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KNOWLEDGE MAPPING AS A STRATEGY FOR BUILDING A KNOWLEDGE BASE

IN A SCARCE SKILLS AREA

PART I: KNOWLEDGE WORK, KNOWLEDGE PROCESSING AND REPRESENTATION IN

THE DOMAIN OF HUMAN AFFAIRS

Knox, C.

Centre for Skills Development and Technology Transfer (CSDTT)

Note: This group presentation will have two parts. Part I (Carol Knox) looks at the theory

behind knowledge mapping. Part II (Nirisha Naicker, Drago Ivanov and Zeenat Dawood)

focuses on the practical application of Knowledge Mapping as it is being implemented at the

Centre for Skills Development and Technology Transfer (CSDTT) as part of its Research Niche

Area strategy.

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PART I:

KNOWLEDGE WORK, KNOWLEDGE PROCESSING AND REPRESENTATION IN THE

DOMAIN OF HUMAN AFFAIRS

Knox, C.

ABSTRACT

In examining ‘knowledge work’, knowledge processing and representation in the domain of

human affairs, an attempt is made to ‘un-muddy’ the waters with respect to definitions of the

terms ‘knowledge work’ and ‘knowledge worker’. In implementing knowledge management in

organisations, four forms of knowledge use are elaborated, as well as Nonaka’s (1991a, 1994),

fourfold classification of the transmission of explicit and tacit knowledge. Four forms of

‘knowledge work’ are suggested. In processing and representing increasing volumes and

complexity of knowledge, knowledge maps are examined as well as reasons for their

effectiveness in an age of knowledge rather than information seeking.

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INTRODUCTION

D. Amidon, (1991) accurately encapsulates the global change from seeking data and

information to seeking knowledge: ‘[W]e no longer seek data or information, but knowledge

including knowledge in the domain of human affairs (wisdom)’. Definitions of ‘knowledge’ do not

exist in the singular. Frequently the terms knowledge and information are used interchangeably.

Nonaka et al. (1995) observe three ways in which knowledge is similar to and different from

information. Firstly, knowledge is about beliefs and commitment, unlike information. Secondly,

knowledge involves action towards some end, which is not the case with information. Thirdly,

like information, knowledge is about meaning, which is context specific and relational. Albert

Einstein is quoted as saying, ‘knowledge is experience, everything else is just information”.

Nonaka et al (1995), further suggest that knowledge is, ‘a dynamic human process of justifying

personal belief towards the truth’. Against the backdrop of the ‘Information Society’, the

‘Information Economy’ and the role of Information Technology (IT), we examine the escalating

need to manage knowledge in the ‘new information age’. In this way, we find ourselves situated

in an ‘Information Society’, where ‘information work’ and knowledge-intensive companies are

moving away from the factory and manufacturing strategies that predominated for so long. This

‘Information Economy’ is ‘based on service work, advanced technology and a shift away from

the production of tangible products using mechanical skills, to the exchange of ideas and

knowledge via new technologies of communication’ (Boisot, 1998). Just what changes will be

involved in this move towards an ‘Information Society’ is a matter of hotly contested debate,

involving political and moral rhetoric. Various writers such as Kling and Dunlop (1992) and

Zuboff (1988) suggest that, whether positive or negative or shades in between, the future will be

determined by new technological developments, particularly in the IT sector.

Individual ‘know-how’1 and tacit knowledge2 are intangible assets for organisations. These

require new forms of work organisation that are open and creative in their working relationships

1 Know-how is complex, non-standardised, individual and creative and closely linked to intellectual capital and tacit knowledge. ‘The capital of know-how is mobile and heterogeneous and of two types, professional and managerial’ (Sveiby, K.). 2 Badaracco (1991) in Madhavean, R., & Grover, R., (1988), conceives of tacit knowledge as existing within individuals or groups. He makes reference to this knowledge in individuals and social groups as embedded knowledge – with Madhavean, R. & Grover, R. conceiving of embedded knowledge as ‘the

potential knowledge resulting from the combination of the individual team members’ stored tacit knowledge’ (1998). Tacit knowledge is embedded and cannot be fully explicated ‘even by an expert and can be transferred from one person to another only through a long process of apprenticeship’ (Polanyi,

1967 in Madhavean, R. & Grover, R. (1988).

