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Succeeding With Knowledge Management: Getting The People-Factors Right


Knowledge Management (KM) and organizational learning are widely accepted as valuable means for organizations to enhance intellectual capital, encourage innovation and optimize performance. The authors maintain that successful implementation of either of these approaches is critically dependent on the collaborative nature of the organization’s social fabric. They further assert that this social fabric is significantly influenced for better or worse by critical non-rational people-factors that are ignored in a typical KM or organizational learning initiative.

The authors contend that organizations largely operate at all times under a cloak of rationality, ignoring non-rational realities such as emotion. The result is that energy that could be applied productively actually becomes a damaging force that undercuts performance. It is argued that an organization implementing KM and/or organizational learning must strike an adequate balance between rationality/technical efficiency and non-rational factors if the anticipated benefits are to be captured.

In this paper a performance-based approach to the design and implementation of a KM system is proposed that facilitates identification, clarification, and remediation of the key non-rational people-factors that impact its usage and efficacy. This approach is independent of the type of KM system envisaged.

The authors first lay a “New Science” foundation for the performance approach. Next they explain how a KM environment can be designed, implemented, and monitored using a simple performance system comprised of three performance drivers or “fields”. They go on to examine important shortcomings they believe are common to KM implementation, and explore remediation via factors that shape the state of these three “fields”. The role and impact of vision and mission statements, plus various physiological and non-rational factors are discussed.

The authors further maintain that leverage for remediation lies in upgrading “Personal KM” by first assisting managers to change the quality of local peer-peer and peer-subordinate interactions to enhance authenticity and create emotional openness. Action learning has been found to be an ideal vehicle to achieve these ends when exploited as part of an intensive workshop and coaching program enriched with skills drawn from disciplines such as counselling.


For more than a decade Knowledge Management (KM) has been proposed by many authorities as a viable means to optimize enterprise performance in the face of the rapidly increasing complexity and ambiguity of our modern world (Drucker, 1988; Itami & Roehl, 1991; Nonaka & Takeuchi, 1995; Davenport & Prusak, 1998; Von Krogh, 2000; Choo & Bontis, 2002). During this period the KM field has been significantly hyped; however, practitioners and researchers have begun to have access to reasoned critiques (Fuller, 2001; Seely Brown & Duguid, 2000; Pietersen, 2001) and balanced reviews (Despres & Chauvel, 2000a). Indeed there is now an admission that KM systems can fail to deliver on their promise (Fahey & Prusak, 1998; Newell & Scarbrough, 1999; Lindgren & Henfridsson, 2002; Storey & Barnett, 2000). It is our contention that the true reasons for sub-optimal KM performance are in very many cases related to the lack of supportive attitudes and emotions on the part of the organization’s employees. Since most organizations only countenance operation within a facade of rationality (Smith & Sharma, 2002a) such negative people-related factors remain unacknowledged or at best undiscussable. As a consequence solutions are not explored and organizations are forced to repeat history with predictably dim results.

Fortunately of late there has been an acknowledgement of the people-centric nature of KM implementation. Comments by authorities such as Wiig (2000; pp. 4) “ … there are emerging realisations that to achieve the level of effective behaviour required for competitive excellence, the whole person must be considered. We must integrate cognition, motivation, personal satisfaction, feelings of security, and many other factors”. Wiig (ibid; pp. 14) cites a number of authors to support his contention that “Overall KM will become more people-centric because it is the networking of competent and collaborating people that makes successful organizations” and “One key lesson to be learned is that we must adopt greater people-centric perspectives of knowledge …Technology only goes so far” (ibid; pp. 25). Snowden (2000; pp. 237-8) notes that:  “ (organizations) … are gradually becoming aware that knowledge cannot be treated as an organizational asset without the active and voluntary participation of the communities that are its true owners. A shift to thinking of employees as volunteers requires a radical rethink of reward structures, organizational forms, and management attitudes. Even where the KM focus is essentially technology based, the importance of people to the process has been acknowledged. For example, Davenport and Prusak remark “ … the roles of people in knowledge technologies are integral to their success” (Davenport & Prusak, 1998; pp. 129); unfortunately such sentiments are quickly viewed by organizations as impractical and serve only as window dressing.

In this paper we aim to heighten awareness of the impact of people-factors on KM implementation and to offer practical approaches that we contend will “get the people factors right”. First we review the tried-and-true approach to performance that one of us (Smith) has utilized successfully with a broad range of organizations for almost two decades, and we will show that this approach is based in a “New Science” perspective. Next we use this performance model to frame descriptions of initiatives that shape various people-factors for successful KM implementation.

We find the notion of a Personal Knowledge Management System (PKMS) useful for exploring and defining what it is that individuals, at differing organizational levels, should know in order to successfully implement KM. According to the performance model discussed later, each individual’s PKMS will contain cognitive, affective and resource related factors with respect to implementing KM. The approach described in this paper is aimed at populating an individual’s PKMS with knowledge about the successes and pitfalls of KM implementation, and is particularly directed to shaping the affective people-factors domain of the individual’s PKMS.

A Performance-Based Approach To KM: The “New Science” Platform

In this section we discuss the theoretical platform for our performance-based approach. The platform is based in complexity science (Gleick, 1987) and Chaos theory (Fitzgerald, 2002). Complexity and Chaos were first popularized as a “New Science” perspective on business organizations by Wheatley (1992), and later developed by other authors such as Mitroff and Linstone (1993), Kelly (1994), Sanders (1998), Gabriel et al (1999), and Lewin and Regine (2000).

Wheatley (1992) contends that the world is formed of complex dissipative structures in which disorder can be a source of order, and growth is found in dis-equilibrium. The richness of the diverse elements in a complex system allows the system as a whole to undergo spontaneous self-organization (Waldrop, 1992). Chaos by itself does not explain the structure, the coherence, and the self-organizing cohesiveness of such systems. Even the most chaotic of systems stay always within certain boundaries called “strange attractors” (Gleick, 1987) providing order without predictability. According to Wheatley, one of the best ways to create control under these conditions is through the use of forces called “fields”. Many scientists now work with the concept of fields – invisible forces that structure space or behaviour (Bateson, 1988; Mitroff & Linstone,  1993; Boisot, 1994).

It is argued that an organization must develop a visionary core at its “center” to provide such fields (McNeil, 1987; Parker, 1990; Smith & Saint-Onge, 1996). The organizational meaning thus articulated becomes Gleick’s (1987) “strange attractor”, and in this way individuals make meaning to produce order from chaos, giving form to work, and structure to what is happening at the level of the individual.

A Practical Three “Field” System For KM Implementation

In this section we describe the three “field” system, based on the theory discussed in the last section, that we use to actualize our performance-based approach to KM, and populate the PKMS. The three systemic fields are termed Focus, Will and Capability. The generic model is presented in Figure 1, and represents here an outcomes-driven KM performance system. Performance is driven by the business outcomes desired; for example, formally via The Balanced Score Card (Kaplan & Norton, 1996) or informally via simple objective-setting exercises.

The model has been introduced successfully since the mid-80’s by one of us (Smith) to enhance performance in organizations as diverse as Exxon (Smith, 1993), Canadian Imperial Bank of Commerce (Smith and Saint-Onge, 1996), and IKEA (Drew and Smith, 1995). The model has also been used as the means to facilitate development of a learning organization (Smith and Saint-Onge, 1996); leadership (Smith & Sharma, 2002b/c); learning applications (Smith, 1997); and dynamic strategic planning (Smith & Day, 2000).

The three fields form a dynamic system. The actual current performance level achieved by the system depends on the interactions and interdependencies of the three fields. Focus represents a clear definition and understanding of the performance proposed; Focus is associated with questions such as What ..?; How ..?; Who ..?; Where ..?; When ..?; Why ..? The field of Will represents strength of intent to action the performance defined in Focus; Will is associated with attitudes, emotions, beliefs and mindsets. Capability represents the wherewithal to transform into reality the performance defined in Focus; Capability is associated with such diverse areas as skills, SW/HW, infrastructure, budgets, tools, physical assets etc. A change in any one of these fields may effect a change in the state of one or both of the other fields.

Optimal performance is favoured when Focus, Will and Capability form a self-reinforcing system, with all fields in balance and harmony. As Figure 1 shows, current performance potential is represented by the degree of overlap of the circles; optimal performance being represented by complete congruence of all three circles.

Areas shown in Figure 1, where only two model fields overlap, are typical of real-life situations. These imbalances and lack of congruence typically lead to misdirected and wasted efforts as well as loss of performance. For example, organizations often concentrate on developing an I/S KM system (strong Capability) without regard for the fact that their employees don’t understand why KM is needed (weak Focus) or a cultural feeling that an individual’s knowhow is their source of power  (absent Will). The key to performance optimization is the continual dynamic tuning of the degree of overlap of the fields based on re-making and re-shaping meaning.

As Figure 2 illustrates, the performance model is consistent across all levels of the organization; however, the meaning of Focus, Will and Capability will change to reflect the changing context. This is a very important strength of the model.

As discussed in the previous section, once ideal Focus, Will, and Capability are defined, the system forms a “strange attractor” termed the “Shamrock Attractor”, by which individuals in the organization make meaning to produce order from chaos through these fields. That means that when Focus, Will and Capability are defined appropriately, KM will be promoted naturally.

The model is particularly important because it provides three “levers” that can be set by senior management in concert with employees to position the organization to attain overall high-performance, including KM. The current positioning of the “levers” can be checked and compared to the designed settings (Smith & Tosey, 1999; Tosey & Smith, 1999).

Based on the authors’ lengthy experience in “field” implementation, Capability is most likely to be overdeveloped; Focus underdeveloped; and Will essentially undeveloped. Yet to optimize, or even maintain good performance, it is critical that balance and harmony are maintained among all the fields, since too much emphasis on any one or two of the fields is probably worse than too little.

A wide range of initiatives can be launched to attempt to shape and harmonize the fields, A selection of learning-related initiatives that could be targeted to KM is presented in Drew and Smith (1995; pp. 10). Initiatives more specifically related to KM are also widely available; for example at the strategic performance level (Itami & Roehl, 1987), general performance (Dixon, 2000), and technical (Applehans et al, 1999).

Endemic Performance Barriers And Overcoming Them

Although the above initiatives are likely to be impactful in shaping and balancing the three fields, we feel that typically there remain serious endemic barriers to implementing KM, particularly with respect to development of open and trusting cultures. In this section we discuss these barriers. Given the highly systemic nature of their interactions, no attempt has been made to discuss individual fields in separate dedicated segments.

As was noted previously, in an effort to foster “ideal” performance, organizations typically explicitly over-develop Capability; under-develop Focus; and to all intents and purposes, do not develop Will at all. This does not mean that Focus or Will in the employee community are necessarily weak. On the contrary, Capability is exerted through “roles and tasks that exert overt and covert control over emotional displays” Putnam & Mumby, 1993; pp. 37), and hence there is an implicit effect on Will. These authors talk of “emotional labour” being expended in this effort (ibid; pp. 37); unfortunately this produces compliance rather than the commitment that is vital to effective KM.

The reasons that prevent organizations from achieving balanced well-targeted fields are complex and illogical, as one would expect where tacit feeling-laden concerns are involved. For example, organizations typically operate with a façade of rationality although Will involves irrational issues. Will is often perceived as negative, linked to the expressive arenas of life rather than to the instrumental goal-orientation that drives organizations. In 1973 Egan wrote “Emotional repression in undoubtedly still a far greater problem than emotional overindulgence” (1973; pp. 61). Thirty years later this statement is as true as ever; society still equates emotional maturity with the control or repression of feelings, continuing to use the word “emotional” in a derogatory sense. In contrast, the fields of Capability and Focus are easier to address, since they rely on production of tangible “evidence” such as vision and mission statements, action plans, and the like.

