**The Liberation of Intellectual Capital Through the Natural Evolution of Knowledge Management Systems**

Harold M. Campbell\* *Vaal University of Technology South Africa*

#### **1. Introduction**

394 New Research on Knowledge Management Models and Methods

Niculescu C. (2009), Knowledge Product Management in Knowledge based Organizations,

Nonaka, I., Takeuchi, H. (1995), The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford Universuty Press Pflaging, J. (2001), Enterprise Collaboration: The Big Payoff,KMWorld, available at:

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*Temporal Methods*, http://citeseer. comp.nus.edu.sg/751889.html

Systems, University of Regensburg, D-93040 Regensburg

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Bucharest

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Ed. RisoPrint, Cluj-Napoca;

*Enterprise Portals*, Addison-Wesley Press

*Systems*, Prentice Hall, New Jersey

Group Publishing, Hershey, SUA

Intelligence, *The MIT Press*

MCB University Press

*Encyclopedia – UNESCO*

"*The Proceedings of the Ninth International Conference on Informatics in economy*",

The research literature on knowledge management (KM) suggests that the valuation and measurement of intellectual capital (IC) is important to business intelligence (BI) and organisational performance. Harnessing the power of KM requires an effective communication interface which will allow the successful process integration of IC with organisational performance. The seminal research of Nonaka & Takeuchi (1995), and Brown & Duguid (1998) among others, established that effective communication of knowledge obtained from an organisational milieu is essential to organisational performance.

For this to happen, the organisation needs to craft an innovative and viable design of its business systems. A business system design (BSD) comprises of a dynamic architecture which is isomorphic across firms in space and time. It is a dense dynamic nexus of social capital, human capital and KM. A firm's IC, is seen as the resultant of its knowledge management network, as posited by von Krogh et al. (2000). Intellectual capital (IC) represents a firm s meta-capability aimed at exploiting opportunities in its continual pursuit of value creation. This process has been one of the most important sources of international competitiveness for some time.

This chapter takes the view that knowledge is shared among organisational members, because, it is connected to the firm's history and experiences, and will soon become the ultimate replacement of other resources. This notion underpins a more general idea that economies of the future will be education-led (Eftekharzadeh (2008)). It means that the capacity to manage knowledge-based intellect will be the critical skill of this era.

If there is one distinguishing feature of the new economy that has developed as a result of powerful forces such as global competition, it is the ascendancy of IC. Competitive, technological, and market pressures have made continuous organisational learning a critical imperative in global strategy effectiveness (Day & Tate (2006), Hislop (2005), and Campbell (2009)).

Allied to this is the seminal work of Nonaka & Takeuchi (1995), on knowledge creation, where their theory of knowledge creation identified four categories of knowledge assets. These being:

1. experiential knowledge assets (tacit knowledge, shared through experience);

<sup>\*</sup>H. M. Campbell is the HoD: Department of Industrial Engineering, Vaal University of Technology.

This is not embedded in some process nor easily transmitted and shared without some systematic effort. The characteristics of tacit knowledge are a subjective view or understanding of a topic, an artefact, an intuition or an internal feeling in the sense of a cultural prejudice, experience, tradition or belief. Tacit knowledge is based on informal metrics, non-standard experience, personal conceptions or convictions. The literature supports this view of tacit knowledge (Nonaka & Takeuchi (1995), von Krogh et al. (2000),

<sup>397</sup> The Liberation of Intellectual Capital Through

Fig. 1. Modes of knowledge common in the knowledge spiral ( Campbell (2005))

aligned to the four areas of active KM, are the following five processes, of KM:

projects. These five KM processes are discussed next.

The classification of the foregoing is represented as the modes of knowledge, common in the knowledge spiral, as are illustrated in Fig.1. This figure seeks to explain how active knowledge sharing may be conceived in an organisational milieu. Active knowledge sharing, according to Campbell (2005), subsumes that most organisations will be focusing on one or more of the following four areas: (a) innovation, (b) responsiveness, (c) productivity, and (d) competency, as discussed in Campbell (2005). Consequently, this research takes cognisance of the processes of gathering, searching, filtering, conceptualizing, and transferring of knowledge, at the firm level (Campbell (2005), Hislop (2005), Day & Tate (2006), and Eftekharzadeh (2008)). As such,

in which Campbell (2005), discusses how technologies can be used in the context of KM

and Campbell (2005)).

the Natural Evolution of Knowledge Management Systems

1. business intelligence; 2. asynchronous groupware; 3. organisational learning; 4. structural capital, and 5. human knowledge,


These categories of knowledge are linked to Nonaka & Takeuchi (1995) modes of knowledge creation and the type of *ba*<sup>1</sup> involved. These platforms aid in giving form to the impact of knowledge on innovation processes, in terms of the characteristics of knowledge. There are three such characteristics which influence the innovation dynamics. These are:


These characteristics of knowledge inform the central role of tacit knowledge to innovation processes is well recognised (Gous & Schutte (2009); Campbell (2005); von Krogh et al. (2000); Campbell (2009); Eftekharzadeh (2008)).

The rest of the chapter is divided into five sections:


We now discuss these concepts in greater detail in the next five sections.

#### **2. KM research**

The most common classification of knowledge in the KM literature may be considered to be that of von Krogh et al. (2000), to date, where an ambiguous distinction between '*explicit knowledge'* and '*tacit knowledge'* is proffered. Explicit knowledge is codified or articulatable in a formal manner (Nonaka & Takeuchi (1995)). Explicit knowledge can be easily passed on from one medium to another; that is, it's transferable. 'Tacit knowledge', on the other hand, may be seen as implicit knowledge or hidden knowledge, as opposed to explicit knowledge. Tacit knowledge is personal knowledge, which is bound to the individual.

