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Knowledge Management & Learning Organisation: Six of one and a half dozen of the other

Moving Beyond “Knowledge for Knowledge’s sake”

Quick ± in 25 words or less, define knowledge management. Can’t do it? You’re not alone.

    There are an assortment of disciplines that have influenced the field of Knowledge Management (KM) thinking and praxis – the most prominent are philosophy, in defining knowledge; cognitive science (in understanding knowledge workers); social science (in understanding motivation, people, interactions, culture and environment); management science (in optimising operations and integrating them within the enterprise); information science (in building knowledge-related capabilities); knowledge engineering (in eliciting and codifying knowledge); artificial intelligence (in automating routine and knowledge-intensive work) and economics (in determining priorities). As a result, there are enormous working definitions of KM and emergent philosophies circulating in the literature and around corporations of the world.

            One cannot get a clear understanding and definition of what KM is without studying the various concepts of knowledge and information (including data), as well as the tacit, implicit, and explicit knowledge dimensions. Much of the still existing confusion that surrounds the topic of KM is based on the varied scholars’ interpretations and suggestions distinguishing the terms information and knowledge as well as the terms tacit, implicit, and explicit.

 What is knowledge?

             Some authors appear to try to avoid the epistemological debate on the definition of knowledge by comparing data, information, and knowledge. However, von Krogh et al. (2000) or Kakabadse et al.’s (2003) understanding of knowledge as ‘justified true belief” goes back to Michael Polanyi’s original work (we know more than we can express) (Polanyi 1958), an epistemological position which is acknowledged to have grown out of Plato’s discourses (Meno, Phaedo and Theaetetus). This definition has been particularly adopted by Western philosophy (Nonaka and Takeuchi, 1995), which provides a comprehensive taxonomy of knowledge models, Plato’s concept was also debated from Aristotle, one of his students, throughout continental rationalism, as well as from German philosophy (Kant 1965; Marx 1976; Hegel 1977); British empiricism (Locke 1987) to twentieth-century philosophers (Dewey 1929; Sartre 1956; Habermas 1972; Tsoukas 1996; cited in Kakabdse et al. 2003, p. 77).

            The above discourse implies that knowledge itself is a very multifaceted concept with many different variations and definitions. Based on the fact that the nature of knowledge is widely acknowledged on differing epistemological stands taken from the individual contributors, but led ultimately to the following definition of ‘knowledge’:

            “Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organisations it often becomes embedded, not only in documents or repositories but also in organisational routines, processes, practices and norms.” (Davenport and Prusak 2000, p. 5).

Knowledge: Tacit/Implicit/Explicit

            ‘Tacit’ knowledge is not expressible and can in no way be made directly explicit or in other words codified into rules and formulations (e.g. the way a project manager behaviourally interacts or communicates during a conflict-solving process). In other words it has to do with an individual’s aptitude for doing things or even cognitively thinking about things.

            ‘Implicit’ knowledge is expressible and by applying appropriate knowledge management practices it has the chance to be made explicit. Thus, implicit knowledge is then transferred into explicit knowledge in a direct way. This process of transferring can be observed through the propagation, application, the amalgamation or the interpretation of explicit knowledge. Interestingly, from time to time, the terms ‘tacit’ and ‘implicit’ are used interchangeably..

            ‘Explicit’ knowledge is expressed implicit knowledge. There is enough evidence from the literature as well as from practice, suggesting that the two terms ‘explicit knowledge’ and ‘information’ have exactly the same meaning. In other words, explicit knowledge should be regarded as implicit knowledge, which when expressed becomes information. However, whereas the management of knowledge is mostly understood as the management of the processes, which can support the conversion of employees’ individual knowledge into overall organisational implicit knowledge, the management of explicit knowledge is understood as the management of knowledge-objects typically held as information in the organisation’s information base or systems in form of data records or documents.

The history of KM

            Knowledge management (KM) is currently receiving significant attention, from both academics and practitioners, and is being addressed by broad range of academic literature and popular press. The study of human knowledge has been central subject matter of philosophy and epistemology since the ancient Greeks and western philosophers. Eastern philosophers, Tzu and Confucius in China and their contemporaries in India, have an equally long and well-documented tradition of emphasising knowledge and comprehension for the conduct of spiritual and secular life. The first attempts at KM, such as capture, storage and retrieval, began with the Cuneiform language in about 3000 BC.