In our view, shaping Will to promote KM requires that a new mindset be developed, one that views organizations as less rational and embraces all their complexity (Wheatley, 1992; pp. 46). Because of the inter-related nature of the performance fields, creating such a culture means shaping Focus to pull people towards the organizational goals rather than pushing them. Traditionally organizations formulate the KM vision/mission/goals in isolation and cascade them downwards through the organization. This will not positively influence the Will segment. Rather people must be pulled toward a visionary core through their involvement. This is accomplished by aligning the organizational vision to people, rather than the people to the vision (Mahesh, 1993; pp. 230-231; Kouzes & Posner, 1995; pp.129-133).

The benefits of collaboratively shaping Focus lie in each person’s subsequent actions. When employees themselves clarify the KM Focus, they gain more than a sense of direction and a means to define their code of conduct. The process helps them develop the appropriate Will. This is because each will be motivated to act in accordance with the role-related responsibilities they have defined for themselves.

In shaping Will it is important to understand that in today’s business world those dubbed “leaders” no longer know all the answers. Leaders and followers need each other. This gives rise to an uneasy balance (Hirschhorn, 1990) since the leader must make plain her/his own vulnerability, and risk that her/his followers may cease to see the leader as worthy of following. Likewise the followers must alter their passive dependent role and risk threatening and/or alienating their leader. Goldstein (1992; pp. 16) contends that what are needed in today’s organizations are authority not authoritarian relationships. In an authority relationship the supervisor sets the context for the work and the supervised individual exercises judgement in how to carry it out. The supervised individual also has the right to negotiate a change in the context. If the supervisor abdicates this responsibility or sets fixed boundaries, the supervised individual becomes more rigid since (s)he feels made responsible for tasks and outcomes that (s)he cannot control. In reflecting on complexity and organizational management from a psychoanalytical point of view, Gabriel (1999; pp. 280-288) notes that it is to be expected that managerial rigidity and faith in authoritarian control will rise with feelings of insecurity and uncertainty such as those related to KM implementation, although such faith is largely misplaced.

Development Of Sound Focus, Will and Capability

In this section we outline initiatives that an organization can undertake to influence the three fields such that “ideal” behaviours (and therefore KM performance) will in principle be developed and maintained. These initiatives will have the benefit of addressing the endemic shortcomings we discussed in the last section with particular reference to people-factors.

Each field is treated individually; however we have attempted to indicate how activities initiated to shape one field will influence one or more other fields. The fields are treated in the order Focus, Capability and Will because actions can be initiated fairly readily for Focus and Capability that are the basis for any successful attempt to influence Will.


A.        Focus

Focus represents a clear definition and understanding of the performance proposed, and in our opinion, the most critical aspects of Focus are the organization’s “Vision and Mission”. Vision and mission make their strongest contribution to Focus when they result from a sharing of the individual yearnings of all employees. In spite of a wealth of information on how to involve the whole organization in development, articulation, and sustenance of vision/mission (Senge, 1990; Senge et al 1994; Senge et al, 1999; Parker, 1990) experience confirms that such an approach is still only infrequently adopted (Kouzes and Posner, 1995; pp. 124).

We will not regurgitate here the recommendations of the above authors. Rather we posit that an organization adopt an approach that will eventuate in both a shared KM vision/mission and the means to keep it evergreen. The simple approach of encouraging individual managers to explore, with their teams, development and articulation of a shared local KM vision/mission for their particular function, consistent with that of their organization, is in our experience sufficient for the purpose.

B.        Capability

An aspect of current organizational life that we believe has become undervalued is an appreciation of the physiological needs of individual employees. This is tragic in that research has shown that satisfying these needs directly correlates with the quality of an individual’s performance (Fortune, 1997). Furthermore, we believe the need for self-actualization pioneered by Goldstein and polished by Maslow (Mahesh, 1993; pp. 35) is critical to the development of cultural traits that successful KM implementation demands.

Organizations would do well to review Maslow’s notion (Maslow, 1943) that human beings have an innate requirement to satisfy a hierarchy of needs. The lowest level he termed the physiological. Once the physiological needs are fulfilled, humans look to satisfy their safety needs. When the two lowest needs are largely gratified, there emerges the need for belongingness. According to Maslow, only when the three lower needs are satisfied will an individual seek esteem. He divided this class of needs into two sub-classes. The first involves the need for self-evaluation; the second involves the views of others. Maslow is quoted by Mahesh (1993; pp. 49) as seeing a further less well formulated stage: “Even if all these (lower) needs are satisfied, we may still often (if not always) expect that a new discontent and restlessness will soon develop, unless the individual is doing what he, individually, is fitted for” and “What a man can be, he must be”. It is very important that Capability needs at lower levels of the hierarchy be satisfied before attempting to introduce Will-related activities aimed at self-actualization. An organization can readily establish the current satisfaction level of its employees with regard to their needs. For example, organizational health surveys are commonly carried out, albeit asking the wrong questions!

C.        Will

The initiatives discussed above for Focus and Capability are in themselves very powerful in shaping Will by pulling it into being rather than mandating a certain state. In this subsection we concentrate on activities that shape Will and are associated with intrinsic motivation.

One area where Will can be positively shaped is by addressing how the people in an organization meet. At most meetings attendees talk for hours without “meeting” each other at all. Often the last thing people want is to be forced to reveal their concerns. This lack of disclosure arises because of the nature and quality of the interactions between individuals and groups. On the surface of a meeting, all may appear well, and discussion proceeds in a calm and dignified manner. However, under the surface, a more turbulent encounter is taking place which will profoundly affect the discussion above the surface plus any subsequent actions.

Whenever people meet, although there are intermediate stages of partial awareness, in simple terms there are two extremes of activity, namely aware and unaware activity. One common way to picture this is to imagine people as icebergs floating together on a sea of life. As one can visualize, when icebergs meet, the submerged parts of the icebergs (unawareness), which is much greater than the visible tips of the icebergs (awareness), meet first. The “aware” part is termed the content of meeting; the “unaware” part is termed the process of meeting. Gaunt (1991) provides details of the group conscious and unconscious awareness at various levels of the iceberg, and points out that the content is often defeated by the unarticulated process, which is about building trust.

Revans (1982) differentiates between “puzzles” (where a solution already exists and where there is one right answer) and “problems” (where there is no single solution and no one way of doing things). KM is typically wrongly implemented as if it were a puzzle. For example, the iceberg tip might be articulated as “How do I develop a KM system for my organization?” However, the underlying problem that will need resolution might more realistically be defined as “How do I and the people in my team deal with feelings related to leadership-follower dynamics, power, competition, job security, vulnerability, envy, poor self esteem etc?” We contend that such KM icebergs cannot be fused into a cohesive whole by examining and responding only to their tips. This is because individuals and groups, and indeed the whole organization, struggle with semiconscious and unconscious impulses that operate at another level.

People meet at their “boundary” and every individual has their own boundary; “… a psychological marker that creates a space within which people can take up their roles with some degree of certainty knowing who they are and what they are accountable for” (Goldstein, 1992; pp. 21). In the absence of boundaries, individuals internalize the business chaos around them, feeling they are being made responsible for activities and outcomes beyond their control, and becoming more resistant to trust and openness so critical to successful KM. People make real contact with one another when they are aware of their own boundaries, and those of others. A meeting with the right tone is one where people demonstrate the qualities that Zinker attributes to the happy family (Zinker, 1998; pp. 114). Zinker also lists the ways that families block communication (Zinker, 1998; pp. 119-124).

A critical pre-requisite to embedding such positive behaviours is an appreciation of “awareness”. Awareness involves comprehending the environment through the use of senses. Its aim is to enrich the background, so that “what matters” stands out fresh, clear and engaging (Nevis, 1987). Thus an employee demonstrating an effective PKMS takes in and processes all the information related to her/his environment plus her/his relationship with it, while keeping hold of the key issue.

Awareness highlights what requires attention or action, but does not necessarily lead to action.  People/organisations can become stuck in their awareness. We typically think of this as “resistance” but this is a descriptive word that must be treated with care (Goldstein, 1992; pp. 20). For example, an individual may be trying to signify something about how they are being approached. As discussed earlier, resistance does not necessarily indicate an absence of Will, but rather the presence of inappropriate Will.

Concerns such as these have been explored through the discipline of group dynamics (most notably psychoanalysis, field and systems theories, and Gestalt). For example, the writings of Freud (1984), Klein (1959), Bion (1961) show that “our experiences of being and working in groups are often powerful and overwhelming.  We experience the tension between the wish to join together and the wish to be separate; between the need for togetherness and belonging and the need for an independent identity” (Stokes, 1994; pp. 19). If we add the levels of uncertainty and pressure associated with KM implementation, we begin to develop a sense of the potential anxieties – conscious and unconscious – that must be dealt with.  In fact we suggest that a KM system in itself is a defence against anxiety.

Egan (2002) has proposed a system of counselling skills whereby emotions such as those highlighted above can be explored, understood, and resolved or managed. We describe in the next section group interventions (PKMS Groups) that we use, building on Egan’s work and that of others such as Heron (1998, 2001). These interventions foster expression of blocks to effective working, and help develop insight into unconscious difficulties whilst promoting personal awareness of oneself as an individual. In our opinion, without such interventions no meaningful KM progress can be made, and in fact harm will be done. As Gaunt (1991; pp. 86) notes: “Un-discharged feelings have the power to block logical thinking.  Anger and sadness are normally difficult to express in a work environment but they are there, and without some access and ventilation an individual (or in some circumstances a whole organisation) becomes emotionally disabled.  Feelings are facts”.

PKMS Group Meetings

In this section we describe our approach to developing the characteristics of happy families that Zinker posits, plus appreciation of the importance of boundaries, awareness, and the capacity to address the aware and unaware aspects of “icebergs”.

Our interventions are directed to populating an individual’s PKMS with knowledge critical to the successful implementation of KM, and in particular targets people-factors. We term such programs PKMS Groups. PKMS Groups are based on an action learning process, utilizing counselling and group work skills that draw on psychodynamic, Gestalt, and client-centred theory.

A PKMS Group program typically begins via a 2-day workshop for middle managers (up to 18 at a time). In day 1 morning we begin by identifying what PKMS means for the participants, and could include exploration of barriers and anxieties related to participants’ personal understanding and experience of KM; in particular addressing “what’s in it for me?” There could also be familiarization with best practices.

The afternoon would provide an introduction to action learning (McLaughlin, 1998) as a PKMS model, with practice applied to participants’ real life KM problems, including identification of key skills e.g. active listening, confrontation, facilitation. These skills would be treated in detail on day 2. We use a style of action learning based on the counselling approach pioneered by Gaunt (1991) where participants negotiate for time to explore an issue. We favour this model over the more familiar “project model” advocated by many exponents of action learning (Revans, 1982) because it encourages individuals to define their own areas of interest/concerns, and work in-depth with these issues, thus building increased capacity for ownership and insight.