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and capable of sharing knowledge and expertise in ‘evolving communities of practice’ (Zuboff,

1988). Information about and for organisations, ‘organisational knowledge’, how the various

aspects are performing and how this performance relates to the organisation’s environment

have become the focus of study. Weber was perhaps the first to identify the form of

organisational knowledge that characterises the modern organisation. In discussing various

types of profit making, Weber (1978) referred to ‘capital accounting’, which is central to a ‘profit

making enterprise’. The extension of the organisation beyond being an enterprise for the

calculation of profit and loss to representation of a wide range of other activities (e.g. accounts,

maps, charts, graphs and knowledge/domain maps) has made knowledge processing

capabilities a sought-after ability, in contrast to concern for only figures of profit and loss on the

balance sheet.

Since Peter Drucker (1979) coined the phrase ‘knowledge workers’, the population of

‘knowledge workers’ has increased dramatically, and, concomitantly, so has the management of

organisational knowledge. This increase has gone hand-in-hand with the greater recognition

that organisational knowledge represents the firm’s ‘intellectual capital’ (Stewart, 1997). Drucker

suggests, in fact, that if an organisation does not recognise and manage organisational

knowledge, this will be the single most important reason for organisational failure.

In terms of ‘knowledge work’ and ‘knowledge worker’, it is clear from the literature that, despite

the popularity of these terms, they are poorly defined. It is therefore imperative to attempt to ‘un-

muddy’ the waters by reviewing the current definitions and attempting to create a new definition

by specifying how knowledge is actually used in organisations and by briefly mentioning the

model of knowledge work created by Kelloway and Barling (2000). Three definitions are evident.

Firstly, ‘knowledge work’ has been defined as a profession. Secondly, it has been described as

an individual characteristic. Finally, it has been defined as an individual activity.

The definition of ‘knowledge work’ as a profession is the most frequent, usually being

associated with professional occupations, information technology or high tech industries (Choi &

Varney, 1995; Dove, 1998). Janez et al (1997) refer to ‘knowledge workers’ as ‘high level

employees who apply theoretical and analytical knowledge, acquired through formal education’.

As recognised by Choi and Varney (1995) and Kelloway and Barling (2000), this is an élitist

view, which Kelloway and Barling believe to be ‘Tayloristic’ in origin, with the separation of

‘thinking’ and ‘doing’ in organisations. There are numerous problems with this view: the

expanding role of blue-collar workers, emphasis on participative management, participative

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decision-making initiatives etc have put paid to the notion that managers are the ones who think

and the workers are the ones who do. Analysis of workplace change has identified increased

worker participation as central to new organisational environments (Giles et al, 1999).

Furthermore, the popularisation of ‘learning organisations’ (Senge, 1990) as ‘… organisations

where people continually expand their capacity to create the results they truly desire, where new

and expansive patterns of thinking are nurtured, where collective aspiration is set free, and

where people are continually learning to see the whole together’ makes it clear that such a

definition is disadvantageous. Additionally, the definition of ‘knowledge workers’ according to

specific occupations focuses on ‘credentialism rather than contribution’ (Kelloway & Barling,

2000), with the focus on what individuals have done (their education, professional qualifications,

experience), rather than on what they are doing (their current contribution to the organisation).

Dove (1998) points out that it is the possession of ‘knowledge’ that characterises ‘knowledge

workers’, not credentials.