            A number of management theorists have contributed to the evolution of KM, among them such notables as Peter Drucker, Paul Strassmann, and Peter Senge in the United States. Drucker and Strassmann have stressed the growing importance of information and explicit knowledge as organisational resources, and Senge has focused on the “learning organisation,” a cultural dimension of managing knowledge. Chris Argyris, Christoper Bartlett, and Dorothy Leonard-Barton of Harvard Business School have all examined diverse aspects of managing knowledge. In fact, Leonard-Barton’s well-known case study of Chaparral Steel, a company which has had an effective KM strategy in place since the mid-1970s, inspired the research documented in her Wellsprings of Knowledge. 

            The 1980s also saw the development of systems for managing knowledge that relied on work done in artificial intelligence and expert systems, giving us such concepts as “knowledge acquisition,” “knowledge engineering,” “knowledge-base systems, and computer-based ontologies. Knowledge management-related articles began appearing in journals like Sloan Management Review, Organisational Science, Harvard Business Review, and others, and the first books on organisational learning and knowledge management were published (for example, Senge’s The Fifth Discipline and Sakaiya’s The Knowledge Value Revolution).

            By 1990, a number of management consulting firms had begun in-house knowledge management programs, and several well known U.S., European, and Japanese firms had instituted focused knowledge management programs. Perhaps the most widely read work to date is Ikujiro Nonaka’s and Hirotaka Takeuchi’s The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation (1995).

            By the mid-1990s, knowledge management initiatives were flourishing, thanks in part to the Internet. Knowledge management, which appears to offer a highly desirable alternative to failed TQM and business process re-engineering initiatives, has become big business for such major international consulting firms as Ernst & Young, Arthur Andersen, and Booz-Allen & Hamilton.

What is KM?

            Murray E. Jennex (2005) tells us that during a conversation he had with a fellow engineer, he made the comment that it was too bad we could not get back to the moon. Murrray, of course, agreed and expressed the desire that the government would allocate funds for it. His friend then surprised him by saying it was not money that was the issue but that what really prevents the US from getting back to the moon is that they do not remember how to build Saturn V rockets, Apollo capsules, and Lunar Modules. It seems after the end of the Apollo programme; management ordered all the plans put on microfiche and all but a few of the paper copies destroyed. This was done, however, when there was talk of going back to the moon and engineers went to retrieve the plans, the usable paper copies could be found, and everyone who knew how to build the rockets, capsules, and modules were either dead or retired. Additionally, when the younger engineers began to reverse engineer these components, they were stymied because they did not understand the technology from that time; technology had advanced so much that the engineers had not been taught some of the fundamental issues faced by engineers of that time. In other words, they had forgotten the knowledge from the experience of solving the problems that prevented moon flights.

            The above does in fact show that the space program is an example of failed KM. They attempted to store relevant knowledge but when it came time to retrieve it, it could not be retrieved and applied to the current decision- making activity due to media volatility and a lack of capturing the relevant context that makes the critical knowledge usable.

 Why do we need KM?    

            Why do we need knowledge management? We need KM because we need a proper process to help organisations identify, capture, store, and retrieve critical knowledge. We need KM processes to help organisations deal with changing storage strategies. We need KM to help us deal with the transience of knowledge workers. We need KM processes to help organisations manage a glut of knowledge. Ultimately, we need KM to help organisations make sense of what they know, to know what they know, and to effectively use what they know. The whole point of knowledge management (KM) is to make sure that the knowledge present in an organisation is applied productively for the benefit of that organisation.

            An organisation’s emergency preparedness activities might involve collaborative efforts between various entities. A vital activity is responding to an actual crisis situation that hits one or more of the member organisations/entities. For some organisations, responding to a crisis situation in done within a consortium environment. Managing knowledge across the various entities involved in such efforts is critical. This includes having the right set of information that is timely, relevant, and is governed by an effective communication process given such organisational structures, and the need to manage knowledge in these environments through effective Knowledge Management Systems (KMS).

            KM efforts typically focus on organisational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, and continuous improvement of the organisation. KM efforts may overlap with Organisational Learning and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and a focus on encouraging the sharing of knowledge. KM efforts can help individuals and groups to share valuable organisational insights, to reduce redundant work, to avoid reinventing the wheel per se, to reduce training time for new employees, to retain intellectual capital as employees turnover in an organisation, and to adapt to changing environments and markets.