Action learning requires highly skilled facilitation to encourage discipline in setting aside one’s own agenda and working openly with the group process. The facilitator trains the group in action learning techniques, models the skills, and provides what Winnicott describes as a ‘holding environment’ for the client group (1965).  By acting as “ … a safe container who can accept and survive the anxieties and sometimes the hostile projections coming from the client system, [the facilitator] provides the containing space within which challenging and thinking can happen” (Linklater & Kellner, 2000; pp.15). Our aim in facilitating a PKMS group is to enable members to become self-facilitating, taking responsibility for their own development.

Whilst individuals often bring problems, participants may use their time to explore an opportunity, or reflect upon the learning from an achievement. The rest of the group act as collective ‘counsellor’ to the ‘presenter’ of the issue, enabling her/him to explore and clarify their situation and, where appropriate, identify options, solutions, or ‘next steps’. Under non-workshop formats, there is a follow-up meeting at which the presenter reports to the group on her/his progress, i.e. the subsequent ‘action’.

Day 2 would be built around intensive skills practice and development of an understanding of Egan’s “3-stage process of helping” problem solving process (Egan, 2002). This process is about exploring the presenting problem and moving to a detailed understanding of the underlying issues, followed by action planning. Here we enable people to develop the skills to look below the waterline of the iceberg, and explore the semi- and un-conscious motivations and defences operating when KM is being introduced. Role-plays could be included where participants would be encouraged to share and work with their own real-life PKMS issues.

Longer-term action learning groups would be formed at the end of the 2-day program, meeting typically every month for about 6 months (post the 2-day workshop) to embed skills, focus in-depth on current issues, and exchange best practices. These meetings would be typically half-day facilitated sessions and could be technology-supported ‘at arms length’. A review session would be included midway to ensure effectiveness. At the end of the 6-month period, participants would move into a general communities-of- practice framework. This post-workshop activity would be captured in an individual’s PKMS and, as appropriate, in the overall organisational KM system. In effect this makes tacit knowledge explicit via spaces (“Ba”) for knowledge sharing and creation (Nonaka and Reinmoller, 2000; pp. 98-111).

In this way approximately 100 managers could pass through five 2-day PKMS Group workshops in 3-4 weeks, meaning that in about seven months an organization would develop a very knowledgeable KM implementation community. Although participants are encouraged eventually to offer their PKMS to their teams and reports, as well as familiarize their own manager with the approach, this is not routinely included initially in the program. We feel strongly that it is important that participants first feel how it is to be involved personally in these PKMS Groups before trying to help others.  As Gaunt (1991; pp. 85) asserts “I can only help others to the extent I have begun to ‘map my own ignorance’”.

Closing Remarks

In this paper we discussed foundations for, and details of, methods we recommend for acknowledging, exploring and positively influencing, non-rational people-factors that we feel are ignored in a typical KM or organizational learning initiative. Our intention was to heighten awareness and understanding of these factors, and to point out that by addressing them proactively, such initiatives would have a much greater chance of living up to their promise.

As Wheatley says so eloquently “There are no recipes or formulas, no checklists or advice that describe ‘reality’. There is only what we create through engagement with others and events” (1992; pp. 7); thus actioning our recommendations will still entail the exercise of leadership, vision, patience and fortitude.

by Peter A.C Smith and Moira McLaughlin

Knowledge Management Solutions – The IT Contribution


Managing an organization’s knowledge more effectively and exploiting it in the marketplace is the latest pursuit of those seeking competitive advantage. The interest in knowledge management has surged during the last few years, with a growing number of publications, conferences and investment in knowledge management initiatives.

In a year long study of international best practice (Skyrme and Amidon 1997), two main thrusts were identified. The first is that of making better use of the knowledge that already exists within the firm, for example by sharing best practices. This addresses the oft cited lament: “if only we knew what we knew”. Too frequently people in one part of the organization reinvent the wheel or fail to solve customer’s problems quickly because the knowledge they need is elsewhere in the company but not known or accessible to them. Hence, the first initiative of many knowledge management programs (between a third and a half according to surveys) is that of installing or improving an Intranet, and adding best practice or ‘expert’ databases.

The second major thrust of knowledge focused strategies is that of innovation, the creation of new knowledge and its conversion into valuable products and services. This is sometimes referred to as knowledge innovation (Amidon 1997).  This requires an environment where creativity and learning flourishes and knowledge is encapsulated in a form where it can be applied. One way is to embed  knowledge into products, where it is more easily disseminated. Products from tractors to domestic appliances are getting ‘smarter’, while other products, such as software, represent packaged knowledge.

The range of knowledge management activities is broad,  and touches many aspects of business operations, for example:

  • Creation of knowledge databases – best practices, expert directories, market intelligence etc.
  • Effective information management – gathering, filtering, classifying, storing etc.
  • Incorporation of knowledge into business processes e.g. through the use of help screens in computer procedures or access to experts from icons

Development of knowledge centers – focal points for knowledge skills and facilitating knowledge flow

  • Reuse of knowledge at customer support centers e.g. via case-based reasoning
  • Introduction of collaborative technologies, especially  Intranets or groupware, for rapid information access
  • Knowledge webs – networks of experts who collaborate across and beyond an organization’s  functional and geographic boundaries
  • Augmentation of decision support processes, such as through expert systems or group decision support systems.

In fact, any activity that uses and applies knowledge can benefit from the disciplines of knowledge management, and that covers most managerial and professional activities. Therefore, like other management ‘fads’ before, many existing business practices (such as information management and intelligence gathering) are coming under the knowledge management umbrella. Similarly, information systems solutions, such as document management and data warehousing are being similarly relabelled.

Such relabelling raises the question as to whether the current knowledge focus is merely a passing fad. The importance of knowledge as a strategic lever can in fact be traced back many years, to writers like Peter Drucker, who is credited with coining the term ‘knowledge worker’ (see explanation in Drucker 1993).  More recently, writers such as Quinn (1992), Wiig (1994), Nonaka and Takeuchi (1995), and Stewart (1997) have given important insights as to the contribution of knowledge to corporate success.

What is new, and therefore makes knowledge management more fundamental than simply a passing fad are the following factors:

  • The value of an organization’s wealth is increasingly in its intangible assets – its people, know-how, brands, patents, licenses, customer relationships etc.
  • Knowledge can command a premium price in the market – Applied know-how can enhance the value (and hence the price) of products and services. Examples are the ‘smart drill’ that learns how to extract more oil from an oil field, and the hotel chain that knows your personal preferences and so can give you a more personalized  service.
  • As suppliers and consumers get more globally connected (e.g. through the Internet), access to critical knowledge becomes easier and more cost effective.
  • As organizations become more efficient at what they do, they need to apply new learning and talent to help them differentiate themselves in the marketplace.
  • By retaining knowledge as organizations downsize or restructure, organizations can save costly mistakes and prevent “reinventing the wheel”.

The significant change as companies respond to these factors is that their knowledge processes become more explicit, more systematized, more cross-organizational and more geographically dispersed. As a consequence they more readily lend themselves to the application of information and communications technologies (ICT).

Thus, surveys (e.g.  Murray and Myers 1997, Chase 1997) have shown email, Intranet, Internet as effective knowledge management tools. Also, videoconferencing, document management, online information sources and decision support tools are quite widely used as such, although views diverge as to their effectiveness.

The First Generation – What Went Wrong?

Computer support of knowledge activities is far from new. In the 1970s there was a proliferation of ‘expert systems’, and heightened interest in artificial intelligence. It was suggested that they might radically transform knowledge activities within firms. The reality, as we know in hindsight, is that they fell far short of expectations. They could handle only a narrow range of problems, they required extensive knowledge elicitation, and they failed to grasp the fundamental nature of human thought processes. This era is best characterized as the one where we tried to make computers think, rather than using computers to help humans think.

Today, after years of steady progress, artificial intelligence has evolved new techniques, such as neural networks and intelligent agents, and is being widely applied in a growing number of applications. Our research also found it is used to some degree in a significant proportion of the world-class knowledge management programs we investigated. The main hurdle affecting all applications of ICT to knowledge management is coping with the fundamental difference between explicit and tacit knowledge (Figure 1).

Whereas explicit knowledge is that which can be codified into documents, databases and other tangible forms, tacit knowledge is that in the heads of individuals. Ask a

Figure 1. Two Types of Knowledge

person to describe explicitly how to ride a bicycle and they cannot, yet they know how to. This distinction, and the processes by which tacit knowledge is converted in to explicit knowledge and vice versa, is one of the central planks of Nonaka and Takeuchi (1995). Our research found it one of the most widely cited concepts by knowledge management practitioners, yet one that is often ignored by information systems professionals. There seems to be a Western tendency to capture knowledge by ”getting it into a database”. Yet some of the most successful applications of ICT in knowledge management include those that help human-human communications, most notably groupware, and especially Lotus Notes.

Frameworks for Thinking and Action

From the perspective of a knowledge architect, frameworks provide a convenient way of thinking about the role of ICT in supporting knowledge processes. Most frameworks map different ICT tools according to their function and whether they are used individually or by teams. One such framework is shown in Table 1.

Passive (information) Active





Computer conferencing

Expert networks

Meeting support





Document Mgmt

Info Retrieval

Knowledge bases

Expert Systems

Decision Support

Computer-Computer Data Mining Neural Networks

Intelligent Agents

Table 1. Knowledge Transfer Mechanisms

From an analysis of a wide range of tools and classifications, Jan Wyllie of Trend Monitor International has developed the functional schema shown below:

A MIND: Assimilation and Interpretation

a Mapping, b Summarization, c Significant pattern discovery, d Decision support

B COLLABORATION: Network and Communication

a Conversing, b Workflow, c Information sharing,   d Resource sharing e Groupware

C CONTENT: Gathering and Retrieval

a Preparation, b Classifying, c Searching,                d Filtering, e Indexing

D MEDIA: Storage and Form

a Numeric databases, b Textbases, c Imagebases,     d Multimedia

A framework that most managers can easily relate to is that which maps various ICT tools according to the knowledge processes they enhance. Having learnt about  Business Process Reengineering, many are now well oriented to the process view of the firm. Figure 2 shows a schematic of knowledge processes (similar to a value chain), whose left hand categories distinguish the two strands of knowledge management – identifying existing knowledge and creating new knowledge. A representative selection of ICT tools are mapped into different knowledge processes.

Some Key Technologies

The impact of each technology varies enormously from situation to situation. Several technologies recur in many knowledge management programs, partly because they are generic and pervade many core activities and processes. The main ones are now briefly reviewed.

Intranet,  Internet

The ubiquitous Internet protocols make it easy for users to access “any information, any where, at any time”. Further, browsers and client software can act as front-ends to information in many formats and many of the other knowledge tools such as document management or decision support. Remember too, that the basic functions of email, discussion lists and private newsgroups often have the biggest short term impact.

Booz Allen & Hamilton’s Knowledge Online is an Intranet that provides a wealth of information (e.g. best practice, industry trends, database of experts) to their consultants world-wide. Through active information management by knowledge editors (subject experts and librarians) the information remains well structured and relevant.

Groupware – Lotus Notes

What groupware products like Lotus Notes add over and above Intranets are discussion databases. Users such as Thomas Miller, a London based manager of insurance mutuals, access their ‘organizational memory’, as well as current news feeds in areas of interest, through one of Lotus’s key features, its multiple ‘views’. When writing new insurance proposals, existing explicit knowledge can be assembled from the archive, guided by an expert systems front-end, while tacit knowledge is added through discussion databases.

