Beyond first-generation KM

In the past, knowledge-management programmes have focused on knowledge as if it were simply a more complex form of information. Roderick Smith and Simon Burnett discuss the limitations of this approach, and outline the need to move towards a more balanced understanding of what knowledge is and how we should attempt to manage it.

One view of knowledge management has become focused on the definition of knowledge as complex information. The management of knowledge has subsequently been seen as an extension of information systems and the technologies they involve. But if knowledge is defined in relation to our understanding of information, there are clearly limitations with this view that need to be made explicit.

In this article, we consider why we might have adopted this view. The reasons are entirely understandable, but it could be said that in doing so we have knocked our approach to the management of knowledge out of balance. To redress this imbalance, we need to go back to a consideration of knowledge itself and what it means to manage it.

Any view or understanding of knowledge will determine how it is managed. For KM to be successful in the long term, the goal is to seek a balanced view of knowledge. In other words, we need a richer and deeper view of knowledge that can encompass its diverse characteristics if we are to identify how we might best manage it.

Knowledge organisation and information systems

We have been successful in managing information through the use of information and communication technologies and, given this, we have attempted to superimpose this success on the management of knowledge. Information systems, such as transactional processing systems, have supported business process re-engineering initiatives at an operational level. Management information systems, in attempting to specifically support less structured management decision making, implicitly suggest that the characteristics associated with decision making can be defined to the extent that a system can support this process. We have seen this idea extended to incorporate the likes of expert systems, which also claim to replicate less structured management decision-making activities.

The question that the process outlined above raises relates to the extent to which technologies can be applied to less structured activities. These activities can be associated with the need to apply judgement and intuition based on experience and it is here that knowledge management enters the equation. The application of information systems to the management of knowledge relates to the point at which we are able to break down an individual’s expertise into a number of qualifiers and place these within an expert system. This is knowledge as complex data.

Data, information and knowledge

Data, information and knowledge are often viewed in a hierarchy. Data can be defined as being an isolated element of information. Standing alone, it represents something but does not inform beyond this representation. Information integrates this data within an iterative process that produces information. Information, not surprisingly, should inform and support an action. ICT has supported this process superbly. It does not simply store data, it is also able to manipulate it in order to create information and, equally importantly, it can move this information around in an almost infinitely flexible way. From the information-management point of view, this has been a revolutionary step forward, at least to the point that ICT can accomplish things in a manner way beyond the capabilities of any individual. It would appear, however, that at some point within this iterative process of data integration we have decided that this informed data – information – is the same as knowledge.

Figure 1 – linear view of data-integration process supported by information systems

As figure 1 indicates, the iterative process of data integration illustrates the relationship between data, information and knowledge, and the information systems that have supported this process. It indicates that knowledge can or should be able to be broken down until it once again becomes data. All knowledge is, therefore, a more complex form of information, just as information is a complex form of data.

First-generation KM

This view of knowledge as a structured resource, which is essentially the result of a process of data integration, can be identified with what has been called first-generation KM. This view tends to emphasise the management of data. It brings to the fore data management, taxonomies and the application of ICTs through information systems. It is a popular view because it offers what organisations are usually looking for: a practical means of getting access to a valuable resource, in this instance knowledge.

Unfortunately, this view has placed limitations upon the knowledge resource, primarily because it has hindered the development of a richer and deeper interpretation of what knowledge is. The issue for practitioners in developing this understanding relates to the need to adopt a more reflective approach to the application of knowledge. It requires practitioners to operate in a context of uncertainty and one of constant change. Ironically, it is this context that initially underpinned the need for the management of knowledge. Change and the organisation’s need to respond to an environment of constant change was to be met by the creativity of the knowledge that is locked into the organisation.

This creativity, together with the ability to create knowledge, has been undermined in first-generation KM, primarily because it allows only a limited view of knowledge as complex information. To remedy this there is a need to re-visit the nature of knowledge itself and, in particular, to consider the ability of individuals and the organisation to create knowledge. In doing this we must, to some extent, be prepared to operate in a context of uncertainty where there is not necessarily an answer or a piece of knowledge waiting to fit a given problem. Rather, there is an element of faith involved in terms of how able individuals within an organisation are at coming up with an answer to a specific problem. In other words, can the individuals within an organisation act knowledgeably? The answer to any given problem, within this context, is not what is important, but how the answer is arrived at. Was it arrived at efficiently and effectively? Were the individuals involved able to identify the answer to the problem quickly and apply a creative solution to it? Underpinning this is not the certainty that is often sought in relation to organisational management. Instead, we must recognise that, at best, we have only a degree of certainty, not in the knowledge that we have, but in our ability to act knowledgeably.

