La Tahzan Wa La Khauf

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Today's organizations are facing challenges never before conceived because of the shift into the Knowledge era. This is undeniable in a global world that sees all man-made and even natural boundaries collapsing. With this comes the realization of the importance of "knowing what we know," and maximizing the use of knowledge that we may already possess. Furthermore, there is a need to expand what we know to create/discover Knowledge. In the business enterprise this is never more urgent as it has turned into a matter of survival. We seem to have lost all of our comparative advantage except for the Knowledge that we have.
The challenge is that existing "corporate knowledge" may not be centralized or apparent, often residing in many different places such as: desktops, databases, filing cabinets and in peoples' heads. All too often, companies duplicate work, time and effort because they either don’t know what they already have, or can’t locate what they need. In order to combat these issues, organizations need to know what their knowledge assets are and how to manage and make use of these assets to get maximum return.
Competitive pressures, and increased employee mobility, continue to reduce the size of the workforce and the knowledge "contained within". As corporations become more customer-centric, employee focus is switched from the formal knowledge of their functions to the informal knowledge of the who, what, when, how and why of the customer. There is a need to realign business processes with the need for new and dynamic kinds of knowledge, accessible at internet speed.
Thus, the adoption of an effective Knowledge Management System may be the single largest factor to sustainable competitive edge for today…and into the future.
So What is Knowledge?
While many would say things like "I have a Knowledge of ABC" where ABC could be Accounting or Mathematics or Biology etc., we do not normally speak of having Knowledge about Knowledge itself. While businessmen, engineers, accountants and others may have some ideas as to what Knowledge is, in truth, it is unfair to fault them if they do not know what exactly is the nature of Knowledge. We must realise that the study of the nature of Knowledge is the purview of Philosophy. It is only in Philosophy that students really delve deeply into Theories of Knowledge and explore questions such as what is Knowledge and how it is acquired in the subject area called Epistemology. It becomes important for us to hear what the Philosopher has to say even in a seemingly business and information technology-like field such as Knowledge Management for it would seem that Knowledge Management is not only multi-disciplinary but is in a very important sense rooted in Philosophy. Here, we would like to avoid the Philosophical debates of what is Knowledge i.e. whether it is Justified True Belief or whether Knowledge must be acquired through the process of falsification rather than verification and other epistemological contentions. We would simply point out that in Knowledge Management, the concern is not so much the outcomes of philosophical debates but more so about what exactly is being managed in what we term as "Knowledge Management". Rather, in Knowledge Management, Knowledge is to be seen in relation to Data and Information. I would thus make the following observations about Data and Information followed by my working definition of Knowledge I think is most suitable for the field of Knowledge Management:
• Data - Raw facts; numbers; simple attributes
• Information - Data in context thereby enabling construction of Meaning
• Knowledge - Information which is contemplated in the mind, thus internalised and subjectivised to be evaluated by one’s belief system, prior knowledge and experiences thereby affecting one’s decision making and thus actions
There appears to be no clear-cut demarcation between these three sense of what is known. What appears to be data to one may be information to another. The context is not in the data but may very well be arrived at by the one reading the data. And, what is regarded as information to one may be Knowledge to another. Clearly, central to the idea of Knowledge is the Knower and not some repository of data or information in the sense of a Database.
Can We Then Define Knowledge Management?
There are many definitions of Knowledge Management but many of these definitions are lacking in scope as well as in reflecting an understanding of the Philosophical nature of Knowledge. Here we define Knowledge Management as both a process and a field of study:
• Knowledge Management is a field of study which analyses how:
• Knowledge Management is a process whereby:
the usage of data, information, information technology, human expertise/resources, intellectual assets and other organisational resources are planned, organised, directed, controlled and co-ordinated harmoniously to enable efficient creation/discovery, acquisition, usage and flow of Knowledge such that relevant Knowledge is integrated into the business process and thus leveraged towards the achievement of organisational goals.
It is clear that this definition builds upon the traditional understanding of Management from the perspective of what Managers do (first explored by Koontz) i.e. that they plan, organise, direct, control and co-ordinate. However what is involved in Knowledge Management is of course, Knowledge. Also importantly, this definition is centred on the usage of data, information, information technology, human expertise/resources, intellectual assets, in short, all resources that constitutes Knowledge assets and its enablers. Importantly, this definition also covers primary Knowledge processes which are the creation/discovery, acquisition, usage and flow of relevant Knowledge. And finally, this definition also considers the integration of these processes into the running of the business to leverage organisational Knowledge to achieve organisational goals.