Intelligent Agents

The problem of information overload is becoming acute for many professionals. Intelligent agents can be trained to roam networks to select and alert users of  new relevant information. Additionally they can be used to filter out less relevant information from information feeds. However, in practice it seems that a well run knowledge center, such as those at Price Waterhouse, the best intelligent agent is still a human being!

A related technology is that of text summarizing, which British Telecom have found can summarize large documents, retaining over 90 per cent of the relevant meaning with less than a quarter of the original text.

Mapping Tools

There are an increasing number of tools, such as COPE and IDONS, that help individuals and teams develop cognitive maps or ‘shared mental models’. These have been used by companies such as Shell to develop future scenarios and resolve conflicting stakeholder requirements. In addition, other mapping tools, such as those found in Knowledge X, can represent conceptual linkages between different source documents.

Document Management

Documents, and especially structured documents, are the form in which much explicit knowledge is shared. With annotation and redlining facilities, they can become active knowledge repositories, where the latest version and thinking is readily shared amongst project teams.

By using a document management system for the construction of the Thelma North Sea oil platform, AGIP reduced construction time by 9 months and reduced document handling costs by 60 per cent. Suppliers like Dataware are repositioning their products as knowledge management products and are also adding ‘knowledge enriching’ functionality.

Knowledge Enriched Solutions

With a burgeoning and lucrative market for knowledge management solutions, many companies are simply relabelling their products and approaches e.g. information management as knowledge management, databases as knowledge bases, data warehouses as knowledge repositories. True knowledge management solutions are not simply new labels, but add knowledge-enriching features. These include:

  • Adding contextual information to data – where was this information used? What factors need to be considered when using it?
  • Using multimedia e.g. adding video clips or voice to databases of best practice or problem solution databases
  • Providing annotation – adding informal notes to individual data items; using MAPI enabled software, where a document or file can be sent with a forwarding note by email
  • Qualifying information – giving details of originator, users adding comments about the quality of information
  • Providing links to experts – a ‘click’ button to contact an expert (either by email or phone). GIGA, for example, lets its client access global experts through its web site (http://www.gigaweb.com).

These all help the transfer of tacit knowledge, and any tool should increasingly provide hooks that add new levels of interaction, not just person-to-computer but person-to-person.

Knowledge Collaboration Architecture

Over time, the boundaries of individual tools blur (c.f. groupware and Internet, document management and information retrieval), and effective usage requires seamless interoperability and fluidity of information and knowledge flow.

Therefore organizations using ICT to support knowledge activities need to think about an overall architecture. Some companies, such as Glaxo Wellcome are recognizing that knowledge management requires changes in established technical architectures.  Our analysis of several companies who have developed  architectures that support knowledge management indicates that tools and supporting processes are needed at several levels (Figure 3).

At the base level is the requirement that people should be able to connect into knowledge whenever and wherever they are (in the office, at remote sites, on the move etc.). At higher levels, there must be mechanisms for threaded conversations and structured collaborative work.

As you move up through each architectural layer (each of which depends on the one below), more of the challenges are people and organization, rather than technology, related. In our experience, most large organizations,

taking their position overall,  are still between the bottom two levels.

Achieving the Benefits

As any manager of change or implementer of ICT infrastructure knows, it is the human, organizational and cultural factors that are the ultimate determinants of success. ICT solutions for Knowledge Management are, in essence, social computing, and therefore need such an approach. Implementations that are successful are typically found to share the following characteristics:

  • Clear vision and leadership – a solid appreciation of the contribution of knowledge to business success and how IT can help.
  • Multidisciplinary teams – including information managers (librarians), facilitators, business experts as well as technologists.
  • User and business-centric. Users are actively engaged in developing solutions that enhance knowledge activities.
  • Well designed processes that engage humans where they are best, and allow them to interact with computers where computers perform best. A business process that does not consider applying best knowledge (and updating it) is an incomplete process.
  • Active learning and experimentation. There is no such thing as a finished requirement specification. Solutions evolve and adapt.
  • A knowledge sharing culture. People want to share information and their experience and are rewarded for doing so.


Information and communications technologies are an important ingredient of virtually every successful knowledge management program. An ever wider range of highly effective solutions are coming to market, including a new generation of artificial intelligence solutions, new flavors of document management systems and various collaborative technologies such as the Internet.

Successful implementation depends, as always, on giving appropriate focus to the non-technical factors such as human factors, organizational processes and culture, the multi-disciplinary skills of hybrid teams and managers, and the already existing knowledge repository of prior learning – providing, of course, that it is well structured, accessible and gives you access to critical expertise!

by Dr David J. Skyrme and David Skyrme Associates Limited

The Typology of Intellectual Capital and knowledge Management in Malaysian Hotel Industry


In order to sustain in the 21st century, organizations need to manage their knowledge based resources such as knowledge that is embedded in people, relationship and organization.  This study explores the knowledge management practices used by Malaysian hotels in exploiting their intellectual capital. This study employs case study approach, where interviews were conducted with Human Resource Managers of seven hotels. The hotels were from various star rating categories. In analyzing the data, within and cross-case analyses were performed. The findings supported the proposition that the development of intellectual capital in Malaysian hotel industry must correspond to the rating achieved by the hotel. The evidence from this study indicates that structural capital and human capital are significant in managing knowledge in Malaysian hotel industry. The outcome of this study ia a typology of knowledge management practices and intellectual capital in accordance to the star rating given by the Malaysia Ministry of Tourism and Heritage.

Keywords: knowledge management, human resource management, organizational knowledge, intellectual capital and case study.


Factors such as globalization that leads to new technology, free flow of capital, increased competition, the demand for innovation, changes in customer demand, changes in economic and political structures are constantly reshaping the way business is carried out (Buckley and Carter, 2000; Thorne and Smith, 2001).  Previous research has acknowledged the fact that organizations have begun to realize that sustainable advantage relies on managing intangible resources such as the knowledge embedded assets. According to Stewart (2002), in the 21st century, knowledge embedded assets have become more important to the organizations than financial and physical assets. Therefore, in order to compete in this millennium, organizations must have the ability to create value, be agile and sensitive to the market.

As such, knowledge embedded assets such as ideas, practices, talents, skills, know-how, know-what, relationships and innovations (Stewart, 2002), that arise from the creation of intellectual capital have become a pre-eminent economic resource and the basis for competitive advantage (Finney, Campbell and Powell, 2004; Demediuk, 2002; Graves, 2002). These knowledge embedded assets determine the success or failure of an organization. Sveiby (1997) believes that knowledge embedded assets can be found in three areas: the competencies of the employees; organization’s internal structure such as patents, models, computer and administrative systems; and organization’s external structure such as brands, reputations, relationship with customers and suppliers. On the other hand, Stewart (2002) believes that  knowledge embedded assets comprise of talents, skills, know-how, know-what, relationships and also include machines and network that can be used to create wealth to an organization. In short, many intellectual capital theorists have termed the knowledge embedded assets as intellectual capital (Demediuk, 2002; Sullivan, 1999; Stewart, 1997).

There is a dearth of research into intellectual capital management practices, and in particular practices of hotels. Previous research concentrates on intellectual capital measurement and reporting practices (Bart, 2001; Zsidisin et al., 2003; Abesekera and Guthrie, 2004).  The substantial growth in the awareness of intellectual capital issues together with the importance of knowledge is the major inspiration behind the hotel industry.  Apart from its tangible assets, the main driving force of its values comes from intellectual capital which customers are now willing to pay (Rudez and Mihalic, 2007).  Thus, our study focuses on the knowledge management practices in exploiting intellectual capital in hotel industry particularly in Malaysia.  This paper answers the questions such as: how Malaysia hotels can exploit their intellectual capital using different knowledge management practices?; which of the intellectual capital categories have impact on knowledge management practices?; and how to maximize the potential of  intellectual capital using different management practices? The findings from this research will contribute to the body of knowledge of intellectual capital from the management perspectives.


There is a multi-faceted description of intellectual capital as proposed by intellectual capital theorists. According to Stewart (2002), the term ‘intellectual capital’ seemed to have first appeared in 1958 when two financial analysts reported that the intellectual capital of several small science-based companies is perhaps the most important element in the organizations’ financial statements. The analysts termed the high stock valuations as an intellectual premium (Stewart, 2002), but, for a quarter of century, the idea remains unchallenged. In the 1980s, discussion and debate on resource-based theory had nurtured the ideas of intellectual capital. In 1987, a study by Sveiby produced the nature of intellectual capital.  He proposed that knowledge-based assets could be found in three places; the competencies of organization members, its internal structure—patents, models, computer and administrative assets, and its external structure—brands, reputation, relationships with customers (Sveiby, 1997). Meanwhile, Edvisson (1997) a leading thinker in intellectual capital from Skandia Insurance classifies intellectual capital into three dimensions: human capital (including employees’ collective competence, capabilities and brain power), organizational capital (such as a firm’s policy and procedures, customized software applications, research and development programs, training courses, patent and the like), and customer capital (comprising of relationship with customers, suppliers, industry associations and market channel).

In conclusion, most of the definitions and frameworks of intellectual capital includes human, customers, suppliers, and organizations as factors of intellectual capital (e.g. Roos and Roos, 1997; Saint-Onge, 1996). In order to remain forefront and maintain competitive edge, organizations must have the capability to retain, develop, organize and utilize their intellectual capital (Kalling, 2002; Wiig, 2000). Organizations must also be able to consolidate their intellectual capital faster than their competitors. Furthermore, most of the literature in intellectual capital proposes that the value of an organization is largely based on the management and utilization of intellectual capital (Ukkola et al., 1999; Chris and Emma, 1999; Beveran, 2002). Accordingly, intellectual capital must be explicitly managed and the competitive advantage will emerge from the way a specific knowledge is applied to production factors (Aranda and Molina-Feraz, 2002). To explicitly manage the intellectual capital, an understanding of how knowledge is formed and how people and organizations learn to use knowledge is essential.

There are two levels of knowledge within intellectual capital: explicit knowledge and tacit knowledge (Hall and Adriani, 2002; Kamiki and Mphahlele, 2002). Explicit knowledge is articulated knowledge and it can be embodied in the form of documents, standard operating procedures, and blueprints. Meanwhile, tacit knowledge includes the intuition, perspectives, beliefs, and values that people form as the result of their interactions and experiences (Hall and Adriani, 2002; Kamiki and Mphahlele, 2002). In an organization, tacit knowledge is made up of the collective mindsets of everyone in the organization. Tacit knowledge shapes the way a leader of an organization perceives his industry and his organization place within it. Tacit knowledge determines how an organization makes decisions and shapes the collective behavior of its members (Saint-Onge, 1996). It is acquired by experience, by learning and by doing. It is not codified and may not be communicated in the form of language. Haldin-Herrgard (2000), highlights that these tacit and explicit knowledge must be managed differently. Much of existing literature discusses more on philosophy and concepts of intellectual capital and less attention has been given on the value creation aspect of intellectual capital. Intellectual capital theorists argue that intellectual capital can only generate value when it is accessible and utilized. Intellectual capital management is applied to access and utilize intellectual capital of an organization.

Intellectual capital AND KNOWLEDGE management

Edvinsson and Sullivan (1996), Graham and Pisso (1998) and Chen and Lin (2004) have argued that managing intellectual capital is about managing, leveraging and harnessing knowledge embedded in those assets. Intellectual capital can only create value to organizations when knowledge embedded in the intellectual capital is exploited. The three types of intellectual capital: human capital, organizational capital and relational capital can be exploited through intellectual capital management. According to Volpel (2002), the three critical elements in managing intellectual capital are: the strategic imagination and the construction of the intellectual capital; the sharing of meaning emerging from intellectual capital; and the transforming of identifying through the assimilation of the intellectual capital. However, different styles of intellectual capital management can be applied by organizations to effective manage their pool of intellectual capital. The choice depends on organizations’ priorities and capabilities.

