRW (Nordrhein-Westfalen, 2009) in Germany. They are appointed as case officers, tax auditors, programmers or leaders. Although their daily tasks are different, they are all led by the lawmakers’ mandate to determine and levy taxes. This means, among other things, that they must have a command of over 100,000 rules and regulations (Hahne, 2004). Knowledge workers spend 15-30 per cent of their working time actively searching for information with a success rate of only 50 per cent (IDC-Research, 2000). This is an enormous figure and the reason that many organisations experience maladministration. A promising discipline to tackle these problems seems to be the still quite recent discipline of knowledge management (KM) (Bontis and Serenko, 2009b).

Compared to the popularity of KM in the competitive economy, few statements in the literature about KM in the public administration can be found. One explanation is perhaps the lack of competition as an important driving force. However, budget pressure forces many governments in the world to aim for more efficient and effective processes in their entities.

Public administration sees its role primarily not as a service delivery organisation, in contrast to organisations in the competitive economy. The classical intervening public administration has to preserve social stability and internal security through prevention and reaction to interferences. The major task is, therefore, to keep social turbulences within acceptable limits (Dunsire, 1990). The actions of the public administration are oriented towards results and effects which are either legally prescribed or politically desired. The tax administration is an almost totally knowledge-based organisation. Knowledge is, therefore, the most important potential factor. The tax administration possesses knowledge about the society, the lawful or unlawful behaviour of taxpayers; knowledge about the administrating actions and their effects; about laws, regulations and directives and finally about themselves as an organisation. All this is dispersed in files, documents, data bases and especially human heads. This knowledge has clear and unclear components.

Enterprises, for instance, are only able to survive on the market if on the one hand their costs are lower than those of their competitors or if on the other hand their products and services are differentiated effectively (Porter, 1980). Differentiation is achievable by the application of the theory of the resource-based view. Therefore, the success of companies is crucially dependent on their accessible resources. In doing so the production factor of “knowledge” is gaining an increasing importance against the classical factors of capital goods, land and labour. The resource knowledge is viewed downright as a key resource for the future (Drucker, 2009).

The question occurring in this context is whether the abovementioned recitals are even valid for public services such as the tax administration.

At first sight the tax administration is not operating in a competing environment. But as the global economy tends to be one global, spanning market, the economical basis is dependent on competitive conditions such as business location and opportunities of capital investment. This is due to the fact that economic actors are nowadays able to shift their investments faster and to a greater extent than ever before. The state is, therefore, intrinsically linked with its economical actors. This is also due to the fact that an expensive and ineffective public service finally leads to higher taxes and is an economic strain on the firms who have to compete in an international market. Economical actors are only able to be successful if the state is not impeding the necessary adjustments to fast changes in today’s environment (McNabb, 2007). This only can be done by adapting to new conditions and becoming more effective and efficient (Friedmann, 2001). The aspiration for better structures and processes is an essential part of the new public management, which aims to adopt private economical management techniques (Politt and Bouckaert, 2011). Finally the enormous public debt of €147 billion in NRW at the end of 2009 is an obvious indicator that NRW lives beyond its means (Nordrhein-Westfalen, 2010).

“A state is only as good as its administration. The administration is as good as its civil servants. The civil servants are as good as its education” (Kohlrust and Heilmann, 1968). This citation is still valid, although it is from 1968. A satisfaction survey in NRW has revealed a rather mediocre professional competence on the part of the tax administration as perceived by taxpayers, tax consultants and visitors to the tax authorities personnel (Oppermann, 2004). This seems to be a decent result considering the complexity of tax law, but it turns out to be unsatisfactory when regarding the sensitive field in which the tax administration is operating (Senger, 2009).

The tax administration is a knowledge-based environment where tax officers are facing great challenges due to the permanent flood of new information such as frequent changes in legislation, new court decisions, directives etc. (Yuen, 2007). The speed of change in the tax law environment and the dynamics of new legal developments have steadily increased (Kirchhof, 2011). In addition it is necessary to enter the subsumed results subsequently through many different figures into a complex computer system to ultimately produce the tax bills.

This flood of information necessitates a structured, fast and reliable information system to get reliable information for day-to-day work.

It is supposed that employees spend a lot of time to get targeted information with unsatisfactory results. This is primarily due to a poorly structured intranet system called ISYS, and the result of not knowing where to get particular information. The objective of ISYS is to provide all employees with extensive information about official issues, themes of particular interest for the tax administration and interesting news for the individual scope of duty (OFD-Rheinland, 2007). In addition, the general scripts, essays or books often do not contain only one topic. The search results, therefore, render a lot of material which first has to be arranged.