 Implications of Global cultural diversity on KM

            Global cultural diversity has profound implications for the effective design and implementation of knowledge management (KM) projects. Thus, the view on global cultural diversity recognises the existence of different organisational contexts and great care must be taken when making assumptions about patterns of organisational performance and innovations (Avgerou, 2002). For example, the wide gap in the availability and use of ICT across the world, and the influences ICT exerts on globalisation, raise questions about the feasibility and desirability of efforts to implement the development of ICT through the transfer of best practices from Western industrialised countries to developing countries, and whether organisations can utilise such ICT in accordance with the socio-cultural requirements of the contexts (Avgerou, 2002).

            Reliable research concludes that diversity and local context does matter, and that the global techniques employed in western industrialised countries should not be implemented mechanically in developing countries without consideration for the local context. Further, gender considerations have been shown to be of great importance in the successful adoption of ICT.

The Arab region Knowledge Evolution

            Recently, there have been a couple of noticeable groundbreaking models pursued by Dubai and Qatar to transubstantiate the region’s population into a ‘‘knowledge society.’’ Both of these initiatives deemed human development a central goal and targeted narrowing the knowledge gap between the Arab region and the rest of the world. At the latest Middle East World Economic Forum, held in Jordan in May 2007, Sheikh Mohammed bin Rashid Al Maktoum, launched an endowment of ten billion US dollars for an avant garde foundation called the ‘‘Mohammed Bin Rashid Al Maktoum Foundation’’ to promote knowledge in the region.

            The second major initiative occurred in Qatar, where the government gathered leading world university representatives into a center for knowledge-creation called ‘‘Education City,’’ which is headquarters for the ‘‘Qatar Foundation.’’ The main objective is to form the most powerful educational and research hub in the Middle East.

             One of these efforts may lead to Beit Elhikma II or may produce distinguished geniuses such as Averroes (ibn-Rushd) (1126-1198), who created the first domestic and exotic knowledge hybridisation model that is not only admired, but also accepted, by Western societies. Averroes published his commentaries on Aristotle based on the epistemic fundament that ‘‘knowledge is the conformity of the object and the intellect.’’ The comeback of the Arab mind in a systematic ‘‘brain gain’’ program is needed as happened in India.

            To align the intellectual capacities with new business requirements, the region must work on different fronts to invest in expatriates, to leverage its strategies to reverse the ‘‘brain drain’’ and to fill the knowledge gap at both intra- and inter-regional levels. To keep the momentum of the ‘‘Knowledge Society” paradigm, the sustainability of the paradigm needs uninterrupted diffusion and infusion of innovations and continuously relevant knowledge, which may need restructuring at the organisational level.

            The chimera of ‘‘epistemic sovereignty’’ is an outmoded self-centeredness that is not acceptable in the current globalised marketplace. More pointedly, epistemological pluralism is required for success in the realm of the ‘‘knowledge society’’. A ‘‘co-opetitive’’ relationship is considered crucial to build the ‘‘knowledge society’’. The Arab world can revert from the status of ‘‘knowledge entropy’’ to the former ‘‘golden age’’ of Islam – if the principles of modern knowledge are effectively leveraged and crossbred with traditions to result in a lucrative ‘‘knowmadism’’.

Knowledge transfer and social capital: the case of Corporate Egypt

            Most of the knowledge related initiatives in Egypt have been at the country and community levels with limited emphasis at the organisational level. According to the World Development report for Africa, Egypt needs to work fast in order to increase its knowledge base, to invest in educating the people about knowledge management, and to take advantage of the new technologies for acquiring and disseminating knowledge. The report emphasises the importance of (1) instituting policies that enable them to narrow the knowledge gaps that separate poor countries from rich countries; (2) promoting collaborations among the organisations—governments, multilateral institutions, nongovernmental organisations, and the private sector—in order to work together; and (3) nurturing a knowledge sharing culture.