Liebowitz (2002), Davenport and Prusak (2000) and Sveiby (1997) have pointed out that the application of knowledge management is crucial in making organizations more effective. Therefore, as argued by Davenport and Prusak (2000), in order to make knowledge-based assets more visible, organizations should encourage and aggregate behaviors and build knowledge management infrastructures. They also argue that knowledge management infrastructures both indirectly and explicitly show the role of knowledge-based assets in an organization. Furthermore, appropriate infrastructure will support employees’ ability to think critically and creatively that will facilitate and foster employee effectiveness and behavior. In other words, organizations provide safe environment for employees to do their work, permit them to innovate, impose and ‘stretch’ organization policies and practices, and motivate the employees to act intelligently in doing the right things (Wiig, 1999).

Generally there are five activities involved in knowledge management activities: knowledge acquisition, knowledge innovation, knowledge storage, knowledge dissemination, and knowledge application.   Knowledge acquisition involves the acquisition activities and can either be created by the organization itself or acquired from various internal and external sources. Meanwhile, knowledge innovation is created through the interaction amongst individuals or between individuals and their environment. Consequently, there are four different modes of knowledge innovation: socialization, internalization, externalization, and combination (Nonaka and Takeuchi, 1995). Knowledge storage refers to the process of choosing a repository of knowledge once it is acquired and created. Knowledge repositories can be in the form of knowledge embedded in hard copy and electronic media which are made available to everyone in the organization (Bennet and Gabriel, 1999). Knowledge dissemination is concerned with knowledge sharing where knowledge is shared formally through meetings, seminars and databases or through informal discussion. Knowledge application is the process where knowledge is translated into actionable knowledge (Lee and Yang, 2002). This can be in the form of adjustments to organizational routines, the creation of new products or services or an improvement in the understanding of the environment.

Besides that, organizations must also be positioned to anticipate the needs of customers and respond to this need through additional innovative products and services. They must look inward and develop new products, processes and services constantly and also provide customers with high functionality and preference for products and services (Johannesson, Oldisen and Olsei, 1999). It is said that competition in today market focuses on competencies, relationships and new ideas. Therefore, organizations must undertake specific programs, activities, provide supporting infrastructure, capabilities and create incentives to motivate employees, department and business units. The transformation of intellectual capital requires transformation of common understanding in the organization and this will lead to attribution and sharing of real expectation.

Malaysian hospitality industry

The Asian Region is considered to be one of the fastest growing regions in the world in terms of travel, hospitality and tourism. In Malaysia, the hospitality industry has grown tremendously in line with the rapid development of travel and tourism in this country. The tourism sector in Malaysia has risen to the challenges and has emerged as the second largest contributor in terms of foreign earnings towards national income. With a flurry of international events being hosted in Malaysia and the ASEAN region, it is imperative and crucial for investment in human resource as a key factor for growth, sustainability, productivity and profitability in the Malaysian hospitality industry. In line with that, the importance of intellectual capital in hotel industry cannot be disputed.

To maintain an image of Malaysia as a family-oriented holiday destination, it is pertinent to ensure good hotel service and facilities. Thus, the Government has imposed tighter criteria for hotel ratings in a move to ensure better quality hotel service and facilities.  The star rating is based on the guidelines set by the United Nations World Tourism Organization, and adjusted to local cultures (Ministry of Tourism, Culture and Heritage, 2006). All hotels will be rated based on their qualitative and aesthetic requirements, common areas, bedroom requirements, services, safety and hygiene standards, and staff.  As in December 2007, there were 624 star rated hotels in addition to more than 2,200 tourist accommodation premises nationwide (Malaysian Associations of Hotels, 2008).


The evidence indicates that for the knowledge acquisition activity, the five and four-star hotels use environmental scanning to extract new knowledge. According to Pitts and Lei (2000), environmental scanning refers to the obtaining and gathering of information about a company’s environment. These hotels sent their employees to conferences and workshops to gain new knowledge. They also use feedback received from customers and related agencies to enhance the quality of their services. Acquired knowledge does not have to be newly created but only new to the company (Davenport and Prusak, 2000). Meanwhile, for the three and two star hotels, the acquisition activity is more internally focus. These hotels gain new knowledge from employees’ experiences, meeting reports, and internal documents. As argued by Jordan and Jones (1997), internal sources include co-workers, company’s database and internal documents. Reports from meetings are normally used as the main reference in problem-solving and decision making.

Although the management acknowledges the importance of knowledge in gaining competitive advantage, there was a lack of willingness seen in hotel rating 2 and 3 to invest in intellectual capital development specifically human capital.  This is similar to the findings from a study by SubbaNarasimha (2002).  It can be posited that this practice is due to management beliefs that once the employees gain such exposure, it is likely for them to move to other hotels.  Similar to Abeysekera’s (2007) findings, this study also found that hotel use structural capital to complement the knowledge management practices such as acquisition and dissemination activities.

Consistent to Abeysekera (2007), the findings of this study found that 3 and 4 star hotels consider employees as a cost to be minimized.  Therefore, they rely more on the contract workers especially during peak seasons.  This study perceived hotels which hire contract workers put less emphasis on human capital.

For knowledge storage activity, all hotels focus on development of customer database. But the knowledge storage activities for the five star hotels emphasize more on developing individual knowledge. Employees are encouraged to apply their creativity in order to enhance the quality of the services provided and to satisfy customers’ needs. On the other hand, for the three and two star hotels the knowledge storage activities put more emphasis on documenting organizational knowledge. All procedures, policies and standards are well documented and are strictly followed. There is no room for flexibility.

For knowledge dissemination activity, the evidence obtained indicates that in five and four star hotels, they encourage interactive interactions for sharing tacit knowledge. In these hotels, employees are given the opportunity to give suggestions and voice out their opinions especially matters that are related to their tasks informally. Nevertheless, for the three and two star hotels, the knowledge dissemination activity occurs formally and this knowledge is transformed into explicit knowledge in the form of documents.   However, the documents can only be accessed by the management level. Furthermore, the meetings that are conducted focus on daily operation to monitor their task and performance.

For knowledge application activity, the evidence from this study indicates that for five and four star hotels the focus is more to increase the quality of their services. New knowledge is applied to enhance their quality. However, for the three and two star hotels, this study found that the knowledge application activity is more towards increasing the effectiveness of their operations.


The study shows that the development of intellectual capital in Malaysian hotel industry must correspond to the rating achieved by the hotel. Since the rating of the hotels was based on the facilities and the services provided, intellectual capital would enhance their positions in that category.  The requirement of the rating can be met by any hotel as long as they have the financial capabilities.  However, what makes the hotel different from one another in the same rating depends on the intellectual capital that is manifested into the services provided.  The evidence from this study indicates that structural capital and human capital are significant in managing knowledge in Malaysian hotel industry.  Furthermore, these findings also revealed that these two capitals are necessary to initiate relational capital in the organizations.

The study suggests two important issues in managing intellectual capital.   First, it stresses that hotels need to continually upgrade their human capital by providing trainings consistently, encourage their employees to acquire new knowledge by related conferences and workshop, provide cross exposure by sending employees to other branches.  Secondly, hotels need to improve their structural capital by having frequent formal and informal meetings, encourage and acknowledge their participations and contributions to enhance the quality of its services and products.


The findings of this study largely support the theoretical arguments which suggest that organizations’ intellectual capital management reflect the resources that they have. Different organizations apply different types of intellectual capital management practice in order to exploit their intellectual capitals. This study is consistent with Hamzah and Ismail’s (2007) findings which indicates that the management of organizations intellectual capital is depends on the intellectual capital being developed by the organizations.

Although we believe this study has made a number of contributions to the body of knowledge, it inevitably subject to a number of limitations. Therefore, the findings of this study must be considered in light of: first, lack of generalization – as a case study research is typically based on a number of case, it is not qualified for statistical analysis and interpretation. But, generalization in case study research is achieved through the analytical generalization (Yin, 1994). Second, due to the difficulty to gain access to these organizations, the interviews were conducted with the top management only to get overall information of the organizations.   However, this study also used other method such as observations, and documentations to aid triangulation for multiple interpretations.

Research on intellectual capital can be considered as being at a growing stage. Therefore, there are many opportunities for conducting research in this field. This research can be held out as an attempt to delve into this area by suggesting directions for future research. This research concentrates on the intellectual capital management being practiced by focusing on hotel industry. The evidence gathered reveal that the intellectual capital management practiced vary in accordance with the resources that the organizations have. Future research could reconfirm these findings and generalize them over population by using large sample. This could be done by employing quantitative research and statistical test. Future research could also examine the intellectual capital management practiced on a longitudinal basis.  Furthermore, future studies could be undertaken involving various industries.

By Rosmah Mat Isa rosmah and Nor Liza Abdullah iza

Knowledge Exchange in Networks of Practice


Knowledge Exchange in Networks of Practice


The concept of a community of practice is emerging as an essential building block of the knowledge

economy. A community of practice consists of a relatively tightly knit group of members who know each other, work together face to face, and continually negotiate, communicate, and coordinate with each other directly. The demands of direct communication and coordination limit the size of the community, enhance the formation of strong interpersonal ties, and create strong norms of direct reciprocity between members (Brown & Duguid, 2000). These communities develop through the mutual engagement of individuals as they participate in shared work practices, supporting the exchange of ideas between people, which results in learning and innovation within the community (Brown & Duguid, 2000). However, typically not all of an organization’s relevant

knowledge resides within its formal boundaries or within its communities of practice. To remain competitive, organizations need to ensure that new knowledge found in the external environment is

integrated with knowledge that is found within the firm (Cohen & Levinthal, 1990). Organizations must rely on linkages to outside organizations and individuals to acquire knowledge, especially in dynamic fields where innovation results from inter-organizational knowledge exchange and learning (Cohen & Levinthal, 1990).


Current research has focused on the role of communities of practice for encouraging knowledge exchange and innovation within organizations; however, we know much less about the role that members of communities of practice play in creating linkages to external knowledge sources. Previous research has found that organizational members may simultaneously be members of a community of practice as well as members of broader occupational communities (Van Maanen & Barley, 1984). These individuals perform the dual roles of generating local knowledge within an organizational community of practice while providing linkages to knowledge and innovations outside of the organization. These interorganizational networks have been referred to as networks of practice. Networks of practice are social structures linking similar individuals across organizations who are engaged in a shared practice, but who do not necessarily know one another (Brown & Duguid, 2000). Although individuals connected through a network of practice may never meet one another face-to-face, they are capable of sharing a great deal of knowledge and may play a vital role in a firm’s ability to acquire new knowledge. While the participation of individuals in networks

of practice is not a new phenomenon, the ability to access these networks has increased due to recent advances in information and communication technologies. Previous efforts to interact with others outside an organization’s legal boundaries were often fruitless since they could be time-consuming or cumbersome, and individuals may not even have known whom to contact or how to find a relevant person. Furthermore, if management did not provide the resources to attend external conferences or other events, finding other like-minded individuals with whom to discuss work-related problems often proved difficult. However, communication technologies, such as cell phones, e-mail, IRC, chat rooms, bulletin boards, and so forth, have reduced the costs of informal inter-organizational communication. As a result, individuals may now easily access and discuss their work tasks with others outside their organization. These informal interactions are valued and sustained over time because the sharing of knowledge is an important aspect of being a member of a technological community or network of practice (Bouty, 2000).Sharing knowledge across external organizational boundaries poses significant challenges to organizations attempting to manage their

knowledge resources (Pickering & King, 1995). Through external sources, individuals gain access to knowledge not available locally and can interact informally, free from the constraints of hierarchy

and local rules. However, accessing knowledge from external sources usually involves a high degree of knowledge trading and reciprocity. In order to receive help, individuals must be willing to

give advice and know-how as well, some of which company management may consider proprietary

(von Hippel, 1987). Of special interest to management is that individuals generally participate in networks of practice based on their own personal biases and preferences for others as opposed to

what the formal organization dictates, and as a result, they may be exchanging knowledge with others who are working for direct competitors (Schrader, 1991). This makes the study of networks of practice of prime interest for researchers and practitioners.