In defining ‘knowledge workers’ as having certain individual characteristics, Tampoe (1993) and

Brophy (1987) emphasise creativity and innovation. Harrigan and Dalmia (1991) suggest that

‘knowledge workers’ are those who create intangible value-added assets. However, most

organisations remain hierarchically structured, which limits the ability of the individual to make

this type of contribution. Also, ‘classes’ of workers may be created with greater value inherent in

those who are creative/innovative than in those who are not. The ability to display creativity may

be confounded by lack of opportunity to contribute, rather than lack of ability.

Finally, looking at the third definitional category, we briefly review those defining ‘knowledge

worker’ in terms of the balance between ‘thinking’ and ‘doing’ as an individual activity. Drucker

defines ‘knowledge work’ as those jobs in which individuals work more with their heads than

with their hands. This focuses on what is actually done; that is, creation of ideas (Conn, 1984),

work that requires high levels of cognitive activity (Helton, 1988) and work carried out by

individuals using information to make decisions (Fox, 1990). However, the possibility still exists

for this potential to be confounded with opportunity, as we saw above. This definition does,

however, allow for the possibility that the definition may define the category of ‘knowledge work’

out of existence. Most employees contribute, and thereby add value, to their organisation by

using intellectual abilities in their day-to-day work. Kelloway and Barling (2000) suggest that a

categorical definition of ‘knowledge work’ and ‘knowledge workers’ is misleading, especially

because reliance on such a definition and others as mentioned above have focused on specific

groups of workers, rather than on what workers actually do. They propose that ‘knowledge work

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is not a category, but rather a continuum along which work may vary. Thus, all employees may

well be knowledge workers, although the extent and nature of knowledge use may vary

substantially both within and across organisations’.

In their proposed definition of ‘knowledge work’ in organisations, Kelloway and Barling (2000)

suggest that ‘knowledge work’ is best understood not as an occupation, but as an aspect of

work. It is their contention that the most appropriate focus for managers and researchers is the

use of knowledge in the workplace, and propose that ‘knowledge work’ is ‘best understood as

discretionary behaviour in organisations’. Davenport et al (1996) describe four forms of

knowledge use:

1) where employees are primarily engaged in finding existing knowledge

2) where employees create new knowledge

3) where employees package existing knowledge

4) where existing knowledge may be applied to a production process or to a problem.

Nonaka (1991a) focuses on the creation of knowledge and, in particular, the interrelations

between explicit and tacit knowledge. Nonaka (1991a, 1994) has proposed a fourfold

classification (see Figure 1) as a result of the transmission of both types of knowledge.

Tacit Knowledge to Explicit Knowledge

Tacit Knowledge Socialisation Articulation

from

Explicit Knowledge Internalisation Combination

Figure 1. Nonaka’s modes of knowledge conversion

Socialisation would involve the transmission of tacit knowledge from one worker to another, as

is the case when a new employee learns through working with and observing a skilled worker

(on-the-job learning). Combination is the transmission of explicit knowledge between individuals

and is most evident in activities such as formal education. Articulation requires the conversion of

tacit knowledge to explicit knowledge – making the ‘unknown’ known. The use of metaphor and

analogy would constitute articulation (Nonaka & Takeuchi, 1995). Internalisation involves the

conversion of explicit knowledge to tacit knowledge. This is the process whereby formal

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knowledge is learned so well that it becomes ‘second nature’. Nonaka (1991a) advocates that

articulation and internalisation are the most important forms of knowledge creation within

organisations, since they increase the store of knowledge. Based on the above, Kelloway and

Barling suggest four forms of ‘knowledge work’ in organisations:

1) creation of new knowledge or innovation

2) application of existing knowledge to current problems

3) packaging or teaching and transmitting of knowledge

4) acquisition of existing knowledge through research and learning.