In the quest for better overall knowledge management systems and related performance objectives, corporations are devoting greater attention and detail to the subject of classifying the knowledge that drives them. While the technology associated with the knowledge management systems is important, the knowledge itself is paramount. The ability to conceptualize, classify and use/reuse the knowledge is the true core to any knowledge management system. This is what ontologies are about. While again, this is a subject explored very much earlier in Philosophy, the emphasis in KM is less about the philosophical discussions of the various Theories of Existence. Rather in KM, ontology focuses more on the conceptualisation and classification of what is to be Known and what is already Known for the establishment of database, data-mining as well as for easy information storage and retrieval.
A counterpart concept of "ontology" is taxonomy. The successful classification of Knowledge revolves around the creation of a sound taxonomy. A taxonomic system is like a small universe of ideas that fit together in a logical fashion. Taxonomies are the intellectual skeleton around which a knowledge management system is assembled. A sound taxonomy system is built by distilling human intellect and combining it with a good deal of discipline as well as the realities of the industry within which the organisation is operating.
Many may say that the old saying that “knowledge is power” has now been replaced by the saying that “sharing knowledge is the true power.” However, we need to go further. Empowerment in fact does not come from the mere possession of Knowledge nor from the sharing of Knowledge per se. Power comes from the possession of Knowledge coupled with the authority to act on what is Known. As mentioned, an organization’s Knowledge is one of its most important resources, and may be the organization’s best sustainable source of competitive advantage. It stands to reason that the organization that has developed or selected the technology vehicles to share and transfer Knowledge effectively stand a better chance to remain competitive for the long-term. But the key to Knowledge Management is leveraging Knowledge i.e. the proper usage of Knowledge for decision making and application.
However, Knowledge sharing is without doubt a significant start point not only because Knowledge sharing is about relationships between people but also that any individual can start sharing what they know immediately. In fact many are already doing just that even if in an unstructured manner. Thus in order to build effective Knowledge Management Systems, it is first necessary to identify the underlying factors that encourage or discourage knowledge transfer in organizations. Once knowledge transfer is understood in the organizational context, managers can develop and implement strategies to boost organizational efficiency through better Knowledge Management.
Collective web-based collaboration, facilitating the creation of dynamic learning communities that are focused and process-driven, will provide an organization with eminently more effective and cost efficient knowledge transfer. The results are predictable: a more skilled and competent work force that is aligned with corporate goals and initiatives.
The question remains, how? How do we manage Knowledge? As with P. Drucker, we can say that the term "Knowledge Management" itself is at best, a misleading term and at worse, even linguistically unfortunate. Confounding our understanding is the software providers who are too quick to paste the term KM onto their products even when KM is the least that these products can do. In 1999, I wrote an unpublished paper to clarify the matter. My approach is that we do not manage Knowledge per se. What we do manage is really the flow of Knowledge. To do this, there is a need to conceptualise a system i.e. a Knowledge Management System which shows how Knowledge flows in an organisation. What follows is a copy of the paper:

By Abdul Halim Abdul Karim
Much has been said about Knowledge Management. Simply put, it is how Management manages Knowledge but that is a truism that does not say anything. We however, could do just as bad if we attempt to understand Knowledge Management merely in terms of the so-called traditional functions of the manager such as planning, controlling, leading, etc. Such functions do not in any significant sense apply to the management of Knowledge.
How then do we approach Knowledge Management? All indications are that you approach Knowledge Management from where you stand. The philosopher, educationist, engineer, psychologist etc., begin in their own respective ways. In the Business Management perspective we need to begin with the "organization". Much like the organization chart, which is really a blueprint of how an organization is run, we need to conceptualize some kind of a blueprint or framework which approximates, at least on paper, a system by which Knowledge is properly managed.
Managers may not necessarily need to build a Knowledge System from scratch although that may be preferable in many cases. Instead, much of the processes involved in a Knowledge system may very well be in operation in a current set-up. It is just that these processes were not conceptualized and therefore not optimized as a part of a Knowledge system for Knowledge Management.
It is clear that the management of Knowledge necessitates a basic understanding of the nature of Knowledge, not necessarily in the deep philosophical (epistemological) sense but at least as much as how Knowledge is conceived and related to people and decision making. This is because, an integral part of Knowledge Management is the management of the flow of Knowledge. Significantly, Knowledge primarily flows through people (of course with the help of Information Technology). How do we manage this flow of Knowledge? This is a key question in the Management of Knowledge. It is commonly known that an organization that is able to effectively manage the flow of Knowledge would have a comparative advantage that matters in the new economy.