Previous research related to networks of Practice

Networks of practice are not a new phenomenon. They have existed for hundreds of years and have played an important role in the diffusion of knowledge through society. For example, the well-known term, invisible colleges, dates back to the 1640s when a group of 10 men who were well-educated within one field would meet informally in the taverns of London. These meetings later developed in 1660 into the Royal Society, the oldest scientific society in Great Britain (Price, 1963; Tuire & Erno, 2001). While there is considerable previous research on inter-organizational informal networks under a variety of names—such as scientific communities (Knorr-Cetina, 1981; Polanyi, 1962), co-citation networks (Usdiken & Pasadeos, 1995), invisible colleges (Crane, 1972), epistemic communities (Haas, 1992; Holzner & Marx, 1979), thought-collectives (Fleck, 1935), paradigms (Kuhn, 1962), and occupational communities (Van Maanen & Barley, 1984)—a review of this literature reveals that research that explicitly focuses on knowledge sharing is quite limited. Below we present the relevant research and empirical studies that we found in our review. This research can be divided into two categories: (1) studies from the perspective of scientific communities and (2) studies from the perspective of high-technology firms.

Scientific Communities

Research on scientific communities suggests that knowledge sharing occurs between members as they engage in debate and discussion of each other’s ideas and results, and through collaboration

on joint research projects (Crane, 1972). Due to the universal nature of knowledge, shared language, and values within the scientific community, individuals can communicate relatively easily with one another (Tushman & Katz, 1980; Van Maanen & Barley, 1984). Thus, knowledge and innovations spread quickly across organizational, national, and cultural boundaries through these informal relationships. In many cases, these informal networks are more valuable for sharing knowledge than more formal channels, such as publications, since the results of failed experiments

are rarely published, and learning about these can prevent their duplication. In scientific communities, the central goals and values of the members are generally developed and spread throughout the network (Hagstrom, 1965). Strong norms that are well defined and socially imposed, such as reciprocity in knowledge sharing, respect for individuals’ intellectual property rights, and honesty in research, facilitate knowledge exchange (Bouty, 2000; Liebeskind, Oliver, Zucker & Brewer, 1996). Trustworthy behavior and norms are enforced since the level of participation in the community is jointly determined by the community’s members. Individuals who fail to follow the norms and implicit code of conduct can be excluded from participating in valuable exchanges with others (e.g., participation in research teams with leading researchers, access to the latest research findings, etc.). This exclusion can then negatively impact their career success (Tuire & Erno, 2001). As a result, the production and sharing of valuable knowledge is facilitated, allowing the frontier of knowledge to progress rapidly and at minimal cost Structural studies of research-based communities of academic scientists have shown that these networks are generally characterized by a center and a periphery (Schott, 1988). The most important, visible, or active members are generally found in the center, and these individuals influence the direction of the development of the community’s knowledge. The activities of the individuals in the core determine the community’s dominating theoretical concepts, methods, and chosen research problems, which are then mediated through the community’s links to individuals in the periphery (Schott, 1988). Through a process known as social contagion (Marsden, 1988), new members are socialized into the community and as such transform their personal identities, adapting their attitudes, behaviors, and values to those of the community (Holzner & Marx,

1979). Additionally, power is an integral part of scientific communities, with individuals often using knowledge strategies as components of power strategies (Holzner & Marx, 1979). Thus, the center of a scientific community is not only a realm of activity, but it also is a realm of identity

and cultural values of the community (Schott, 1988; Tuire & Erno, 2001).

High-technology Firms

Researchers have also taken the firm’s perspective and focused on inter-organizational boundary spanning activity in high-technology firms. A major stream of this research began in the 1960s with an investigation into the communication patterns of scientists and engineers in R&D laboratories (see Flap, Bulder & Volker, 1998, for a review). One area within this research is why individuals communicate informally with others outside the organization. For example, von Hippel (1987) found that when specialist engineers could not find the required know-how in-house or in publications, they went outside their organization to their professional networks developed at conferences and other events. Further research has found that quite often professionals communicate with others in their professional networks in order to maintain contact with a reference group and to keep abreast of technological changes (Aiken & Hage, 1968). Allen (1970) has also found that low-performing individuals choose to go outside for help. He argues that this choice is a way to avoid paying a sychological price of loss of face that occurs when an individual asks a colleague who is not a friend or advice.A second area of investigation has focused on the informal flow of knowledge across a  irm’s boundaries in a limited number of settings, such as semiconductor, specialty steel and mini-mill industry, and R&D operations (Carter, 1989; Schrader, 1991; von Hippel, 1987). This research provides evidence that participation by individuals in inter-organizational networks leads to  knowledge sharing across a firm’s legal boundaries that is generally not governed by firm  ontracts or other market mechanisms (Liebeskind et al., 1996). In many instances, this  nowledge sharing may even include the exchange of confidential organizational knowledge,  ven with others who might even be working in rival firms (Schrader, 1991; von Hippel, 1987).  hus, it is argued that knowledge “leaks” across the firm’s legal boundaries (Mansfield, 1985; von  ippel, 1988). Bouty’s research (2000) raises a very interesting point though—confidentiality is socially  onstructed, and as one of her interviewees noted, there are  “open secrets.” Research by Jarvenpaa and  taples (2001) further touches on this aspect of socially constructed confidentiality since they find that the more individuals view their knowledge as personal expertise, the more individuals regard such  nowledge as their own property and not that of the organization. However, this research suggests that  ndividuals do not just give the knowledge away to others outside their firm. Rather they  onsciously exchange knowledge with other carefully chosen individuals with whom they often have    ong-term relation built on mutual trust and understanding (Bouty, 2000; Schrader, 1991). Research  onducted by Schrader (1991) finds that individuals often expect that their chances of receiving  aluable knowledge in return are likely to increase after they provide knowledge. Thus,  articipation in inter-organizational emergent networks results in reciprocity and dyadic exchange  f knowledge (von Hippel, 1987), with knowledge sharing viewed as an ‘admission ticket’ to the  ngoing ‘back room’ discussions within professional networks (Appleyard, 1996). As a result,  articipation in inter-organizational networks leads to knowledge leaking in at the same time as it  eaks out of the firm (Brown & Duguid, 2000). Research on the relationship between this knowledge  xchange and performance at any level, however, is scant. One of the primary reasons is that it  s very difficult for firms to manage and evaluate the benefits since it occurs “off the books”  (Carter, 1989). Secondly, data regarding the sharing of potentially firm proprietary knowledge  re  ifficult to collect due to their sensitive nature. However, there is some initial evidence of a positive  elationship between knowledge trading and firm performance (Allen, Hyman & Pinckney, 1983;  chrader, 1991), between knowledge trading and project performance (Allen, 1977), and  etween  nowledge trading and individual performance (Teigland, 2003; Teigland & Wasko, 2003).

Areas For Future research Networks of practice are proposed to be a valuable complement  o intra-organizational face-to-face communities of practice. The implication is that in order to be  ompetitive, organizations should focus on sponsoring participation in both traditional communities of  ractice and networks of practice, as well as stimulating the interaction between the two. This leads to  everal interesting areas in need of further research. One area that deserves attention addresses the  uestion of why individuals participate and access knowledge in networks of practice. While the  esearch within high-technology firms provides some initial suggestions—for example, the  nability to find the required knowledge in-house, the desire to maintain contact with a professional  eference group or long-term relations with close ties, to keep abreast of technological changes, and  ven to avoid loss of face—the ability to access knowledge through weak tie connections  asically requires depending on the kindness of strangers (Constant, Sproull & Kiesler, 1996). Prior research has emphasized the importance of shared language, values, and goals, as well as long-term  elations built on mutual trust for knowledge exchange. Thus, another area of research should  nvestigate the factors that lead to the creation of these facilitators within networks of practice,  specially networks sustained through electronic communication. Future research should also  nvestigate the relationship between network structure and knowledge sharing, how network structures change over time, and how network structure influences the cognitive aspects of  hared language, values, and goals. The studies reviewed above have also provided evidence that  ndividuals in many instances participate in the exchange of confidential organizational  nowledge,  ften making their own decisions to share knowledge without management’s consensus or even  wareness. As a result, knowledge “leaks” across an organization’s boundaries, indicating  additional areas for future research. For example, future research could investigate the factors leading  o this leakage such as “open secrets,” social construction of confidentiality, expectations of  eciprocity, and so forth. Another factor to be investigated is that of commitment. Just as individuals have    ertain degree of commitment to their organizations, they also have a degree of commitment to their profession or occupation (Van Maanen & Barley,  1984). In some professions, the degree of commitment to the profession can be so strong that the norms of the profession transcend the norms of  he employing organizations. Finally, research on the relationship between knowledge leakage and  erformance at all levels is scant and is in need of significant research, especially due to management’s concerns relating to the “leakage” of firm proprietary knowledge.


In  onclusion, the purpose of this article was to direct our attention to networks of practice since current  ommunity of practice research has focused primarily on their role for encouraging knowledge  xchange and innovation within organizations. While networks of practice are not a new  henomenon, a review of previous, related research reveals that the studies that explicitly focus on  nowledge sharing are quite limited. As a result, we know much less about the role that members  f communities of practice play in creating linkages to external knowledge sources and how  articipation in networks of practice influences performance at the firm, project, or individual level.  ur review of the literature has also provided us with several areas for future research, and we hope that these suggestions, along with our review, will inspire researchers to further investigate networks of practice.

by Robin Teigland and Molly McLure Wasko

Knowledge Transfer in Project-Based Organizations: An Organizational Culture Perspective


This conceptual paper investigates the process of knowledge transfer in project-based organizations from the perspective of organizational culture. The paper identifies obstacles to knowledge transfer in project-based organizations and emphasizes the

importance of organizational and project cultures in this process. The study provides some suggestions for improving knowledge transfer in project-based organizations and notes the implications of the paper for project management.

KEYWORDS: knowledge transfer, project-based organizations; organizational culture


Because the projects undertaken by project-based organizations (PBOs) are characterized by uniqueness, uncertainty, and complexity, PBOs are different from other business organizations in many respects. These differences extend to their requirements with respect to knowledge transfer.

Although the benefits of knowledge transfer have long been recognized in project-based organizations, the effectiveness of such knowledge transfer varies considerably among these organizations. The ability to manage what they know is often constrained by their capabilities with respect to creating, valuing, absorbing, and sharing knowledge. For this reason, an effective understanding of knowledge management-how PBOs utilize and integrate their dispersed knowledge-becomes essential.