It is their position that all the above forms of knowledge may be apparent at all levels of the

organisation and that the ability to ‘manage knowledge’ will relate directly to the ability of the

organisation to bring about the above forms of discretionary behaviour in the workplace. In their

formulation of a model of knowledge use in organisations, Kelloway and Barling suggest three

central characteristics, which mediate the relationships between the use of knowledge and the

predictors of knowledge use: employee ability, employee motivation and opportunity. Employee

ability, motivation and opportunity, for Kelloway and Barling, create the central conditions for

knowledge use in organisations. However, the relationships between these three conditions

remain unspecified, although the implicit assumption is that all three should be present for

knowledge work to occur. Therefore, the validity of their suggestion remains open to empirical

testing. In suggesting that the use of knowledge in organisations is discretionary, they suggest

that employees are likely to engage in knowledge use when they have both the ability and

motivation to do so. Potential predictors of the foregoing are leadership, job design, social

interaction and culture (organisational expectations and reward structures). It is beyond the

scope of this article to examine these predictors in detail; however, they alert one to the view of

Drucker (1999), who regards the enhancement of the productivity of the ‘knowledge worker’ as

a central survival challenge for organisations. Given that, in actuality, few organisations are of

the ‘learning organisation’ (Senge) type, and most are still hierarchically arranged, it is apparent

that opportunity and motivation, for ‘knowledge workers’, is key to organisational survival. This

will entail greater collaboration for all workers, enabling the enhancement of personal mastery,

which goes beyond competence to what Senge (1990) sees as a special kind of proficiency,

which is the process of developing mastery. In turn, this will enhance the intellectual capital of

organisations to keep their products or services competitive. In managing for quality, Kwang et

al (1999) make a somewhat extravagant claim with regard to the importance of knowledge

management as a quality strategy, which is, however, included to elucidate the organisational

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potential of collaboration: ‘by managing it well (knowledge) a company would have invested in a

corporate culture which encourages customers, employees and suppliers alike to embody their

skills in a pool of knowledge which can be utilised to deliver the perfect quality product and

services which provides for a truly delighted customer experience’. Once again, the importance

of knowledge use, motivation and opportunity is highlighted.

In working towards the above and the implementation of knowledge management in

organisations, the ability to process and represent increasing quantities and complexity of

knowledge in ‘evolving communities of practice’ (Zuboff, 1988) is becoming a premium ‘know-

how’. In making knowledge actionable in a way that it can add value to an organisation,

knowledge mapping can be a powerful tool. Vail (1999) provides a definition of a knowledge

map thus: ‘… the process of associating items of information or knowledge, preferably visually,

in such a way that the mapping itself also creates additional knowledge. The mapping process

itself often creates intellectual capital value through the creation of new knowledge from

discovering previously unknown relationships or gaps in expected ones’. Knowledge maps are

outstanding tools for capturing and sharing explicit knowledge and can serve as pointers to the

individuals who hold implicit knowledge. Horn (2001) uses knowledge maps for what he calls

‘social messes’. These are the messes of drugs, gangs, ethnic conflict, globalisation and rapid

technological change. Horn has made use of these maps in varied ways and mentions several

types: strategy maps; options maps; scenario maps; stakeholder goals, values and pressures

maps; unknown territory maps and policy discussion and decision maps. These maps have the

potential to bridge organisational gaps, such as those existing between IT management and

business management, since each holds a specialised view not easily understood by the other.

A knowledge map is the visual representation of captured information and interactions, which

enables ‘the communication and learning of knowledge by observers with differing backgrounds

at multiple levels of detail’ (Vail, 1999). Discrete items of intellectual capital may be text, stories,

graphics, models or numbers. They may then point to holders of implicit knowledge who may be

experts in a particular area. Ideally, this map will not only hold summary level knowledge and

relationships, but will act as an interface to more detailed data. One of the key architectural

principles would ultimately be to minimise the amount of information directly contained in it. The

vast majority of information can then be made available through links to original sources such as

databases, documents, individuals etc.