<sup>1</sup> *Ba* - platforms for knowledge creation.

<sup>2</sup> Drupal - *www.Drupal.org* is the official website of Drupal, an open source content management platform.

2 Will-be-set-by-IN-TECH

These categories of knowledge are linked to Nonaka & Takeuchi (1995) modes of knowledge creation and the type of *ba*<sup>1</sup> involved. These platforms aid in giving form to the impact of knowledge on innovation processes, in terms of the characteristics of knowledge. There are

These characteristics of knowledge inform the central role of tacit knowledge to innovation processes is well recognised (Gous & Schutte (2009); Campbell (2005); von Krogh et al. (2000);

1. KM Research concepts - a review of the recent literature which includes definitions of terms as well as a conceptual model for business intelligence, asynchronous groupware,

2. Research goal - insights from the literature surveyed, a discussion of the innovation processes and network dynamics in terms of the need for intra-organisational collaboration, and the possible types of strategies organisations must devise through external networks, so as to access the requisite knowledge for competitive advantage and

3. *Drupal*<sup>2</sup> - highlights of the analysis, limitations of the research and the contribution of the current technologies of content management aimed at managing the integrated knowledge

4. Directorate - a summary of a case study, which describes an iteration of the AR cycle conducted at Directorate, one of the human resources departments of the public service

5. Concluding remarks - the chapter then points to the way forward for practitioners, and

The most common classification of knowledge in the KM literature may be considered to be that of von Krogh et al. (2000), to date, where an ambiguous distinction between '*explicit knowledge'* and '*tacit knowledge'* is proffered. Explicit knowledge is codified or articulatable in a formal manner (Nonaka & Takeuchi (1995)). Explicit knowledge can be easily passed on from one medium to another; that is, it's transferable. 'Tacit knowledge', on the other hand, may be seen as implicit knowledge or hidden knowledge, as opposed to explicit knowledge.

<sup>2</sup> Drupal - *www.Drupal.org* is the official website of Drupal, an open source content management platform.

2. conceptual knowledge assets (tacit knowledge, in the form of symbols and language); 3. routine knowledge assets (tacit knowledge, embedded in organisational routines and

4. systemic knowledge assets (systematized explicit knowledge).

organisational learning, structural capital, and human capital;

We now discuss these concepts in greater detail in the next five sections.

Tacit knowledge is personal knowledge, which is bound to the individual.

three such characteristics which influence the innovation dynamics. These are:

• the degree of relatedness between bodies of knowledge being linked together.

practices), and

• the degree of tacitness; • the level of complexity, and

BI;

Campbell (2009); Eftekharzadeh (2008)).

network of organisations,

in Botswana, and

organisations alike.

<sup>1</sup> *Ba* - platforms for knowledge creation.

**2. KM research**

The rest of the chapter is divided into five sections:

This is not embedded in some process nor easily transmitted and shared without some systematic effort. The characteristics of tacit knowledge are a subjective view or understanding of a topic, an artefact, an intuition or an internal feeling in the sense of a cultural prejudice, experience, tradition or belief. Tacit knowledge is based on informal metrics, non-standard experience, personal conceptions or convictions. The literature supports this view of tacit knowledge (Nonaka & Takeuchi (1995), von Krogh et al. (2000), and Campbell (2005)).

Fig. 1. Modes of knowledge common in the knowledge spiral ( Campbell (2005))

The classification of the foregoing is represented as the modes of knowledge, common in the knowledge spiral, as are illustrated in Fig.1. This figure seeks to explain how active knowledge sharing may be conceived in an organisational milieu. Active knowledge sharing, according to Campbell (2005), subsumes that most organisations will be focusing on one or more of the following four areas: (a) innovation, (b) responsiveness, (c) productivity, and (d) competency, as discussed in Campbell (2005). Consequently, this research takes cognisance of the processes of gathering, searching, filtering, conceptualizing, and transferring of knowledge, at the firm level (Campbell (2005), Hislop (2005), Day & Tate (2006), and Eftekharzadeh (2008)). As such, aligned to the four areas of active KM, are the following five processes, of KM:


in which Campbell (2005), discusses how technologies can be used in the context of KM projects. These five KM processes are discussed next.

Knowledge sharing must be understood as a natural part of the organisation's business, and

<sup>399</sup> The Liberation of Intellectual Capital Through

On the part of management, there should be executive commitment to the KM strategy. It cannot be expected that employees will share their knowledge, if structures and mechanisms for this cultural change is not provided, in the organisational basic conditions of operations. The approach will be one that begins with the basic conditions, which provides for the individual employee to have the requisite time for sharing his/her knowledge, and also where necessary, the introduction of non-financial incentive systems as motivation for knowledge

It is to be understood that knowledge sharing is not only achieved through direct communication. It may take place over a cup of coffee or in a formal session. The concern here, is when it does takes place, where employees enter the codified knowledge in an information system. A substantial aspect for the motivation of employees to use the system depends on the efficiency and the user friendliness of this system. The systems where all participants interact in real-time are called synchronous groupware systems, and performance considerations (such as fast response time) are especially important here. On the other hand, e-mail and messaging systems are examples of asynchronous groupware (van der Aalst & Kumar (2001)). The metrics governing asynchronous groupware systems will be discussed

... *Groupware is a generic term for computer-based systems which are particularly used to support groups of people engaged in common tasks in organisations. Typically, these groups are small; businesses oriented, and have relevant tasks with definite deadlines [cf. Fig. 1]. There are several taxonomies for groupware. The two most commonly accepted are the application-level taxonomy, based on the main functions the system provides to its users; and the time-space taxonomy, based on the users' temporal and physical distribution while interacting through the*

strategic landscape, in the development of a KM strategy. This is the theme of Fig. 2.

sharing.

next.