Such knowledge management in project-based organizations is often a complex task. This is because project teams often consist of people with diverse skills working together for a limited period of time; indeed, a project team often includes members who have never worked together previously and do not expect to work together again (Burns & Stalker, 1961). In these circumstances, effective knowledge management is complex, but essential. Moreover, many “non-project businesses” are now adopting a “project-style” approach to their conduct of a variety of operational activities, and the influence of such “project-based” actions on the whole organizational performance is of increasing importance in a range of industry sectors. However, as Love (2005) has noted, knowledge management within projects is often suboptimal within these organizations because knowledge is created in one project, and then subsequently misplaced.

Organizational culture is the basic, taken-for-granted assumptions and deep patterns of meaning shared by organizational participation and manifestation of these assumptions (Slocum, 1995). The failure of many knowledge transfer systems is often as a result of cultural factors rather than technological oversights. However, culture, by its very nature, is a nebulous subject with a variety of perspectives and interpretations.

Against this background, the objective of the present conceptual study is to investigate knowledge creation and transfer in project-based organizations from the perspective of organizational culture. The research question addressed by the study is: How does organizational culture affect the process of knowledge transfer in project-based organizations?


The concept of “knowledge” can be distinguished from “data” (unprocessed raw facts) and “information” (meaningful aggregations of data). Knowledge involves a person using his or her perception, skills, and experience to process information-thus converting it into knowledge in the mind of the individual (Kirchner, 1997). Information thus has little worth in itself until it becomes knowledge as a result of processing by the human mind (Ash, 1998).

The process begins with data being organized to produce general information. The next stage involves this general information being sorted and structured to produce contextual information that meets the requirements of a specific group of users (such as project teams). Individuals then absorb the contextual information and transform it into knowledge on the basis of the individuals’ experiences, attitudes, and the context in which they work. The final stage of the process is behavior; as Infield (1997) has observed, unless knowledge leads to an informed decision or action, the whole process is useless.

Knowledge can be categorized into: (i) tacit knowledge and (ii) explicit knowledge (Nonaka & Takeuchi, 1995). Explicit knowledge is documented, public, structured, externalized, and conscious; it has a fixed content that can be captured and shared through information technology. In contrast, tacit knowledge resides in the perceptions and behavior of human beings (Duffy, 2000); it evolves from people’s interactions and requires skill and practice. According to Nonaka and Takeuchi (1995), it is often difficult to express tacit knowledge directly in words; in these cases, the only means of presenting tacit knowledge is through metaphors, drawings, and various forms of expression that do not involve the formal use of language. Tacit knowledge thus refers to feelings, intuitions, and insights (Guth, 1996); it is personal, undocumented, context-sensitive, dynamically created and derived, internalized, and experience-based (Duffy, 2000).

According to Nonaka and Takeuchi (1995), new knowledge is created by an interaction between explicit knowledge and tacit knowledge, facilitated through socialization and knowledge sharing. However, this does not imply a dichotomy between tacit knowledge and explicit knowledge; rather, the two forms of knowledge are mutually constituted (Tsoukas, 1996). According to Mooradian (2005), explicit knowledge is an extension of tacit knowledge to a new level. Tacit knowledge can thus be understood as knowledge that is active in the mind, but not consciously accessed at the moment of knowing. It grounds, enables, and produces the explicit knowing of individual peoplesuch as the members of a project team.

Knowledge Flows

According to Snider and Nissen (2003), knowledge flow is a critical factor in an organization’s success. These authors categorized such knowledge flow from three perspectives: (i) “knowledge as solution,” (ii) “knowledge as experience,” and (iii) “knowledge as socially created.”

The first perspective, “knowledge as solution,” emphasizes the real-time transfer of knowledge among practitioners who are seeking to solve problems or enhance operations. The key managerial issues in this perspective include the selection of an appropriate technology and the motivation of organizational members to use the system.

The second perspective, “knowledge as experience,” describes knowledge as being obtained and accumulated for future use. According to this perspective, the principal flow of knowledge is across time, rather than across organizational or geographical space (as is the case in the “knowledge-as-solution” perspective). The emphasis is on capturing practitioner experiences so that others can have access to (and potentially learn from) these experiences. The rationale of this perspective is learning from mistakes and avoiding attempts to “reinvent the wheel.”

Whereas the previous two perspectives see knowledge as a commodity that can be transferred to others, the third perspective, “knowledge as socially created,” emphasizes knowledge as being created and shared through interpersonal social relationships. Managerial issues associated with this perspective are concerned with organizational design to enhance the development of interpersonal relationships. Members must engage in informal and unstructured communications to facilitate sense making, discussion, negotiation, and argument-which are central to the knowledge-transfer process. This perspective advocates a supporting organizational culture that encourages informal interactions between individuals to ensure that knowledge is created and transferred.

Project-Based Organizations and Project Management

Project-based companies are organizations in which the majority of products are made against bespoke designs for customers. These types of organizations can be: (i) stand-alone companies that make products for external customers, (ii) subsidiaries of larger firms that produce for internal or external customers, or (iii) consortiums of organizations that collaborate to serve third parties (Sandhu & Gunasekaran, 2004; Turner & Keegan, 1999).

The growing trend in project management is not a breakthrough of new ideas; rather, it is a revitalization of the discipline in a current business context. Project management is increasingly concerned with taking systems and processes that originated in the conventional paradigm of project management and applying them to general organizational theory. Whereas project management was previously regarded as a specialized management process with specific planning, monitoring, and control techniques that were applied to the operations of a few project-oriented industries (such as construction, engineering, and defense), it has now come to be regarded as an inclusive concept that can be integrated into a general organizational effort to provide better quality to customers through effective intra-organizational integration and the optimal utilization of scarce resources. As a result, project management is now positioned as a complex managerial process among other organizational processes (such as knowledge management) that ensures an optimal balance between the internal organizational design of a firm and its emerging strategies.

Project Management and Knowledge Transfer

Knowledge management is of crucial importance to efficient project management. The growing complexity of project work means that an increasing number of technical and social relationships/interfaces must be taken into account by project managers in adapting knowledge and experiences from the daily work of a company and from earlier projects. Project team members frequently need to learn things that are already known in other contexts; in effect, they need to acquire and assimilate knowledge that resides in organizational memory. Their effectiveness in doing this determines their personal effectiveness, the project’s effectiveness, and, ultimately, the company’s effectiveness (Huber, 1991).

Within functional organizations, there are established departments and branches in which knowledge and experiences are acquired and stored. Project teams know that they can access this knowledge and experience from the documented records of a specific department, or from observing the competent employees and their working processes.

The situation is somewhat different in specifically project-based organizations because the team members of particular projects are the main transporters of knowledge and experiences of daily work. In the ideal case, the arrangements for transfer of knowledge and experiences from specific projects to the main organization are clearly established by project management. In these circumstances, project-based organizations systematically identify and transfer valuable knowledge from current projects to subsequent projects. However, this ideal scenario is often not the case. In other words, project information is infrequently captured, retained, or indexed so that people external to the project can regain and apply it to future tasks (see also Weiser &Morrison, 1998).

A failure to practice effective knowledge management means that many project-based organizations are unable to appraise projects and learn from them. At its simplest, a failure to review a finished project means that the past errors are likely to be repeated. In some cases, project-based organizations can fail to learn from their mistakes for years on end. A broad range of reasons for this failure in knowledge management has been suggested-including organizational, technical, methodological, and cultural issues (Boddie, 1987).

It is not as though the concept of archiving and using learning histories is unknown in project-based companies. Indeed, in many companies it is considered good practice to create documented accounts of what has been learned in a project. However, according to Conklin (2001), even in companies in which this practice is normal routine, it is difficult to find instances of the resulting document actually being referenced in the next project. Alternatively, some project teams have attempted to capture their learning by videotaping their meetings; however, these teams often accumulate a staggering volume of recorded materials on tape (Conklin, 2001). The important pieces of data they require for subsequent projects are in there somewhere, but no one has the time to peruse all the recorded material and locate the relevant data.

It is thus apparent that project-based companies cannot create a useful memory store merely by capturing lots of data; rather, they must organize these data in a manner that creates a coherent whole. This cannot be achieved as a “by-product”; that is, it cannot be relegated to the status of an extra task that is peripheral to the organization’s main production process (Conklin, 2001). However, many of the people who work in project-based companies are bombarded by urgent problems and pressing deadlines and do not have the time to commit themselves to an explicit knowledgemanagement undertaking (Jashapara, 2004). It is thus apparent that project-based companies must find ways of preserving and utilizing their knowledge within the established practices of everyday teamwork.

In undertaking this task, project-based organizations require a clear understanding of the sorts of knowledge that should be included in an effective knowledge-management system. In this regard, Conroy and Soltan (1998) have identified three “knowledge bases” in project implementation:

* an organization knowledge base, which includes the knowledge specific to organizations and environments in which the projects are implemented;

* a project-management knowledge base, which includes the knowledge of the theory and application of project management; and

* a project-specific knowledge base, which includes specific knowledge acquired within the implementation of a particular project.

Although the knowledge produced within the implementation of a given project is categorized in this schema as “project-specific knowledge,” Conroy and Soltan (1998) noted that the organization base and the project-management base are also developed during the implementation of any project. Conroy and Soltan (1998) divided such project-created knowledge into three general categories:

* technical knowledge, which relates to the techniques, technologies, work processes, costs, etc., that are involved in discipline-specific issues of the project;

* project management knowledge, which relates to the methods and procedures required for managing the implementation of projects; and

* project-related knowledge, which refers to knowledge about the customer and other people or entities that are of significance for the future business of the company.

Because this project-created knowledge is initially held only by project team members, it is necessary to identify, capture, and make this knowledge available to the organizational memory of the company.

Obstacles to Knowledge Transfer in Project-Based Organizations

Most project tasks are conducted under strict constraints of time and budget. In addition, team members from a completed project are usually needed for the next project, and their new team leaders therefore recruit them into new teams as soon as possible. Given these constraints, it is rarely possible for all team members to undertake a systematic review of a completed project and document the knowledge and experiences derived from it.

Furthermore, there are significant individual and social barriers that prevent the articulation and documentation of knowledge and experiences (Disterer, 2001, 2002). In particular, barriers exist with regard to the honest and open analysis of failures and mistakes; the open and productive atmosphere that would facilitate the articulation and analysis of errors is rarely present in most project-based organizations. This is unfortunate because successful projects demonstrate only that the methods that were employed were adequate for that specific task, whereas failed projects are likely to yield more valuable knowledge. Unfortunately, more effort is required to expose what mistakes can teach (Boddie, 1987).

Motivation to undertake a proper review is also a problem. It is apparent that the organization as a whole can benefit if individual employees can make use of the knowledge and experiences of their colleagues in previous projects. However, these synergies among employees can only be fully established and developed if all employees are willing to take part in the knowledge exchange. Unfortunately, these potential benefits to the organization are not readily apparent to individual employees, who are inclined to ask: “What benefit is there in it for me?” In short, there is insufficient individual motivation to document the lessons learned.

There is also often a lack of leadership in according sufficient importance and status to proper knowledge management. Although most methodologies recommend particular work packages for securing knowledge and experiences, the fact is that diese processes are often not included in the overall project plan (Liikamaa, 2006). It is not surprising that team members do not perceive effective knowledge management as being significant if the project plan does not explicitly assign sufficient time and resources to this aspect of the project.