Increasingly, it is critical for organisations in the ‘information society’ to

be swift in anticipating threats and opportunities

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react quickly

be more cost-effective

in order to make the most of intellectual capital. This capital must then be made accessible to all

levels of the organisation, to whoever may require it and in the most appropriate display medium

available.

The need is to capture relevant knowledge that is constantly evolving and to capture it in various

forms (text, pictures, stories, data, models). Knowledge mapping provides the facility for

sustaining organisational learning, since the map may serve as evolving organisational memory,

‘capturing and integrating the key knowledge of an organisation’ (Vail, 1999). Further, by

steering through the map, engaging with it and questioning the information represented in it,

employees discover new relationships, and thereby learn and create new knowledge. One high

value area for introducing knowledge management through knowledge maps is to bridge the

divide between business and IT. Another area is in identifying and capturing different sources of

organisational knowledge. In tracking change, organisations may develop a current ‘as-is’ map

and a ‘to-be’ map and then track the transition models as the organisation evolves over time. In

developing ‘communities of practice’, employee buy-in to the changes is facilitated by being able

to see graphically what, where and when changes will occur and how they will be effected. This

is crucial in times of rapid change, since it will assist in alleviating uncertainty. Knowledge maps

also facilitate more rapid job and role orientation for new or reassigned employees, or, in

Nonaka’s view, facilitate socialisation. In this way, employees may be transformed into

knowledge partners, which significantly improves corporate performance. On their website,

Applied Learning Labs point out the reasons for knowledge maps’ being so effective. Some of

these reasons are outlined below:

1) Employees are engaged in a process that is dynamic and energising.

2) A variety of senses are employed – seeing complex concepts simplified, reading

marketplace data for question and discussion, touching and writing cards and placing

them physically where they fit the metaphor, talking about assumptions and new

business realities, hearing what others have to say and shaping new understandings.

3) Employees are required to engage mentally in the process.

4) Each employee is enabled to answer the question ‘How does it apply to me and what

can I do differently?’

5) The metaphor of the map becomes the mental model of the employee, which can

then be used to process new information.

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6) These knowledge maps are easily understood by clients.

Encouraging employees to internalise an organisational culture which promotes the ability,

opportunity and motivation of ‘knowledge workers’, enables knowledge use by means of, inter

alia, knowledge maps, which are invaluable architectural tools for promoting knowledge

processing and representation, a way of making the unknown known (articulation) and

promoting employee participation. Articulation and internalisation increase the store of

knowledge of an organisation, and hence the intellectual capital. Enhanced productivity and

incentives both enable and promote “knowledge work” as discretionary behaviour. They also

facilitate forms of knowledge use such as finding existing knowledge, creating new knowledge,

packaging existing knowledge and applying knowledge to a process or problem. With the global

move from data and information seeking to knowledge seeking, organisations that have the

ability to ‘manage knowledge’ well, promote ‘knowledge work’ as a discretionary behaviour,

thereby functioning more efficiently in the ‘Information Society’. This will stave off what Drucker

(1999) ominously warns may be the failure of organisations that do not master the trick of

‘managing knowledge’ well.

REFERENCES

Amidon, D. M. (1991). Origins of the knowledge based firm. Rough Draft Internal Memo of

Entovation International (Delivering Knowledge Innovation Strategies for the Millennium).

http://www.entovation.com

Boisot, M. H. (1998). Knowledge Assets, Securing Competitive Advantage in the Information

Economy. Oxford: Oxford University Press, in Hughes, J. A. et al. (2002).

Brophy, J. T. (1987). Linking knowledge workers and information technology. Office, 106 (3), pp.

88-92.

Choi, T. Y. & Varney, G. H. (1995). Rethinking the knowledge workers: where have all the

workers gone? Organisational Development Journal, 13, pp. 41-50.

Conn, H. P. (1984). Improving use of discrepancy time raises productivity of knowledge workers

in offices. Industrial Engineering, 16 (7), p. 7077.

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Davenport, T. H.; Jarvenpaa, S. L. & Beers, M.C. (1996). Improving knowledge work processes.