            A study performed on 41 public/private organisations in Egypt using Hofstede’s (1980) cultural dimensions highlights the need for a change in network relationships and efforts to build the relational dimension of social capital. While the structural and cognitive dimensions are already in place, the insubstantiality of the relational dimension and the focus on individual achievement are curtailing members from sharing their expertise. It is apparent that the lack of trust in getting credit for the information they share makes it hard for them to volunteer their expertise unless instructed to do so and unless they feel the risk of not obeying commands.

            It was concluded that the initiative has to start at the top in order for knowledge workers to have confidence in the system and to be able to cross the cultural gap between a knowledge-hoarding and a knowledge-sharing environment. The initiative must define several processes in order to enable the cultural transition. The study showed that the development of social capital as an infrastructure for knowledge transfer is a critical facilitator of knowledge transfer within organisations. Combining members’ knowledge resources can lead to collaborative knowledge creation that has the potential to limit the economic and knowledge gaps that exist within Egyptian organisations.


Knowledge sharing / lessons learned / storytelling


            U.S. Army has installed knowledge sharing as a standard part of its work in both training and real duty in the form of its well known after-action reviews. No effort is considered complete until it has been reviewed and its lessons obtained, including the lessons learned from failures.

            During the U.S. military efforts in Bosnia, lessons learned were distributed on a frequent basis. Because such observations as, “avoid snow-covered roads with no vehicle tracks, as they are probably mined” were credited with saving lives, members of other cooperating armies frequently requested a copy of the latest “lessons learned.”

            Openness builds confidence and sharing stories openly builds confidence in employees and in the organisation as a whole. This openness also leads to the development of trust that can support innovation. This is done by individuals using stories to build confidence in themselves, the direction of their team or the future of the company. In these cases the moral of the story could be “We did it before and we can do it again”, or “Look how bright the future can be.”

            Companies can further develop the organisation and its employees if people are given the opportunity to reflect on both the positive and negative realities of their workplace. Learning from each others past mistakes or successes through stories can build awareness, skill and confidence. The “glory days” tales or “war stories” you hear informally or formally throughout a company present learning opportunities without having to actually go through the experience. This is what NASA did to convey the culture of excitement around advancing space exploration to a young generation.

            Texas Instruments is a company that is extremely serious about encouraging re-use of ideas and design by its engineers. To encourage this process Texas Instruments periodically holds a contest within the company to collect the best story based on “We didn’t build it here but we used it anyway.” Teams within Texas Instruments scramble to come up with the best story on design re-use. They then share the story with others at an awards dinner. The stories and the activities of the company serve to foster their knowledge-sharing culture. In a well known example, Texas Instruments has achieved $1.5 billion in additional wafer fabrication capacity as a result of their knowledge-sharing program.

 Knowledge work and knowledge workers

            Early literature on knowledge work tended to take a Taylorist view, separating ‘thinking’ and ‘doing’ and comparing it with the fundamentally different but more familiar, type of manual work or blue collar work (Drucker, 1999; Schultze, 2000). Task performance within knowledge work cannot be compared with the sequential prescribed performance of manual work, by claiming that knowledge work is the exact opposite. Contemporary concept of knowledge work integrates doing and thinking and involves an uninterrupted cycle of re-use and creation of knowledge, which can be compared to a process of learning by doing. It involves a large amount of tacit knowledge (Schultze, 2000).

             A knowledge worker in today’s workforce is an individual that is valued for their ability to interpret information within a specific subject area. They will often advance the overall understanding of that subject through focused analysis, design and/or development. They use research skills to define problems and to identify alternatives. The term was first coined by Peter Drucker (1959), as one who works primarily with information or one who develops and uses knowledge in the workplace. Toffler (1990) observed that typical knowledge workers (especially R&D scientists and engineers) in the age of knowledge economy must have some system at their disposal to create, process and enhance their own knowledge. In some cases they would also need to manage the knowledge of their co-workers. Knowledge workers engage in ‘’peer-to-peer’’ knowledge sharing across organisational and company boundaries, forming networks of expertise.

 Knowledge Management (KM) Strategy

            Two philosophies for managing knowledge have evolved over the past decade. Firstly, the codification or explicit-oriented approach, which aligns strategy with information management efforts, such as embedding knowledge in documents, which can be stored and reused. Secondly, the personalisation strategy or tacit-oriented KM style emphasises the human and hence more complex part of tacit or implicit knowledge. Attempts to externalise and transfer this type of knowledge are based on communication strategies, both faceto- face and technology supported, by facilitating informal networks.