*system.*

Campbell (2005), defines groupware as follows:

the Natural Evolution of Knowledge Management Systems

Fig. 3. KM - BI Model ( Campbell (2005))

#### **2.1 Business intelligence**

In his study, Campbell (2005) argues that KM effectiveness depends on how one organizes the generation of new knowledge, and the transfer of existing knowledge within the organisation. The views expressed in that study, are supported by recent studies, as they relate to the growing interest in knowledge sharing practices (Davenport & Prusak (2000), Hislop (2005), and Richard C. Hicks (2007)). It is now commonplace, to find that both scholars and practitioners alike (Sveiby & Simons (2002)), are robustly discussing the benefits of knowledge transfer and knowledge sharing. Allied also with this is a debate on how organisations can effectively demonstrate their internal knowledge value that is their intellectual capital (Richard C. Hicks (2007)), and of particular relevance is the work of Majchrzak et al. (2004), as it resonates with the idea of knowledge reuse, sharing and conceptualization of meta-knowledge into business intelligence.

Fig. 2. A framework for knowledge enablement (Nonaka & Nishiguchi (2001))

In perusing both the literature, and in the study, the researcher found that, one of the most important objectives of KM is to have organisations consolidate their intellectual resources and make them available across organisational boundaries (Martin (2004), and Campbell (2005)). The fact that many of these organisations fail to harness the latent resources of their IC into BI, begs the case for an integrated knowledge network.

#### **2.2 Asynchronous groupware**

Apart from the development of new knowledge in the enterprise and the acquisition of knowledge from external sources, the knowledge that employees already have should not be ignored. In practice, it is found that most employees find it rather difficult to share their knowledge with each other. The problem is due in part to the nature of the organisational culture, or sometimes, to the modes of operation, in terms of how they synchronize with, or co-ordinate with their KM efforts. If employees espouse the "*knowledge is power"* mentality, then, there will be a conflict between their personal interests, and the interests of the enterprise in knowledge sharing. An organisational structure, which is favourable for sharing knowledge, must develop a perspective, which does not let this conflict grow out of control. 4 Will-be-set-by-IN-TECH

In his study, Campbell (2005) argues that KM effectiveness depends on how one organizes the generation of new knowledge, and the transfer of existing knowledge within the organisation. The views expressed in that study, are supported by recent studies, as they relate to the growing interest in knowledge sharing practices (Davenport & Prusak (2000), Hislop (2005), and Richard C. Hicks (2007)). It is now commonplace, to find that both scholars and practitioners alike (Sveiby & Simons (2002)), are robustly discussing the benefits of knowledge transfer and knowledge sharing. Allied also with this is a debate on how organisations can effectively demonstrate their internal knowledge value that is their intellectual capital (Richard C. Hicks (2007)), and of particular relevance is the work of Majchrzak et al. (2004), as it resonates with the idea of knowledge reuse, sharing and conceptualization of

Fig. 2. A framework for knowledge enablement (Nonaka & Nishiguchi (2001))

IC into BI, begs the case for an integrated knowledge network.

**2.2 Asynchronous groupware**

In perusing both the literature, and in the study, the researcher found that, one of the most important objectives of KM is to have organisations consolidate their intellectual resources and make them available across organisational boundaries (Martin (2004), and Campbell (2005)). The fact that many of these organisations fail to harness the latent resources of their

Apart from the development of new knowledge in the enterprise and the acquisition of knowledge from external sources, the knowledge that employees already have should not be ignored. In practice, it is found that most employees find it rather difficult to share their knowledge with each other. The problem is due in part to the nature of the organisational culture, or sometimes, to the modes of operation, in terms of how they synchronize with, or co-ordinate with their KM efforts. If employees espouse the "*knowledge is power"* mentality, then, there will be a conflict between their personal interests, and the interests of the enterprise in knowledge sharing. An organisational structure, which is favourable for sharing knowledge, must develop a perspective, which does not let this conflict grow out of control.

**2.1 Business intelligence**

meta-knowledge into business intelligence.

Knowledge sharing must be understood as a natural part of the organisation's business, and strategic landscape, in the development of a KM strategy. This is the theme of Fig. 2.

On the part of management, there should be executive commitment to the KM strategy. It cannot be expected that employees will share their knowledge, if structures and mechanisms for this cultural change is not provided, in the organisational basic conditions of operations. The approach will be one that begins with the basic conditions, which provides for the individual employee to have the requisite time for sharing his/her knowledge, and also where necessary, the introduction of non-financial incentive systems as motivation for knowledge sharing.

It is to be understood that knowledge sharing is not only achieved through direct communication. It may take place over a cup of coffee or in a formal session. The concern here, is when it does takes place, where employees enter the codified knowledge in an information system. A substantial aspect for the motivation of employees to use the system depends on the efficiency and the user friendliness of this system. The systems where all participants interact in real-time are called synchronous groupware systems, and performance considerations (such as fast response time) are especially important here. On the other hand, e-mail and messaging systems are examples of asynchronous groupware (van der Aalst & Kumar (2001)). The metrics governing asynchronous groupware systems will be discussed next.

Campbell (2005), defines groupware as follows:

... *Groupware is a generic term for computer-based systems which are particularly used to support groups of people engaged in common tasks in organisations. Typically, these groups are small; businesses oriented, and have relevant tasks with definite deadlines [cf. Fig. 1]. There are several taxonomies for groupware. The two most commonly accepted are the application-level taxonomy, based on the main functions the system provides to its users; and the time-space taxonomy, based on the users' temporal and physical distribution while interacting through the system.*

Fig. 3. KM - BI Model ( Campbell (2005))

**2.3 Organisational learning**

the Natural Evolution of Knowledge Management Systems

perimeter of KM.

illustrated in Fig. 3.