A KM initiative initiated in early 2010 by the former state secretary of NRW contained, among other things, the following subprojects:

- Establishing a state-unified handbook for practitioners
- Implementing persons in charge for special issues
- Improving the query system in ISYS

Another organisational issue is the trickling of the processing of experience of certain case constellations that are not stored in a repository system. In doing so the provision of this knowledge is highly valuable for similar cases that need to be processed by other case officers. However, a systematic share of case-related experience is not established within the organisation.

This thesis is partitioned into five chapters. The following chapter, chapter two, is about the literature review and is broken down into subchapters. As a first step the epistemological insights about knowledge and types of knowledge in the tax administration are depicted. Moreover, the theory behind KM with its interrelating dimensions of technology, organisations and humans is reviewed. Furthermore, a conceptual framework of implementing IT successfully based on the IS Impact Measurement Model by Gable (2008) is illustrated. This is followed by critical success factors of knowledge sharing in public services organisations by Yang and Maxwell (2011). The chapter ends with a depiction of summarised best-practice actions in implementing KMSs.

Chapter 3 deals with the research question and the research methodology to be determined, followed by chapter 4, which presents the research findings based on the primary data collected. Chapter 5 contains a description of the key events occurring in this paper and reflections on the learning effects as a result of the research.

1. Literature review

This chapter deals with the most influential theories and insights of knowledge, KM and organisational learning. Furthermore, the chapter explains how knowledge management systems (KMSs) are to be implemented according to best-practice reports in the literature.

1.1. Knowledge and KM

Effectiveness and efficiency are achievable in a knowledge-dynamic environment through a strategic management of organisational knowledge (Becerra-Fernandez and Leidner, 2008). Henry (1974) states with regards to public administration “that new patterns of information and new information technologies can change the content and quality of public policies and by cultivating a new strain on politics and policy-making”. A lot of organisations have recognised this fact through the attempt to leverage their knowledge resources through technologies. There is no general definition of KM (Wallace, 2007). McNabb (2007) figured out that “knowledge management is a set of processes, practices and management philosophies that exist to collect, process, store and make available the organisational knowledge that enables government agencies to be more proficient and competitive in the delivery of public services”.

Although preliminary publications about KM existed in the 1960s, a more profound involvement was noticeable in the 1980s and became prominent during the 1990s (Wallace, 2007). This was a consequence of the discussion about new forms of organisations. Based on these discussions, it was decided that organisations should become more flexible, devolved and process-oriented. They should also abolish rigid structures to introduce flat structures and networks. All this, however, is only possible by establishing a culture of knowledge to conduce the flow of knowledge and information (Leidner et al., 2006). An organisational culture where members rest on an individualistic view of innovation aggravates the success of KM (Ibid.). Collectivistic and cooperative attributes of organisational actors tend to be beneficial in KM (Ibid). In bureaucratic cultures it is necessary that senior management is actively involved in the process of KM (Ibid).

1.1.1. Knowledge

Knowledge is an important resource in organisations and many authors have attempted to explain the term “knowledge” but with no uniform definition. Philosophers such as Kant (1781) and Popper (1987) have not compiled any definition about the term “knowledge”. Plato (428-347 BC) stated that knowledge is “true justified belief”. This statement was part of many interpretations in the discipline of epistemology. Popper (1989) argues that an approach to the truth is only possible by critical asking and by finding a new hypothesis if another one has been disproved.

Ackoff (1989) identifies four categories of the knowledge/wisdom creation process in a hierarchical order from data to information to knowledge and ends up with wisdom. Data are a reasonable combination of characters (letters, digits, special characters) which serve the codification of facts. Data are the basis for value judgments or interpretations and might be seen as raw material for information and is usually collected by observation (Davenport and Prusak, 1998). Information occurs through analysis and the arrangement and revision of data. (Ibid.). Information embodies the transition from data to knowledge. Knowledge contains information enriched with experience and is therefore more extensive than data and information. To generate knowledge the conversion by a human is necessary (Ibid.). Wisdom is a profound insight of cause and effect in certain events or situations linked with the personal attribute of abundance of patience to apply the proper action.