That Knowledge primarily flows through people, gives the false impression that People Management (Human Resource Management) would mean Knowledge Management or that Knowledge Management should be subsumed under Human Resource Management. This is a basic Knowledge Management fallacy based on the false assumption that only people can store information and that the flow of Knowledge equals to the dissemination of Knowledge. On the contrary, Knowledge Management is not only a "people" problem, it is also a "systems" problem. Or, arguably many would say that it is where "people" meets "system".
Here, it is necessary to distinguish between Data, Information and Knowledge. But we must also remember that such distinctions are not rigid for one can easily become the other in a given circumstance.
• Data - Raw facts; numbers; simple attributes
• Information - Data in context thereby enabling construction of Meaning
• Knowledge - Information which is contemplated in the mind, thus internalised and subjectivised to be evaluated by one’s belief system, prior knowledge and experiences thereby affecting one’s decision making and thus actions
In a Knowledge Management System which essentially tracks "Knowledge Flow", we need to remember that we are talking about a system where people meets information systems; data that are often stored morphs into information when put into a context. And information morphs into Knowledge when internalised and contemplated by a person such that it affects his/her decision making. Thus, when we speak of Knowledge Flow generically, we are also speaking about data and information flow and how one morphs into the other and vice-versa.
Furthermore, we must understand that the flow of Knowledge is much more than just a matter of dissemination. Beyond the traditional concerns of security in the dissemination of Knowledge, Knowledge Management is also involved in developing a wholistic system for the management of Knowledge flow. If Knowledge Management were to be a formal business activity there must be some kind of reference, some kind of framework that the Knowledge Managers can work from. We find here the need for us to conceive of a Knowledge System. A Knowledge System is a framework which guides Knowledge Managers not just about who should know what and when but also what kinds of Knowledge processes needs to be done, how and when.
The much-touted Knowledge explosion is arguably an explosion of pseudo-knowledge. This is true otherwise we would not need to sieve through and differentiate between Knowledge and plain falsehood. There is essentially a large pool of claims-to-knowledge. "Knowledge on-time" has always been emphasized when what we need is really "Relevant Knowledge on-time". A good Knowledge Manager must thus be able to identify relevant and useful knowledge from an ocean of claims-to-knowledge. This is essentially what data-mining is about. Importantly, given the speed of the knowledge cycle, we need to anticipate relevance. Indeed, it would be helpful to think of relevance of Knowledge as a continuum:

There is no gainsaying that such anticipating is difficult to do. Furthermore, what is remotely relevant yesterday may be crucial today. Deciding upon the relevance of knowledge also requires a wholistic understanding of the industry within which the organization functions. Organizations related in a (supply) chain for instance, might each have access to knowledge required and relevant to another. If you use DHL's services, it would "know" more about where your customers (and your competitor's) are and when would they receive their purchases than your marketing department. In addition, the relevance of knowledge depends upon the type of industry in which an organization is operating. Determining relevance of knowledge requires a good understanding of related industries; what one firm regards as relevant may be irrelevant knowledge by another. It is for these reasons that any Knowledge System must factor in the related Community of Practice. Indeed, it is often the case that it is the practitioners and not the managers who are able to anticipate the next big thing in their respective domains. They are the feelers to what may become relevant (or alternatively, redundant) knowledge in the near future.
Having in mind what can be accepted as relevant Knowledge and what needs to be discarded as irrelevant, the Knowledge Manager needs to further think of a way to codify what he has identified as relevant. It is in the old Sufi and Taoist wisdom that not all Knowledge can be expressed into words and figures. Not all relevant Knowledge can be codified even though the advancement of IT, developments in the fields of Computer Linguistics and Artificial Intelligence aim to codify everything under the sun. Still, the Knowledge Manager needs to be able to identify and use the latest in hardware and software technology which could be used to effectively codify as much relevant Knowledge as possible. Lotus Notes and Microsoft Exchange are really attempts at doing just that (and maybe more). The reason why such softwares are popular is because Knowledge Managers cannot directly manage uncodified Knowledge. Codification also involves categorizing and classifying knowledge for easy retrieval and as such, it is "IT intensive".