**2.4 Structural capital**

and/or knowledge;

two components here (Campbell (2005)):

Knowledge transfer is not a one directional movement of knowledge. Effective knowledge transfer is more than the movement of knowledge from one location to another. It is proposed that organisations can gain significant learning benefits through transferring knowledge between units and people. Competence tends to improve with those who transfer and share knowledge, because knowledge does not leave the owner when it has been transferred. As a result, the value of knowledge grows each time a transfer takes place. And, the key to knowledge transfer strategies should be based on the internal and the external structure of the organisation. As such, there are three main approaches to knowledge transfer, in terms of technology and organisational culture. The first approach, emphasizes the importance of the technological means and tools for effective knowledge transfer. The second, focuses more on the social interactions and underlying importance of cultural aspects. The third approach, is a comprehensive one, that aims to combine the technological perimeter with the socio-cultural

<sup>401</sup> The Liberation of Intellectual Capital Through

The challenge here is that managers either need to ensure the creation of unique knowledge that can be unleash in value-creating activity, or establish better use of public knowledge that is generally available to the organisation and its competitors (von Krogh et al. (2000)). The chapter reports this as organisational learning, in the KM-BI model (Campbell (2009) as

Knowledge is meaningful when it is codified, classified, given a shape, put in a useful format and stored. Only then can it be used by the right person, at the right time, in the right way. Storage and codification of knowledge is not only important for the effective use of knowledge, but also for re-using knowledge when it is needed; so the knowledge in question belongs to the organisation rather than the knower (Campbell (2005)). In this chapter, KM is viewed as a process. It is the process through which organisations create and use their

1. *Organisational learning* - the process through which the organisation acquires information

2. *Knowledge production* - the process that transforms and integrates raw information into knowledge which in turn creates BI, and is useful to solve business problems, and 3. *Knowledge distribution* - the process that allows members of the organisation to access and

The question one may ask is, how does this inform the concept of a knowledge system? In the context of the present chapter, a *'knowledge system'*, means the web of processes, behaviour and tools which enables the organisation to develop and apply knowledge to its business processes. It includes the infrastructure for implementing the KM process. There are usually

Firstly, there is a robust IT infrastructure, including the organisation's database, computer networks, and software applicationns. This chapter is not advocating the need for just a good or popular relational database, or a sophisticated groupware, or email system - the Asynchronous Groupware component of the knowledge system [cf. Figure 3], it subsumes that there must be an organisational infrastructure, which supports innovation. This prescript

institutional or collective knowledge. It has three sub-processes:

use the collective knowledge - corporate memory of the organisation.

resonates with the views of du Plessis (2007), who defines innovation,

Knowledge is information in action. It includes what people know about any process or approach. The conceptual KM-BI model of Fig. 3 suggests that with good information, people can make better decisions and take intelligent action, which leads to business intelligence at the organisational level. This model relates well with the framework for knowledge enablement in Fig. 2. KM is seen as a systematic process - as conceptualised from the KM-BI model, in this chapter, to:

	- (a) *Socialization* comprises the exchange of tacit knowledge between individuals in order to convey personal knowledge and experience.;
	- (b) *Externalization* involves the conversion of implicit into explicit knowledge, and the exchange of knowledge between individuals and a group;
	- (c) *Systematization* transforms explicit knowledge into more complex and more systematized explicit knowledge, and
	- (d) *Internalization* is the conversion of organisation-wide, explicit knowledge into the implicit knowledge of the individual. These four knowledge work processes combine to form a spiral representing all the knowledge creation and transfer activities within the network.

#### **2.3 Organisational learning**

6 Will-be-set-by-IN-TECH

1. *Identify important knowledge:* The KM-BI model acts as a framework for facilitating knowledge creation and transfer. The model assumes that the organisation's internal structural and cultural dimensions in which knowledge work processes

2. *Create a space and system for people to share what they know and create new knowledge:* The environment in which knowledge work processes are realized "*comprise social interaction and communication processes on an individual or group level. These processes may be categorized according to the transformation that knowledge undergoes as a result of*

(a) *Socialization* - comprises the exchange of tacit knowledge between individuals

(b) *Externalization* - involves the conversion of implicit into explicit knowledge, and

(c) *Systematization* - transforms explicit knowledge into more complex and more

(d) *Internalization* - is the conversion of organisation-wide, explicit knowledge into the implicit knowledge of the individual. These four knowledge work processes combine to form a spiral representing all the knowledge creation and transfer

3. *Capture, collect and manage best practices and useful information in a form that other people can use in the future:* This component of the model is the business intelligence which results from the resulting organisational learning, and the empowerment thereof. The KM-BI model (Campbell (2005)), and the knowledge network architecture (Seufert et al. (1999)) consist of tools that are used to facilitate social relationships, and include organisational, as well as information and communication protocols aimed at enabling or improving knowledge work processes. Gous & Schutte (2009) suggest that a tool classification framework may be employed to divide the combination of organisational information system tools into four main categories: communication and coordination tools, organisation and management tools, intelligent tools and integration and database tools. This is with a view to ensure maximum impact on the knowledge network, these tools are used in combination to form "*solution frameworks*" (Seufert et al. (1999)) instead of operating as modular

4. *Transfer information, knowledge and best practices to others who can use it (von Krogh et al. (2000))*.: Fig.1. sets out the modes of knowledge common in the knowledge spiral (Campbell (2009)), which, with the use of an Asynchronous Groupware (AG) infrastructure will facilitate this systematic process. The work of (Gous & Schutte (2009)), concurs with the previous views of Campbell (2005), that *"the creation of a knowledge portal to provide access to the knowledge network may be realized with modern web-based technologies. This provides a single point of access to the knowledge objects and all underlying systems. Such a knowledge portal should be configurable and adaptable to the needs of knowledge networks as well as the needs of their members*" (Campbell (2009)).

conceptualised from the KM-BI model, in this chapter, to:

*the activity*" (Schutte & Preez (2008)). These being :

systematized explicit knowledge, and

activities within the network.

tools.

in order to convey personal knowledge and experience.;

the exchange of knowledge between individuals and a group;

must take place are already enabled.