            Traditionally, organisations tend to focus on the tangible part of knowledge, introducing information and communication systems to capture and document knowledge, even though these efforts might never have been explicitly termed a ‘KM strategy’ or aligned with organisational strategy. In recent years, however, KM researchers have realised that human KM is the challenge, which has revived the notion of social networks.

            Some other knowledge management strategies for companies include:


 KM (CoPs) Strategy: A success story

            Communities of practice (CoPs) are designated networks of people who share information and knowledge. Community members exchange ideas, collaborate, and learn from one another in both face-to-face and virtual environments. For example:

            Caterpillar, Inc. is the world’s No. 1 producer of earthmoving machinery and a leading supplier of agricultural equipment. The organisation’s strategic driver for communities was just-in-time learning. In the past, Caterpillar employees attended in-class training on topics they might or might not find relevant to their daily jobs. By constrast, CoPs provide a platform through which employees can obtain timely answers to current issues or problems. Communities at Caterpillar are very narrowly focused in order to maintain a direct relationship between community activities and daily work. Communities are a way for Caterpillar employees to connect with the organisation’s global partners, customers, or teams in a virtual environment. Caterpillar currently has approximately 3,500 CoPs with about 40,000 unique participants. Approximately 7,000 Caterpillar dealers also participate in the organisation’s CoPs.

Knowledge management as “doing the right thing” (effectiveness) instead of “doing things right” (efficiency).

            The relatively stable and unchanging environment of the past allowed the luxury of predicting, pre-defining and pre-determining the future based on past data. Businesses could once define their business models, business practices and business value propositions – thereafter, the key challenge remained that of optimisation for increased efficiencies: of ‘doing things right’.

            However, changing customer trends, competitive products and services and changing societal and governmental pressures make the existing business models, business practices and business value propositions obsolete. Most of us are aware of the bloodbath in the desktop computer industry that eliminated many companies competing for business worldwide. However, some companies realised that the only performance outcomes that matter are the ones the customers really care about. They have been savoir-faire in tailoring and growing their customer value propositions around what the customers really needed rather than what they wanted to sell to customers. Dell has been an agile player that has been able to refine and play the game of ‘doing the right thing’ again and again, first in desktops and later in web hosting, printers, PDAs and storage. In the longer run, companies that can figure out the ‘next right thing’ and prepare well in advance to ride the next wave will be more effective in the longer run. However, it goes without saying that ‘doing the thing right’ also matters once you have figured out what the next cash cow will be.

            One central measure of organisational effectiveness is the creation and continuance of a measurable competitive advantage. Many broad initiatives such as efficiency, core competency advancement, actualisation of customer-centric products and services, and limitation of the fixed costs of doing business can help to achieve a sustainable competitive advantage within the marketplace. Thus, the effective management of knowledge understandably has the capacity to deeply impact the way a firm does business from the minor details of daily operations to the broadest strategic decision-making processes. 

Organisational Learning/Learning Organisation

            Argyris (1977) defines organisational learning (OL) as the process of “detection and correction of errors.” In his view organisations learn through individuals acting as agents for them: “The individuals’ learning activities, in turn, are facilitated or inhibited by an ecological system of factors that may be called an organisational learning system”.

            Huber (1991) considers four constructs as integrally linked to OL: knowledge acquisition, information distribution, information interpretation, and organisational memory. He clarifies that learning need not be conscious or intentional. Further, learning does not always increase the learner’s effectiveness, or even potential effectiveness. Moreover, learning need not result in observable changes in behaviour.

            Moreover, by taking the view of the organisation as a learning system, Senge contributed meaningful new insights. In his highly cited publication ‘The Fifth Discipline’ (1990) he argues that the organisations that will truly excel in the future will be the ones that discover how to tap people’s commitment and capacity to learn at all levels within an organisation. Senge believes that the ‘five component technologies’ are converging to create learning organisations: Personal Master – Shared Vision – Team Learning – Mental Models – Systems Thinking

            In his work ‘Disciplines of Organisational Learning: Contributions and Critiques’, Easterby-Smith (1997) argues against most scholars’ attempts to create a single framework for understanding and explaining the management of OL. By reviewing the most meaningful literature in the field he identified the following six disciplinary perspectives: psychology and organisational development, sociology, management science, strategy, production management, as well as cultural anthropology.