Based on Ackhoff’s hierarchy and the implication that a human’s cognitive ability is limited, Ackhoff argues that the cognition allocates in a percentage to the layers as follows (Figure 1):

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Figure 1 Ackhoff’s hierarchy from data to wisdom

Knowledge has the potential to generate new knowledge by sharing, combining and recombining it (Lester and Piore, 2004). Therefore, knowledge is capable of being applied across time and space to yield increasing returns (Garud and Kumaraswamy, 2005). Davenport and Prusak (1998) define knowledge as a fluid mix of framed experience, values, contextual information, expert insight and grounded intuition that provides an environment and framework for evaluating and incorporating new experiences and information. Knowledge originates and is applied in the minds of knowers. In organisations it often becomes embedded not only in documents and repositories but also in organisational routines, processes, practices and norms.

The most commonly used taxonomy for knowledge is the classification of Polanyi (1967) and Nonaka (1994) of tacit and explicit knowledge.

According to that classification, explicit knowledge is describable and may be standardised. This is usually expressed in form of a transformation in language or the ability of being convertible into language that is relatively simple (Nonaka and Takeuchi, 1995). Explicit knowledge is capable of being distributable, transmittable and saveable through media. It is generally available and remains stable over time. This knowledge is found in documentation, data bases, libraries, repository systems, organisational structures and processes in a methodical and systematic order.

Tacit knowledge is commonly referred as personal knowledge of an individual (Crowley, 2000). This type of knowledge is difficult to formalise, communicate or share, as it is mainly formed through experience that is memorised in the individuals. It is not directly describable and exists rather in an intuitive and/or unconscious form (Probst et al., 1997). It is, for instance, the pace in which an individual is able to perceive its environment or the knowledge of a football player about how to kick a ball accurately. The more complex the knowledge, the more it belongs to implicit knowledge (Gottschalk, 2007). The congruence of implicit and complex knowledge is apparent through knowledge-exchanging techniques recommending how knowledge can be exchanged best with the media (Daft and Lengel, 1986).

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Figure 2 Congruence of explicit/implicit knowledge and usage of media, Daft & Lengel (1986)

Explicit knowledge does not have the equal weight as tacit knowledge, as it has to be understood tacitly and is perhaps a subtype of tacit knowledge (Jensen et al., 2007). Polanyi (1969) stated: “While tacit knowledge can be possessed by itself, explicit knowledge must rely on being tacitly understood and applied. Hence all knowledge is either tacit or rooted in tacit knowledge. A wholly explicit knowledge is unthinkable”. This points out that the human dimension is critically important and must be considered meticulously in the learning process. Types of knowledge in the public administration

The management of knowledge requires the identification of the major groups of knowledge commonly existing in the public administration. Lenk and Wengelowski (2002) detect three types of knowledge groups in the public administration.

- Knowledge about processes and procedures
- Knowledge about cases and contents (contains facts and rules)
- Contextual knowledge (“world knowledge”)

The knowledge about processes or procedures encompasses knowledge about the work process. A typical process within the tax administration is characterised by the determination of what is to be taxed and to which amount. These actions are well-structured but there are also unstructured production processes. Many open decision processes such as the controversial taxation of tax bases or negotiated tax bases produce their own story. In the end the case officer must be aware of the processes and procedures to (inter)act in the most optimal way.

The knowledge of content can be broken down into the knowledge of facts and rules. An important subordinate of knowledge of rules is the legal knowledge. This type of knowledge is provided by different (semi-) professional sources (e.g., codes of law, juridical information systems). Knowledge of cases is meant by knowledge about current and closed cases. It has a significant role for the collective memory of an organisation, as it might be the basis for the development of knowledge of employees, the entire organisation and even as a basis for the legislative impact assessment.

Contextual knowledge describes knowledge about the environment and the world as a whole. It serves the understanding of facts of a case and is not clearly separable from knowledge about cases. A case officer who is processing a tax return of a software engineer who is declaring earnings below reasonable fees will initiate further investigations if the officer knows the common standard rates.

1.1.2. KM in theory

The theory of how knowledge is generated systematically within organisations by Nonaka and Takeuchi (1995), called the SECI-model, is perhaps the most cited model within the discipline of KM (Grant, 2007). Some scholars criticising no sound empirical grounding and no established link between knowledge and semantic information as the underlying data for the SECI-model comes from earlier studies of semantic information (Gourlay, 2002). However, the model provides a general understanding of organisational knowledge creation, which is essential for the concept of KM initiatives rather than as a practical guide for KM (Nonaka and von Krogh, 2009).