Knowledge is information in action. It includes what people know about any process or approach. The conceptual KM-BI model of Fig. 3 suggests that with good information, people can make better decisions and take intelligent action, which leads to business intelligence at the organisational level. This model relates well with the framework for knowledge enablement in Fig. 2. KM is seen as a systematic process - as

Knowledge transfer is not a one directional movement of knowledge. Effective knowledge transfer is more than the movement of knowledge from one location to another. It is proposed that organisations can gain significant learning benefits through transferring knowledge between units and people. Competence tends to improve with those who transfer and share knowledge, because knowledge does not leave the owner when it has been transferred. As a result, the value of knowledge grows each time a transfer takes place. And, the key to knowledge transfer strategies should be based on the internal and the external structure of the organisation. As such, there are three main approaches to knowledge transfer, in terms of technology and organisational culture. The first approach, emphasizes the importance of the technological means and tools for effective knowledge transfer. The second, focuses more on the social interactions and underlying importance of cultural aspects. The third approach, is a comprehensive one, that aims to combine the technological perimeter with the socio-cultural perimeter of KM.

The challenge here is that managers either need to ensure the creation of unique knowledge that can be unleash in value-creating activity, or establish better use of public knowledge that is generally available to the organisation and its competitors (von Krogh et al. (2000)). The chapter reports this as organisational learning, in the KM-BI model (Campbell (2009) as illustrated in Fig. 3.

#### **2.4 Structural capital**

Knowledge is meaningful when it is codified, classified, given a shape, put in a useful format and stored. Only then can it be used by the right person, at the right time, in the right way. Storage and codification of knowledge is not only important for the effective use of knowledge, but also for re-using knowledge when it is needed; so the knowledge in question belongs to the organisation rather than the knower (Campbell (2005)). In this chapter, KM is viewed as a process. It is the process through which organisations create and use their institutional or collective knowledge. It has three sub-processes:


The question one may ask is, how does this inform the concept of a knowledge system? In the context of the present chapter, a *'knowledge system'*, means the web of processes, behaviour and tools which enables the organisation to develop and apply knowledge to its business processes. It includes the infrastructure for implementing the KM process. There are usually two components here (Campbell (2005)):

Firstly, there is a robust IT infrastructure, including the organisation's database, computer networks, and software applicationns. This chapter is not advocating the need for just a good or popular relational database, or a sophisticated groupware, or email system - the Asynchronous Groupware component of the knowledge system [cf. Figure 3], it subsumes that there must be an organisational infrastructure, which supports innovation. This prescript resonates with the views of du Plessis (2007), who defines innovation,

it more available and accessible. Knowledge integration implies that timely insights can be made available to be drawn at the appropriate juncture for sense making, i.e. knowledge can be exchanged, shared, evolved, refined and made available at the point of need. Knowledge integration via knowledge management platforms, tools and processes must therefore facilitate reflection and dialogue to allow personal and organisational learning and innovation. This requires linkability, adaptability and dynamic representation of business information and knowledge. Without effective information and knowledge management that drives knowledge integration, which in turn underpins innovation, organisations could be underutilizing knowledge as an innovation resource [Baddi & Sharif (2003); Chen et al. (2004)]. The above three drivers resonate with the prescript for organisational learning, knowledge production, and knowledge distribution, which define the concept of a knowledge system, and a basic requirement for the enablement of structural capital. Given the foregoing, we can

<sup>403</sup> The Liberation of Intellectual Capital Through

The focus of this component, human knowledge, of the knowledge system is on knowledge creation and knowledge dissemination. This is not to suggest, in any way, that knowledge utilisation is not just as important. Rather, the elements comprising knowledge utilisation are subsumed here. The component of human knowledge involves the process of knowledge acquisition, which looks at the integration of external knowledge in the enterprise. This integration is by means of recruiting knowledge workers, specialists with particular value adding expertise, who usually bring relevant experience to the enterprise to assist it to meet its strategic objectives. The period over which this method of knowledge acquisition is used

can be for different life cycles, ranging from permanent to project specific duration.

Fig. 4. A framework for knowledge networks (Gous & Schutte (2009))

Allied to this, though, is the active process of knowledge development, which involves not only the functions of knowledge production in the formal sense of the concept of the development of a process, or a product, or service for consumption in terms of the commercial

now explore the component of human capital.

the Natural Evolution of Knowledge Management Systems

**2.5 Human knowledge**

... *as the creation of new knowledge and ideas to facilitate new business outcomes, aimed at improving internal business processes and structures and to create market driven products and services. Innovation encompasses both radical and incremental innovation.*

This includes the soft characteristics of the system. There are incentives schemes, organisational culture, critical people and teams which are involved in the KM sub-processes. This also accounts for, most importantly, the internal rules that govern these sub-processes. This is the structural (knowledge) capital component of the knowledge system [cf. Figure 4]. In the structural capital framework, one should think of data as information devoid of context. Information is data in context, while knowledge is information with causal links. So within the logic of the knowledge system, the more structure that is added to a pool of information, the easier it will be for one to achieve the benefits of a knowledge system [cf. KM-BI model]. In this regard, the definition of a meaningful KM initiative should be aligned to the enterprise strategy. This would, therefore, mean the development of formal KM strategies, from which realistic and concrete goals can be derived. These strategies should be closely aligned with the three drivers of the application of knowledge in innovation advocated by Marina du Plessis (du Plessis (2007)):