In many ways, these problems reflect inadequacies in organizational culture. Knowledge transfer involves communication among people, and although technology can handle the communication of already explicit knowledge, the communication of intrinsic knowledge (and the creation of new knowledge by the transformation of information into knowledge) requires social interaction and human cognition. Any analysis of knowledge transfer thus requires the culture of the organization to be taken into consideration.

In summary, the above discussion has shown that knowledge cannot simply be stored (Gopal & Gagnon, 1995). Knowledge resides in people’s minds, rather than in computers (“CSFI Knowledge Bank,” 1997). Unlike raw material, knowledge is not coded, audited, inventoried, and loaded in a warehouse for employees to use as needed. It is scattered, messy, and easy to lose (Galagan, 1997). In this regard, Allee (1997) identified 12 characteristics of knowledge in noting that:

. . . knowledge is messy; it is selforganizing; it seeks groups of people; it travels on language; it is slippery; it likes carelessness; it is in shape of experiments; it does not grow forever; it is a social phenomenon; it evolves organically; it is multi-modal; and it [requires] the flow of data/information.

It is therefore necessary to develop effective multidimensional means of facilitating the input of (and access to) information (Mayo, 1998). It is also necessary to develop effective ways of sorting the useful from the useless (Schaefer, 1998). To achieve these things, it is necessary for project-based organizations to develop an organizational culture that coordinates and facilitates knowledge transfer.

Organizational Culture and Knowledge Transfer

An organization’s culture consists of the practices, symbols, values, and assumptions that the members of the organization share with regard to appropriate behavior (Schein, 2000; Wilson, 2000). Such a culture is holistic, historically determined, and socially constructed; moreover, it exists at various levels in the organization and is manifested in virtually all aspects of organizational life (Hofstede, Neuijen, Ohayv, & Sanders, 1990). According to Denison (1990), an organization’s culture serves as a foundation for its management system and practices. Because the organization’s culture provides norms regarding the “right” and “wrong” ways of operation, organizational culture stabilizes the firm’s methods of operation.

Organizational culture thus ultimately determines how decisions are made, and how staff members respond to the environment (Ott, 1989). In the words of Schein (2000, p. xxiv), organizational culture represents: “… the deeper level of basic assumptions and beliefs that are shared by members of the organization, which operate unconsciously in the environment.” It has been described as a “social force” that motivates people to act in a particular manner (Gundykunst & Ting-Toomey, 1988). In the opinion of Kilmann, Saxton, and Serpa (1985), culture is to the organization what personality is to the individual-themes that provide meaning, direction, and mobilization.

An awareness of the organization’s culture increases the likelihood of learning becoming a natural process in the organization. This is because a proper awareness of the organization’s culture involves the identification and recognition of the tacit assumptions and beliefs that are embedded in the organization (Schein, 2000). Recognizing and questioning these basic assumptions enhances the capability of the members of the organization to engage in so-called “double-loop learning” (Argyris & Schön, 1978). An organizational culture that is based on a commitment to truth and inquiry empowers individuals to: (i) reflect on their actions, (ii) consider how these actions can contribute to problems, (iii) recognize the necessity for change, and (iv) perceive their own roles in the change process (Senge, 1990). In terms of project management, such “double-loop learning” (or “generative learning”) is likely to occur only if the project design encourages team members to question institutional norms (Ayas & Zeniuk, 2001).

Organizational culture thus has the potential to constrain or facilitate knowledge creation and transfer within an organization. According to West (1997), the two fundamental dimensions of organizational culture are: (i) flexibility versus control and (ii) internal orientation versus external orientation. Greater flexibility is characterized by “flatter” organizational structures, decentralized decision making, and minimal specialization of jobs, whereas greater control is characterized by hierarchical structures, centralized decision making, and a large number of specialized jobs with a proliferation of job titles. Rigid and formal structures can promote mere functional efficiency, but this is often at the expense of collaborative and innovative activities.


Figure 1: Four core cultures.

External forces also shape organizational culture because organizations necessarily reflect the national, regional, industrial, and occupational cultures within which they function. In some cases, these can take the form of religious dogma and political ideology. An organization’s culture can thus reflect many beliefs that do not originate from within the organization.

In the management literature, there are many different typologies of organizational culture. For example, according to Schneider (1994), it is possible to identify four distinct “core cultures” on the basis of: (i) what each culture focuses on (“content”) and (ii) how each culture makes decisions (“process”). As illustrated in Figure 1, this can be depicted in terms of two axes: (i) a vertical axis indicating content (“actuality” or “possibility”) and (ii) a horizontal axis indicating process (“personal” or “impersonal”).

According to Schneider (1994, p. 77):

… the qualities and characteristics associated with the content and process axes are organizational and cultural preferences or central tendencies . . . [and as such] are not exclusionary-having a preference for one does not preclude involvement in the other.

In other words, placing an organization in a particular quadrant does not mean that the culture of the organization is exclusively of a particular type. For example, an “actuality” organization does not deal exclusively in facts, nor does a “possibility” organization ignore facts; rather, one style predominates in how the firm works.

The four “core cultures” illustrated in Figure 1 can be characterized as follows:

* Control core culture is concerned with ensuring certainty, predictability, safety, accuracy, and dependability.

* Competence core culture is concerned with achievement, gaining distinction by being the best and/or having the highest quality; this is a culture of unique products and/or services

* Collaboration core culture is concerned with affiliation and synergy in a culture of unity and close connections; this culture is concerned with tangible reality, actual experience, practicality, and utility; however, its decision making is people-driven, organic, and informal.

* Cultivation core culture is concerned with meaningfulness, self-actualization, and enrichment; this culture is concerned with potential, ideals, beliefs, aspirations, inspiration, and creative options; its decision making is people-driven, open-minded, and subjective.


Figure 2: Project culture (Ruuska, 1999).

Understanding the culture of an organization is critical to running successful projects. However, individuals, project teams, and organizations can seldom be categorized into one particular type of organizational culture because they typically represent mixtures of several cultural patterns. Nevertheless, shared values and a unified vision are vital for projects because they provide the focus and energy for knowledge creation. Although adaptive knowledge creation is possible without vision, generative knowledge creation occurs only when people are striving to accomplish something that matters deeply to them. The whole notion of generative knowledge creation can appear to be abstract and meaningless unless people become enthused about a shared vision to which they are committed.

The situation is complicated in project management because a project involves several experts working in various fields. Different professions typically have their own cultures and ways of working, which are not necessarily in harmony with one another or with the prevailing culture of the whole project (Ruuska, 1999). According to Wang (2001), a professional culture shapes a professional community by ensuring that the members of the profession think and behave as the profession requires. Because a profession is not limited to a particular organization (or even a particular industry or nation), its professional culture exists across boundaries.

To achieve harmony in these circumstances, a project requires a strong directional culture, as illustrated in Figure 2.

This requires a synthesis of cultures, rather than an attempt to unify the various professional cultures; it thus requires appropriate modes of cooperation and communication for the project at hand.

Promoting Knowledge Transfer in Project-Based Organizations

An organization consists of several levels in which knowledge can be initiated (Crossan, Lane, &White, 1999; Nonaka & Takeuchi, 1995). For convenience, these levels can be differentiated as the individual level, the group level, and the organizational level.

* Individual: According to Simon (1991), knowledge originates with individuals and is then transferred to other levels of the organization.

* Group: Knowledge transfer at the group level can be understood as a social process (Simon, 1991), which provides an opportunity for an exchange of ideas (Hall, 2001).

* Organizational: Knowledge can then be transferred and institutionalized in the wider organization (Crossan et al., 1999). This knowledge alters the beliefs and assumptions of the organization, and ultimately transforms the organization’s prevailing procedures and systems.

According to Schein (2000), any difficulties in knowledge transfer between these levels are primarily related to the “psychological climate” of the organization, which, in turn, depends upon the culture of the organization. According to this view, the biggest challenge for knowledge transfer is not technical (which can be overcome with IT systems), but cultural (“Knowledge Management,” 1997; Koudsi, 2000). In particular, there is often a prevailing attitude that holding information is more important than sharingit (Anthes, 1998). In one study (“The People Factor,” 1998), culture was perceived by 80% of those surveyed as the biggest obstacle to effective knowledge transfer.

Many project-based organizations are attempting to facilitate knowledge management by utilizing databases of customers, products, and services to share and distribute information. However, organizations that attempt knowledge management without an effective managerial support structure often discover that their investment in knowledge management fails to deliver the expected benefits (Goh, 2002; Nahm, Vonderembse, & Koufteros, 2004). The project manager has a crucial role in creating a team culture that facilitates the development of project goals and group norms with respect to decision making, conflict resolution, and so on. In doing so, project managers often have to deal with several different cultures simultaneously. They typically work within the core culture of their own organization, and also have to work with the subcultures of various departments within the organization (such as research and development, marketing and sales, and manufacturing) and with the core cultures of external organizations. Each of these has its own ways of doing things (Suda, 2006). Effective communication with these various subcultures and external cultures is necessary to develop plans and strategies that will be accepted by all, while avoiding practices that violate the beliefs and values of any.

Managers who are aware of cultural differences can avoid or minimize unproductive conflicts and misunderstandings. For example, the nature of communication in research-and-development projects is different from that in standardized delivery projects, and it is therefore important for managers to take these differences into account. If managers are not aware of such cultural differences, they might attribute difficulties to a coworker’s inflexibility or stubbornness, which is likely to polarize differences, escalate conflicts, and increase the difficulties of completing the project.

According to Abell and Oxbrow (1997), three areas require particular attention by management in seeking to establish an effective organizational knowledge culture: (i) preparing the organization, (ii) managing knowledge resources, and (iii) organizing knowledge for competitive advantage. However, transformation of an organizational culture is difficult to accomplish (Roth, 2004). Smaller organizations and recently established organizations are easier to change than larger, older organizations that have a well-established corporate culture and an inflexible managerial style (Becerra-Fernandez, Gonzalez, & Sabherwal, 2004).

Certain questions must be addressed in gathering and preserving knowledge at different stages of a project (Disterer, 2002):

* How is communication conducted among various members of the project team?

* What elements have improved the progress of the project, and which have slowed it down?

* What types of knowledge from the project can be forwarded to others?

* What is the progress of the project tasks during different stages?

* Which issues are critical for successful acquisition of project knowledge?

* What can be performed well and what can be improved in the next project?

* What are the particular complications during a project that can inhibit knowledge collection and preservation, and how can these be managed?

From the above discussion, it is apparent that knowledge management in project-based business has a higher probability of succeeding if managers:

* begin with the premise that organizations are living social systems;

* assess and identify the organization’s core culture, and align the project with it; and

* recognize that all organizations have a core culture and that the project culture must function in accordance with the organization’s core culture.


The conclusions of this paper can be summarized as follows:

First, for effective knowledge transfer in project-based business, it is crucially important to prepare the organizational culture to accept, adopt, and utilize new knowledge-transfer activities.

Second, knowledge management is not just about transferring knowledge; rather, it is about fostering an organizational culture that facilitates and encourages the creation, sharing, and utilization of knowledge.

Third, project managers must merge several different organizational and professional cultures into one project culture that promotes effective knowledge management.

The identification of viable means of ensuring that knowledge is produced and diffused across project boundaries and throughout the organizational hierarchy is a very important issue for project-based businesses. This requires a thorough understanding of the complexities of the organizational and professional cultures that guide and motivate the people working in projects.

By Ajmal, Mian M,Koskinen, Kaj U