A central role of the SECI-model is played by the epistemological differentiation in tacit and explicit knowledge (Polanyi, 1966). Nonaka (1994) divided up tacit knowledge into cognitive and technical elements. Cognitive elements of tacit knowledge are mental models such as schemes, paradigm or beliefs that enable individuals to find their way in the world and achieve personal goals. Technical elements of tacit knowledge encompass the specific capabilities and competences of an individual that are applicable in a specific context. The second dimension of the model is ontological and describes the layers of generating knowledge. Organisations are not able to generate knowledge without individuals. Hence, organisations can only provide a framework that is conducive for the process of knowledge sharing. These different tiers of sharing and generating knowledge individually, in groups or in the organisation together, form the ontological dimension (Nonaka and Takeuchi, 1995).

By the transition of knowledge from tacit to explicit knowledge, new knowledge is generated. The individual is In the middle of this process that is generating new knowledge through social interaction. This model of knowledge development, which is generally termed the “knowledge spiral”, is based on four types of knowledge transition (Ibid.).

Socialisation describes the transfer of tacit knowledge directly from one individual to another without previous explication. This can occur through the observation of other individuals and through imitation or application of the observed behaviour.

Through externalisation tacit knowledge becomes explicit. The conversion happens by articulation or symbolisation. It is supposed that knowledge transferred from the knowledge carrier through analogies, metaphors, models or concepts implies being communicable and codifiable to be understood by the potential recipient of knowledge.

Combination merges explicit knowledge to generate new knowledge. This is supposed to happen through networks, documents or communication tools.

Explicit knowledge is being transitioned through internalisation to tacit knowledge. This conversion is achieved through the application of explicit knowledge and the subsequently resulting internalisation.

Nonaka and Takeuchi (1997) argue that a development of organisational knowledge is only possible through the continued and dynamic interaction of tacit and explicit knowledge. This interaction can be influenced by changed patterns of knowledge conversion which, in turn, are inducible by several triggers. The dynamic relations between the four types of knowledge conversions ideally form a self-reinforcing spiral (Figure 3).

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Figure 3 The knowledge spiral. Source: Nonaka & Takeuchi

With the exception of the combination the depicted processes are social processes between individuals. The development of organisational knowledge is not restricted to one tier but escalates onto higher ontological tiers when knowledge is being transferred to other knowledge carriers. This spiralled process is always induced through interaction of tacit and explicit knowledge on an individual level and will be transferred afterwards to a group or organisation level, thus embedded into organisational knowledge (Figure 4).

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Figure 4 Nonaka’s spiral of science of organisational knowledge creation

However, the knowledge spiral requires five key success elements (Nonaka and Takeuchi, 1995). Firstly, the organisation must have the intention, namely a proper strategy, standards and vision to steer the spiral. Secondly, the organisation should grant employees autonomy to raise motivation and enhance engagement. The third requirement is fluctuation and creative chaos to diminish rigid thinking and develop new concepts. The knowledge creation process also includes the existence of a certain redundancy to give knowledge workers sufficient time to acquire the necessary knowledge. The last requirement is the so-called internal diversity, which means that employees need sufficient flexibility and variety to meet the organisations’ environmental complexity. This also means that an organisation should employ different academic disciplines and backgrounds to become inspired by new ideas and theories.

1.1.3. Organisational learning

Organisational learning (OL) can be subdivided into several tiers dependant on the purpose and/or the organisational culture (Rashman et al., 2009). The taxonomy of Argyris and Schön (1996) in single-loop-learning, double-loop-learning and triple-loop learning (sometimes confusingly termed “deutero-learning”) is one of the most popular classifications of OL.

Single-loop-learning is about to ascertain a stable organisational existence. This means a continuous maintenance, acquisition and recovery of required knowledge to meet the basic organisational needs. Single-loop learning aims for the identification and adjustment of interfering deviations to keep or reach the desired condition. This process of regulation is ascertained through a constant adjustment of existing knowledge for the sake of upholding the administration. A change in fundamental conviction or basic orientation does not happen. This class of learning pursues better efficiency and the achievement of an objective within the given framework.

Double-loop learning empirically is triggered when single-loop learning does not lead to the desired objective. Previous basic orientations and self-conceptions will be questioned and perhaps modified, as they are the main reason for the shortage of satisfying results. This process of examination incurs a reorientation where at the end a new more effective standard will be established. Hence, it is necessary to unlearn the existing orientations to be open to new concepts and insights.

Triple-loop learning questions and analyses all sorts of learning process within the organisation. This is commonly referred to as a meta-level of learning where learn-promoting and learn-inhibiting issues will be detected. That is why it is considered as an approach of learn to learn. This level of learning is reserved mainly for the domain of political leadership, as it involves to a large extent ideological standpoints (Common, 2004).