*The first basic driver for knowledge management's role in innovation in today's business environment is to create, build and maintain competitive advantage through utilization of knowledge and through collaboration practices. Cavusgil et al. (2003) indicate that building and sustaining an innovation program has, however, become increasingly complex due to changing customer needs, extensive competitive pressure and rapid technological change. organisations find it increasingly difficult to internalize innovations. Some large organisations such as Xerox and Hitachi have therefore started working collaboratively across organisational boundaries to ensure sustained innovation and competitive advantage (Cavusgil et al. (2003)). Knowledge management can facilitate such collaboration. Close collaborative relationships can provide access to the processes other organisations use that could be applied in different contexts. Acquiring knowledge and skills through collaboration is considered to be an effective and efficient way of successful innovation.*

The second driver of the role of knowledge management in innovation is that knowledge is a resource used to reduce complexity in the innovation process, and managing knowledge as resource will consequently be of significant importance. Innovation is extremely dependent on the availability of knowledge and therefore the complexity created by the explosion of richness and reach of knowledge has to be recognized and managed [Adams & Lamont (2003); Cardinal et al. (2003); Darroch & McNaughton (2002); Pyka (2002); **?**]. According to **?** the upsurge in the amount of knowledge that is readily available to organisations seems to add increased complexity to the design and management of new product development, but this complexity can be addressed by knowledge management and knowledge-intensive units in the organisation that are strategic in nature. Cavusgil et al. (2003) agree that knowledge management is a mechanism through which innovation complexity can be addressed. It assists in managing new knowledge created through the innovation process, but also in managing existing knowledge as a resource used as input to the innovation process. Cavusgil et al. (2003) are of the opinion that firms that create and use knowledge rapidly and effectively are able to innovate faster and more successfully than those that do not. According to Pyka (2002), creation of innovation networks are driven by synergistic creation and management of knowledge.

The third driver of applying knowledge management to the benefit of the innovation process is the integration of knowledge both internal and external to the organisation, thus making it more available and accessible. Knowledge integration implies that timely insights can be made available to be drawn at the appropriate juncture for sense making, i.e. knowledge can be exchanged, shared, evolved, refined and made available at the point of need. Knowledge integration via knowledge management platforms, tools and processes must therefore facilitate reflection and dialogue to allow personal and organisational learning and innovation. This requires linkability, adaptability and dynamic representation of business information and knowledge. Without effective information and knowledge management that drives knowledge integration, which in turn underpins innovation, organisations could be underutilizing knowledge as an innovation resource [Baddi & Sharif (2003); Chen et al. (2004)]. The above three drivers resonate with the prescript for organisational learning, knowledge production, and knowledge distribution, which define the concept of a knowledge system, and a basic requirement for the enablement of structural capital. Given the foregoing, we can now explore the component of human capital.

#### **2.5 Human knowledge**

8 Will-be-set-by-IN-TECH

This includes the soft characteristics of the system. There are incentives schemes, organisational culture, critical people and teams which are involved in the KM sub-processes. This also accounts for, most importantly, the internal rules that govern these sub-processes. This is the structural (knowledge) capital component of the knowledge system [cf. Figure 4]. In the structural capital framework, one should think of data as information devoid of context. Information is data in context, while knowledge is information with causal links. So within the logic of the knowledge system, the more structure that is added to a pool of information, the easier it will be for one to achieve the benefits of a knowledge system [cf. KM-BI model]. In this regard, the definition of a meaningful KM initiative should be aligned to the enterprise strategy. This would, therefore, mean the development of formal KM strategies, from which realistic and concrete goals can be derived. These strategies should be closely aligned with the three drivers of the application of knowledge in innovation advocated by Marina du Plessis

*The first basic driver for knowledge management's role in innovation in today's business environment is to create, build and maintain competitive advantage through utilization of knowledge and through collaboration practices. Cavusgil et al. (2003) indicate that building and sustaining an innovation program has, however, become increasingly complex due to changing customer needs, extensive competitive pressure and rapid technological change. organisations find it increasingly difficult to internalize innovations. Some large organisations such as Xerox and Hitachi have therefore started working collaboratively across organisational boundaries to ensure sustained innovation and competitive advantage (Cavusgil et al. (2003)). Knowledge management can facilitate such collaboration. Close collaborative relationships can provide access to the processes other organisations use that could be applied in different contexts. Acquiring knowledge and skills through collaboration is considered to be an effective and*

The second driver of the role of knowledge management in innovation is that knowledge is a resource used to reduce complexity in the innovation process, and managing knowledge as resource will consequently be of significant importance. Innovation is extremely dependent on the availability of knowledge and therefore the complexity created by the explosion of richness and reach of knowledge has to be recognized and managed [Adams & Lamont (2003); Cardinal et al. (2003); Darroch & McNaughton (2002); Pyka (2002); **?**]. According to **?** the upsurge in the amount of knowledge that is readily available to organisations seems to add increased complexity to the design and management of new product development, but this complexity can be addressed by knowledge management and knowledge-intensive units in the organisation that are strategic in nature. Cavusgil et al. (2003) agree that knowledge management is a mechanism through which innovation complexity can be addressed. It assists in managing new knowledge created through the innovation process, but also in managing existing knowledge as a resource used as input to the innovation process. Cavusgil et al. (2003) are of the opinion that firms that create and use knowledge rapidly and effectively are able to innovate faster and more successfully than those that do not. According to Pyka (2002), creation of innovation networks are driven by synergistic creation and management of

The third driver of applying knowledge management to the benefit of the innovation process is the integration of knowledge both internal and external to the organisation, thus making

*services. Innovation encompasses both radical and incremental innovation.*

(du Plessis (2007)):

knowledge.