What about Knowledge directly created/discovered by the organization? The direct (or active) creation of Knowledge by an organization would presumably be carried out by the Research and Development Department. R&D is a specific organizational function. Processes involved in such a function are generically similar to processes involved in a Knowledge System. An example of these is the codification of Knowledge. A good R&D department would have in place, a system which would codify Knowledge as it is created, done for instance through proper documentation of findings and analysis. This is indeed one of the important aims of Knowledge Management; to have such a system organizational wide rather than just restricted to the R&D department. This is where a Knowledge System would help. This does not mean that an R&D is necessarily a microcosm of a Knowledge System. It is just that an organization would do well to look at how good R&D departments handle what they have always been handling, Knowledge.
Identifying relevant Knowledge and Codifying them are two examples of Knowledge Management processes. However, these processes need to be placed within a Knowledge System mentioned earlier. Arguably, the first step towards Knowledge Management is to analyze the workings of an organization and build a Knowledge System appropriate for it. What, however, does a Knowledge System looks like in theory? After much theoretical research and also some attempts at conceptualizing a Knowledge System for a firm in Kuala Lumpur, I have come up with a knowledge flow-chart which I am proposing to be a Model of a Knowledge System:


Firstly, we must understand that Knowledge flow is very unlike the flow of tangibles. Water also flow i.e. from a higher plain to a lower area. Indeed, when a thing is said to flow from point A to point B, that thing cease to be at point A as it is transferred to point B. This does not apply to Knowledge. When person A shares his/her Knowledge with person B we may say that that particular Knowledge has been transferred from A to B but, A still retains the Knowledge he/she has shared. (Hence while Knowledge that is not relevant and not codified is seen above as going back to the Community of Practice, it in fact never left it - Uncodified (Tacit) Knowledge always resides in the minds of the people who make up the Community of Practice and it is also these members who would also know if a particular Knowledge is irrelevant or obsolete) Our understanding of Knowledge flow begins with experience for it is from experience that we learn and gain Knowledge. This can be seen to be worker's experience from all levels of the organisation. Also, through our exchanges with a Community of Practice, we learn from other's experiences. These experiences are in short, claims to knowledge for not all in our interpretation of the collective pool of experience are true and can be regarded as Knowledge. This is because, other than hearsay, we have differing perceptions which affects the accuracy of our understanding of our own experiences. Furthermore, not all the claims to knowledge are relevant for industrial or domain specific organizational decision making.
There is thus a need to identify Knowledge from a pool of claims to knowledge. There are claims to knowledge which are not Knowledge at all and so must not be allowed into the system. There are knowledge which are not relevant for the purposes of the organisation which should also not be allowed into the system until the organisation or the Community of Practice which would inevitably review these knowledge claims, find use for them at a later time. Not all knowledge thus identified as relevant, however, can be codified. Knowledge that resists codification cannot be managed by any Information System in the traditional sense of the word. rather, these are to be managed by other more human-centred Knowledge Management Initiatives that facilitates sharing of Knowledge such as the use of live face-to-face story-telling. Indeed, Story-telling is one way to facillitate Knowledge Flow within the Community of Practice. As such, a Knowledge Management System manages Knowledge Flow in the sense of it flowing through people as well as in the sense of it flowing through Information Technology and Communications Systems. Nevertheless, the knowledge that can be codified needs to be codified.
Codification is crucial for storage of data/information/knowledge into some kind of Data Bank. We can safely assume that knowledge directly created through Research and Development is codified and therefore could be channeled to the Data Bank directly. Such a Data Bank in turn must be sophisticated enough to be accessible to those who require the Knowledge. This is done through a system of on-time dissemination of Knowledge.
Thus, Knowledge is disseminated to those who need it to make decisions. Carrying out such decisions, i.e. applying such Knowledge in turn becomes a part of our experience that we in turn bring to our respective Communities of Practice. Notice the double headed arrow between Communities of Practice and Experience. And so, the chain of Knowledge flow goes on
The above model of a Knowledge System is generic in the sense that it is not focused upon any particular type of industry. As such, even though I mentioned above that "a Knowledge System is a framework which guides Knowledge Managers not just about who should know what and when but also what kinds of Knowledge processes needs to be done, how and when". The "who" and "how" is not detailed here as it is context or industry dependent. Incidentally, the technical "how" of Knowledge Management processes comes more so under the purview of the Knowledge Engineer than the Knowledge Manager. The chart above is thus meant to be a first blueprint of a Knowledge System to be used by Knowledge Managers in formulating a Knowledge System for any organization.
If you have any feedback about the Knowledge System Model please e-mail the author at


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"To Sharing Islamic Knowledge With Muslims In The World"