According to a report sent to the National Audit Office from the LSE Public Policy Group, in terms of innovation, “government organisations may tend to focus on single-loop learning and to rely on political imperatives to sustain double-loop learning or broader revisioning” (10)(Gilson et al., 2009). This ideology is partly responsible for the inertia and lack of flexibility of government organisations, especially when it comes to necessary changes.

The LSE Public Policy Group also deems human resource management (11) as crucial within the reciprocal processes in organisational learning. A diversified compound of specialists within the organisation having different types of education such as managers, economists or psychologists might stimulate ideas and innovations and break down traditional structures.

Finally, the most impact on learning in government sector organisations (GSO) is steered by the political system (12). A public discourse with stakeholders, politicians and lobbyist groups might be an obstacle for an optimal organisational learning approach due to the “fishbowl” nature (Ranson and Stewart, 1994).

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Figure 5 OL in GSO within external influences. Source: LSE Public Policy Group

Web 2.0 has the potential to support the organisational learning process (Argote, 2011).

1.2. KMSs in the public service

A KMS is commonly only associated with IT ad hoc. KMS is much more than just IT, as the technological part is just one of three dimensions that a KMS is affected by. Based on a holistic approach of KM, three dimensions must be considered. These dimensions are the human dimension as the major actor, the organisation with its processes, structures and culture and finally the information technology dimension (Lee and Choi, 2003).

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Figure 6 Holistic approach of KM according to Lee and Choi (2003)

McNabb (2007) illustrates the mechanism, process and the payoff of a total KMS for the public service with a prevailing organisational culture of knowledge sharing and value-knowledge creation (Figure 7). The processes mutually interact by processing internal and external data. This raw data is an integral part of KMS. The raw data is transformed into information by people, technology and procedures. In a second step the information architecture will be implemented into the KMS, namely the knowledge development, knowledge transfer and knowledge sharing. Moreover, the stored knowledge must be transformed to be applied or used. This is possible through knowledge audits, communities of practice and knowledge registries. The final level is the transformation of an ethos of isolation to a culture of collaboration. All this leads to a reduction of bureaucracy and establishes a learning organisation that embraces changes and rewards creativity and innovation for the welfare of state and citizen.

Figure 7 Fundamental mechanisms, process, and payoffs in public-sector KMS. Mcnabb (2007)

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According to McNabb (2007), a KMS is a living system encompassing five collectively contributing subsystems (Figure 8).

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Figure 8 KMS subsystems. Mcnabb (1997)

Those subsystems all belong to one of the three influenced dimensions: the human, organisation and information technology dimensions.

1. Hardware and software tools that are able to facilitate the conversion process from data to knowledge are an information processes subsystem. Such systems must be able to ease the process of coding and shaping data and information to become knowledge. Tons of raw accounting data have no meaning if it is not possible to work with the data and bring the data into a context to generate valuable information. This subsystem facilitates the knowledge creation to a maximum by reducing superfluous processes that can be done by computers. It should support the learning activities on an individual and organisational level.
2. The social processes subsystem promotes the sharing and distribution of knowledge according to the SECI-process by Nonaka and Takeuchi (1995). The design of this kind of subsystem is dependent on the strategic objective of the KMS. If the KMS is about to act as a knowledge repository (such as wikis or document management systems) then the process of socialisation can be neglected. However, a strong focus is on the process of externalisation, combination and internalisation.
3. The most important key activities of the human interactions subsystem are knowledge audits, communities of practices and knowledge registries. Those activities are critical to facilitate the establishment of an environment embodied in the organisational culture where knowledge is gathered, assessed and conveyed.

Knowledge audits are one of the first measures to be taken when establishing a KMS. This technique allows identifying and cataloguing an organisation’s information needs (target) and knowledge assets (actual). Knowledge audits reveal the gap between the target and actual status (Griffiths, 2005).

Communities of practice (CoPs) are, according to McNabb (2007) “groups of people with like interests, knowledge, concerns, skills and training who come together in some social situation, such as an informal meeting or conference, to share what they know and what they do not know”. They serve the exchange of knowledge, insights and recommendations, help solve problems and discuss new issues and ideas. This is why they are also called communities of knowing (Boland and Tenkasi, 1995). Three elements define such a community:

- The domain or area of work is the basis of every community. It legitimates the existence and shows the members (and other persons) the value of their activities.
- The members form a network, which becomes a community. The members exchange ideas, questions and answers and therefore learn from each other.
- The practice of the interaction within the members is performed by certain manners and behaviours. The members use a particular language and certain narration styles and documents. This practice shapes a culture where the learning process is significantly promoted.



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Title: Knowledge Management in Public Administration: Critical Success Factors and Recommendations