*efficient way of successful innovation.*

... *as the creation of new knowledge and ideas to facilitate new business outcomes, aimed at improving internal business processes and structures and to create market driven products and*

> The focus of this component, human knowledge, of the knowledge system is on knowledge creation and knowledge dissemination. This is not to suggest, in any way, that knowledge utilisation is not just as important. Rather, the elements comprising knowledge utilisation are subsumed here. The component of human knowledge involves the process of knowledge acquisition, which looks at the integration of external knowledge in the enterprise. This integration is by means of recruiting knowledge workers, specialists with particular value adding expertise, who usually bring relevant experience to the enterprise to assist it to meet its strategic objectives. The period over which this method of knowledge acquisition is used can be for different life cycles, ranging from permanent to project specific duration.

Fig. 4. A framework for knowledge networks (Gous & Schutte (2009))

Allied to this, though, is the active process of knowledge development, which involves not only the functions of knowledge production in the formal sense of the concept of the development of a process, or a product, or service for consumption in terms of the commercial

1. Knowledge management assists in creating tools, platforms and processes for tacit knowledge creation, sharing and leverage in the organisation, which plays an important role in the innovation process. Knowledge management provides a focus in the organisation on the value of tacit knowledge and assists in creating the environment for tacit knowledge creation, sharing and leverage to take place. An example would be through creation of communities of practice around areas of innovation that requires attention in the organisation. Knowledge could also provide other platforms and processes for tacit knowledge sharing, such as breakfast briefings. Knowledge management can also facilitate tacit knowledge transfer across organisational and inter-organisational boundaries through ensuring that experts with relevant expert knowledge have opportunities to share their tacit knowledge through collaboration. Knowledge management can also assist in identifying stocks of available tacit knowledge. 2. Knowledge management assists in converting tacit knowledge to explicit knowledge. It can provide both the platforms as well as the processes to ensure that tacit knowledge becomes explicit. Examples of codification platforms include discussion databases or online collaborative communities of practice. An example of a process to codify tacit knowledge to explicit knowledge is the capturing of tacit knowledge at tacit knowledge sharing events such as breakfast briefings into an electronic form where the knowledge can be organized and retrieved for later use. This adds a lot of value to the organisation as

<sup>405</sup> The Liberation of Intellectual Capital Through

the Natural Evolution of Knowledge Management Systems

it is known what knowledge is available, and it is retrievable for future re-use.

organisation.

innovation.

3. Knowledge management facilitates collaboration in the innovation process. Knowledge management allows collaboration across functional boundaries within organisations, but also across organisational boundaries through online collaboration forums as well as organisational tools and platforms such as intranets and extranets. These collaboration forums are extremely valuable as they ensure the codification of knowledge utilized as input to the innovation process, but also generated as output of the innovation process. It provides accessibility to the knowledge and provides identification of collaborators in the knowledge sharing and innovation process, thus building up a reference of expertise and where it resides in the organisation. It also ensures that knowledge external to the organisation relevant to the organisation's innovation processes is available and accessible. 4. Knowledge management ensures the availability and accessibility of both tacit and explicit knowledge used in the innovation process using knowledge organisation and retrieval skills and tools, such as taxonomies. It allows the organisation and retrieval knowledge in a structured way according to the unique structures and value chain of the organisation. It also provides search facilities and tools (e.g. Autonomy, Convera, and others) to enable staff to search for knowledge required in the innovation process. It provides a unique corporate structure to the corporate knowledge base. It can also make tacit knowledge more accessible through directories that identify individuals' areas of expertise in the

5. Knowledge management ensures the flow of knowledge used in the innovation process. Through the provision of collaboration forums and knowledge management processes, knowledge required for the innovation process can flow easily across functional boundaries as well as across organisational boundaries to facilitate internal and external collaboration. Creation of a knowledge sharing culture, which is an essential part of any knowledge management program, also stimulates knowledge flow, which is beneficial for

milieu, but it also includes the performance metrics of an organisation. This is not to say that, that the development of knowledge and knowledge creation initiatives, in the physical sense, in the organisation's R and D department is not important. One is arguing that the processes used in the investigation and communication of that knowledge is more important than in the context of product creation and production. The generation of new ideas, abilities and products (of course) must be considered in addition to the other innovative processes of the enterprise. A central role of knowledge development is the promotion of creativity and communication among employees through the integration of enabling knowledge sharing strategies and an appropriate collaboration framework.

The presence of an appropriate organisational culture is a prerequisite for successful knowledge development. The analogy is like the role played by technological devices and tools within the spectra from telephones and whiteboards, to videoconferences and groupware, but more specifically asynchronous groupware (AG). Nonaka & Takeuchi (1995) argue that knowledge development is based on the interaction of implicit and explicit knowledge as the basis for the generation of new knowledge. Also, from the literature, Nonaka & Nishiguchi (2001) specifies a model for organisational knowledge development, which he calls the spiral of knowledge. This model is replicated in Fig. 1.

#### **3. Research goal**

The research goal of this chapter is to provide some insights from the literature surveyed and suggest how the innovation processes and network dynamics in terms of the need for intra-organisational collaboration, and the possible types of strategies organisations must devise through external networks. So they would be able to access the requisite knowledge for competitive advantage and business intelligence. This is with a view to lead to a robust discussion on how innovation may be supported by an integrated knowledge network, and whether the current ICT architecture available to organisations can offer the necessary functionality.

The research problem is conceptualized on the premise that: *"innovation within a globalized economy requires that a wide range of role-players along a knowledge management network of collaboration by transferring and creating knowledge."* A mechanism that offers this functionality is required.