            Ang & Joseph (1996) contrast Organisational Learning and Learning Organisation in terms of process versus structure. They define OL as the ability of an organisation to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. However, the managers’ role in the Learning Organisation, Senge (1990) argues, is that of a designer, teacher, and steward who can build shared vision and challenge prevailing mental models. He/she is responsible for building organisations where people are continually expanding their capabilities to shape their future — that is, leaders are responsible for learning.

Implementation of KM: The Xerox Case

            Xerox was set out to be as educated as possible about knowledge management (KM). The organisation has spent considerable financial resources and time to codify the collective knowledge through its research, consortium work, and sponsorship of research.

            During a study on its representative’s behaviour, Xerox noticed that most of the causes of breakdowns in the machines they sold couldn’t be found in any of the firm’s record of cases.However representatives, thanks to their own knowledge and the knowledge they shared among each other during lunch breaks, were able to solve those problems.

            The solution, called Eureka project, was the creation of: An electronic database, in which they stored best practices, ideas and solutions; an intranet for representatives to make knowledge accessible to the whole company and facilitate the information sharing.

            The validity of the KM Eureka project’s implementation is strictly linked to the economic resources that it succeeds in recovering and saving up. In that perspective, the project Eureka made the Xerox Corporation save about the 5-10% on the job developed from the representatives and about $10 million on the cost of pieces or replaced machines.

Poor Knowledge Management can kill

            On September 30, 1999, a nuclear criticality accident occurred at a uranium processing plant operated by JCO Co., Ltd. (hereinafter referred to as JCO) in Tokai village, Ibaraki Prefecture. A solution of enriched uranium in an amount several times more than the specified mass limit had been poured directly into a precipitation tank bypassing a dissolution tank and buffer column intended to avoid criticality. This action was in contravention of the legally approved criticality control measures. Three JCO plant workers were exposed to high levels of radiation in the accident. This has resulted in the death of two of the workers making this an unprecedented nuclear accident in Japan which has developed nuclear energy for peaceful purposes.

            Except for what are sometimes called ‘Act of God’, any problems arising at a nuclear plant originate in some way in human error. However, unless there is a sufficient set of vulnerability causal factors and one or more triggering causal factors, neither an instance of human error nor a consequential event occurs. Based on the systemic analysis of the criticality accident, it was proved that its root cause was inappropriate knowledge management – combination of (1) inadequate risk awareness by the top management and (2) “kaizen” (production improvement) drives.


            Today’s more balanced view of KM is therefore a combination of managing explicit information resources as well as managing the working environment and people so that tacit knowledge is more readily developed, shared and exploited. KM is well beyond the “fad” stage – from previous surveys that showed two thirds of senior managers regarded KM as a fad, today it is recognised as fundamental and a contributor of value. It does add value to an organisation’s bottom line, and though difficult to prove directly, new measuring instruments have helped stakeholders identify the sources of value more clearly.

            KM becomes more pervasive, a knowledge ‘lens’ and KM perspective are being applied to wide range of management and business processes. Total quality management, customer relationship management and risk management are examples of where such approaches have given stakeholders new insights and methods improves through the fusion of existing methods with good KM practice.

            KM was very much a practitioner led discipline and only belatedly has the academic community caught up. However, there are now several business schools with active programmes of research. We are constantly learning more about KM in different contexts. KM is also considered a side-show until it is fully integrated into the strategic planning and decision processes of an organisation, which means the explicit recognition of knowledge, and KM in the corporate strategy and a clear articulation of its contribution to the business bottom line (including non-financial objectives).

            Both the literature on organisational learning and knowledge management has been growing over the past years. While OL primarily aims to identify the underlying processes of learning by clarifying critical issues like the content, agents and levels of learning, KM takes a proactive role of explicitly providing guidelines for active intervention into the organisation’s knowledge base. Both perspectives have their merits. OL provides a theoretical framework for analysing changes in the organisational knowledge base. This framework can be used to hypothesise and explain cognitive and behavioural changes within organisations over time. KM serves as a manager’s framework for improving the OL’s potential. By guiding managerial intervention into the organisation’s knowledge base, KM serves as a management tool of one of the most critical resources of organisational success.

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