Sloan Management Review, 37, pp. 53-65.

Dove, R. (1998). The knowledge worker. Automotive Manufacturing and Production, 110, 26-28.

Drucker, P. F. (1979). Managing the knowledge worker. Modern Office Procedures, 24, pp. 12-

16.

Fox, M. L. (1990). Arming knowledge workers with computer systems. Production and Inventory

Management Review and APICS News, 10, pp. 50-54.

Giles, A.; Lapointe, P.; Murray, G. & Belanger, J. (1999). Industrial relations in the new

workplace. Relations Industrielles, 54, pp. 15-25.

Harrigan, K. R. & Dalmia, G. (1991). Knowledge workers: The last bastion of competitive

advantage. Planning Review, 19 (49), p. 48.

Helton, B. R. (1988). The ‘best work’ method of knowledge worker assessment. Industrial

Management, 29, pp. 26-29.

Horn, R. E. (2001). Knowledge Mapping for Complex Social Messes. A presentation to

‘Foundations in the Knowledge Economy’, at the David and Lucile Packard Foundation.

Hughes, J. A.; Rouncefield, M. & Tolmie, P. (2002). Representing knowledge: instances of

management information. British Journal of Sociology, (52) 2, pp. 221-238.

Janz, B. D.; Colquitt, J. A. & Noe, R. A. (1997). Knowledge worker team effectiveness: the role

of autonomy, interdependence, team development and contextual support variables. Personnel

Psychology, 50, pp. 877-904.

Kelloway, E. K. and Barling, J. (2000). Knowledge work as organisational behaviour.

International Journal of Management Reviews, 2 (3), pp. 287-304.

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Kling, R. & Dunlop, C. (1992). ‘Key Controversies about Computerisation and White Collar Work

Life”, in Baeker, R.; Buxton, W.; & Grudin, J. (eds.). Computer-Human Interaction, San Mateo,

CA: Morgan Kaufman.

Knowledge Maps. Why Maps Work. http://appliedlearninglabs.com

Kwang, K. L.; Pervaiz, K. A. & Mohamed, S. (1999). Managing for quality through knowledge

management. Total Quality Management, 10 (4 & 5).

Madhavan, R. & Grover, R. (1998). From Embedded Knowledge to Embodied Knowledge: New

Product Development as Knowledge Management. Journal of Marketing, 62, pp. 1-12.

Nonaka, I. (1991a). Managing the firm as an information creation process. In Advances in

Information Processing in Organisations, Vol. 4. Greenwich, CT: JAI Press, pp. 239-275.

Nonaka, I. (1991b). The knowledge-creating company. Harvard Business Review, 69, pp. 96-

104.

Nonaka, I. & Takeuchi, H. (1995). The Knowledge-creating Company: How Japanese

Companies Create the Dynamics of Innovation. New York: Oxford University Press, pp. 57-58.

Senge, P., Kleiner, A., Roberts, C., Ross, R., Roth, G. and Smith, B. (1999) The Dance of

Change: The Challenges of Sustaining Momentum in Learning Organizations, New York:

Doubleday/Currency).

Stewart, T.A. (1997). A new way to think about employees. Fortune, April, pp. 169-170.

Sveiby, K. E. (1992). The Know-How Company: Strategy Formulation in Knowledge-Intensive

Industries. International Review of Strategic Management.

Tampoe, M. (1993). Motivating knowledge workers – the challenge for the 1990’s. Long Range

Planning, 26 (3), pp.49-55.

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Vail, E. F. (1999). Knowledge mapping: Getting started with knowledge management.

Information Systems Management, pp. 18-20.

Weber, M. (1978). Economy and Society. (Roth, G. & Wittich, C. Eds., Trans.). Berkeley:

University of California Press.

Zuboff, S. (1988). In the Age of the Smart Machine: The Future of Work and Power Basic

Books. New York.