This chapter, therefore, hypothesized that "innovation may be supported by an integrated knowledge network, that is an ICT architecture that offers the following functionality, such as:


#### **3.1 Value proposition in the innovation-oriented process**

Such a system would be circumscribed by an articulated value proposition. The value proposition of the role of knowledge management in an innovation-oriented intellectual capital milieu plays an invaluable role in fostering business intelligence, and intellectual capital, organisational knowledge, and structural knowledge, towards enabling an organisation's competitive advantage. Marina du Plessis [du Plessis (2007)] defines this value proposition as follows:

10 Will-be-set-by-IN-TECH

milieu, but it also includes the performance metrics of an organisation. This is not to say that, that the development of knowledge and knowledge creation initiatives, in the physical sense, in the organisation's R and D department is not important. One is arguing that the processes used in the investigation and communication of that knowledge is more important than in the context of product creation and production. The generation of new ideas, abilities and products (of course) must be considered in addition to the other innovative processes of the enterprise. A central role of knowledge development is the promotion of creativity and communication among employees through the integration of enabling knowledge sharing

The presence of an appropriate organisational culture is a prerequisite for successful knowledge development. The analogy is like the role played by technological devices and tools within the spectra from telephones and whiteboards, to videoconferences and groupware, but more specifically asynchronous groupware (AG). Nonaka & Takeuchi (1995) argue that knowledge development is based on the interaction of implicit and explicit knowledge as the basis for the generation of new knowledge. Also, from the literature, Nonaka & Nishiguchi (2001) specifies a model for organisational knowledge development,

The research goal of this chapter is to provide some insights from the literature surveyed and suggest how the innovation processes and network dynamics in terms of the need for intra-organisational collaboration, and the possible types of strategies organisations must devise through external networks. So they would be able to access the requisite knowledge for competitive advantage and business intelligence. This is with a view to lead to a robust discussion on how innovation may be supported by an integrated knowledge network, and whether the current ICT architecture available to organisations can offer the necessary

The research problem is conceptualized on the premise that: *"innovation within a globalized economy requires that a wide range of role-players along a knowledge management network of collaboration by transferring and creating knowledge."* A mechanism that offers this functionality

This chapter, therefore, hypothesized that "innovation may be supported by an integrated knowledge network, that is an ICT architecture that offers the following functionality, such

• support for all the necessary knowledge work processes needed for knowledge creation

• support for the full innovation life cycle of projects that develop within the integrated

Such a system would be circumscribed by an articulated value proposition. The value proposition of the role of knowledge management in an innovation-oriented intellectual capital milieu plays an invaluable role in fostering business intelligence, and intellectual capital, organisational knowledge, and structural knowledge, towards enabling an organisation's competitive advantage. Marina du Plessis [du Plessis (2007)] defines this

and transfer within an Integrated Knowledge Network, and

knowledge network." Gous & Schutte (2009)

value proposition as follows:

**3.1 Value proposition in the innovation-oriented process**

strategies and an appropriate collaboration framework.

**3. Research goal**

functionality.

is required.

as:

which he calls the spiral of knowledge. This model is replicated in Fig. 1.


but it also provides a culture within which innovation, creativity and learning through

<sup>407</sup> The Liberation of Intellectual Capital Through

The goal of this chapter is therefore to suggest the design of an information system that facilitates an integrated knowledge network, or a knowledge management - business intelligence (KM-BI) portal [cf. Fig. 3.], while providing support for the full life cycle of innovation projects that develop within this network, following from the work of Gous &

During the implementation phase of the computerised personnel management system (CPMS) project at Directorate, we found that the available innovation management software did not provide much ICT solutions with regard to an integrated knowledge network. The literature also had only few successful projects which had integrated knowledge networks as a part of their web technologies. The few available web technologies, we found, offer remote connectivity, content management, media-rich environments, community building and social

All these technologies had relevance to the nature and scope of the requirements of the Information Systems project definition of Directorate in terms of its integrated knowledge management work processes and value chain. The literature supports the view that an organisation's integrated knowledge network is *". . . a cradle for Innovation in a modern environment, and the exact features many of these technologies boast"* [Gous & Schutte (2009)]. We found that the latest web technologies which were noteworthy, are mainly open-source content management system, among these are WordPress, Joomla, and Drupal [Buytaert (n.d.)], which support content management. We also found that the standard release of Drupal, known as "Drupal core", contains basic features common to most Content Management Systems (CMS). These include the ability to register and maintain individual user accounts, administration menus, RSS-feeds, customizable layout, flexible account privileges, logging, a blogging system, an Internet forum, and options to create an interactive community website [Gous & Schutte (2009)] We concur with Gous & Schutte (2009) that "*Drupal was also designed to allow new features and custom behaviour to be added by third parties. For this reason, Drupal is sometimes described as a "*Content Management Framework." *Although Drupal offers a sophisticated programming interface for developers, no programming skills are required*

At Directorate, the system was designed to support the integrated work carried out by the personnel administration, recruitment, and placement divisions. Internal users of the system were intended to be able to store up-to-date information about public officers in their ministries, and keep track of policy development provided by Directorate through the online Policy Database. In order to meet this requirement, some of the positive and negative

• New content types are easily created and may be extended with the Content

• The Organic Groups module provides unrivalled community building functions

• Flexible framework for the development of web-based applications

• Vibrant developer community on the Drupal site

mistakes are encouraged and valued.

the Natural Evolution of Knowledge Management Systems

*for basic web site installation and administration."*

considerations of Drupal are set out next

Construction Kit module

• Fully customizable user permissions

1. Positive aspects of Drupal:

Schutte (2009).

**4. Drupal**

networking.


but it also provides a culture within which innovation, creativity and learning through mistakes are encouraged and valued.

The goal of this chapter is therefore to suggest the design of an information system that facilitates an integrated knowledge network, or a knowledge management - business intelligence (KM-BI) portal [cf. Fig. 3.], while providing support for the full life cycle of innovation projects that develop within this network, following from the work of Gous & Schutte (2009).