In shifting our view of knowledge from knowledge as an identifiable resource to knowledge as an ongoing process, we re-present KM as knowledge creation rather than as knowledge organisation (or first-generation KM). As such, knowledge creation should be seen as the primary focus for second-generation KM. Figure 1 might now be altered to reflect this by identifying knowledge and data as each contributing to the overall information asset. In other words, explicit knowledge can become valuable organisational information and can indeed be stored, manipulated and moved by the organisation through the information systems that support this information asset. This process is also essentially first-generation KM, but the creation of knowledge is a separate and ongoing process that is in itself a valuable process. Figure 2 presents a less linear view of the relationship between data, information and knowledge.

Figure 2 – the information asset supported by integrated data and explicit knowledge: first-generation knowledge

Explicit knowledge is just one part of the overall information asset. In other words, rather than trying to present explicit knowledge as an expression of knowledge, we can simply call it information. Explicit knowledge is information. It can also be encompassed within the information system. This is the knowledge that can be identified with first-generation KM and that is often referred to as scientific knowledge.

Revisiting knowledge and second-generation KM

Not all knowledge can be made explicit, however. Why this is the case is largely related to the value inherent within second-generation KM and the reasons it is associated with the process of knowledge creation. As knowledge managers we need to have some awareness of the complexity and depth of the asset that we have called knowledge. The epistemological (theories of knowledge) debate is ongoing and highly complex, but the reason it is important to us on a practical, day-to-day level is because, whether we like it or not, we adopt theoretical perspectives that underpin the ways in which we act. If we look at this specifically from a KM perspective, we tend to take a very structured view of knowledge, viewing knowledge almost exclusively as scientific knowledge.

However, this is a limited view of knowledge. In particular, this identification of knowledge with the technology that is available to store, manipulate and move it around the organisation places the emphasis on the organisation of knowledge. This view suggests that taxonomies, supported by data mining and other powerful tools, will ultimately be able to manage the explicit knowledge of even the most intuitive of managers. It is easy to regard this as a strong position for knowledge managers to adopt, one that is supported by the ever-growing power of technology.

Indeed, this view is embedded into the western philosophical tradition, which is grounded in rationality and based on empiricism. Therefore, in adopting this view of knowledge as scientific knowledge, we align ourselves with a position that also appears to be entirely practical and almost common sense. In other words, knowledge can be defined through rational thought and can be shown to be true through empirical analysis. This is a strong position and to argue the contrary is not an easy task.

However, what if we do not accept that scientific knowledge fully represents the richness and depth of knowledge as a whole? This question is essentially about the nature of knowledge itself. Lyotard, in The Postmodern Condition: A Report on Knowledge, emphasises the limitations inherent in regarding scientific knowledge as representative of the totality of knowledge.[1] He goes on to talk about narrative knowledge, by which he is identifying knowledge as part of the way in which we, as individuals, communicate and express ourselves. This is often done through storytelling and other narrative-based means, and is a way in which we are able to justify and explain the positions or attitudes that we adopt. This needs to be seen as something more than just another means of gathering data and information through narrative means. Rather, it should be viewed as seeing knowledge not as a ‘thing’ but as a process. As Polanyi warns, “The declared aim of modern science is to establish a strictly detached, objective knowledge. Any falling short of this ideal is accepted only as a temporary imperfection, which we must aim at eliminating. But suppose that tacit thought forms an indispensable part of all knowledge, then the ideal of eliminating all personal elements of knowledge would, in effect, aim at the destruction of all knowledge. The ideal of exact science would turn out to be fundamentally misleading and possibly a source of devastating fallacies.”[2]

This identifies the unique nature of tacit knowledge. It highlights the thought that the process of making tacit knowledge explicit is itself based upon what Polanyi calls ‘objective knowledge’ and the belief that knowledge can meaningfully be defined in this way. But what if it cannot be defined in this way? Does this invalidate all that has been written and said about KM?

Far from it. Rather, it offers us an opportunity to reconsider the nature of knowledge and to appreciate the depth and richness of this resource. If first-generation KM is concerned with those aspects of knowledge that can be called scientific knowledge, then second-generation KM is concerned with what we might call narrative knowledge. In making this distinction there is no intention of valuing one type of knowledge over another. Ultimately, there is a need to place an appropriate value on these different characteristics of knowledge.

Balancing first and second-generation KM

If scientific knowledge has been the type of knowledge that much of the KM literature has, understandably, focused on, how might we redress this in relation to narrative knowledge? Essentially, we need to consider aspects of knowledge creation and how individuals create knowledge within an organisational context. This issue relates to how people learn and, while a huge subject in itself, is one that is crucial to this debate. It concerns how learning takes place and how it can be supported, facilitated and encouraged. This is the focus for what has been termed ‘organisational learning’. The goal of this is to develop the learning organisation, and the key to achieving this goal is to strike a balance between first and second-generation KM.

The goal of KM is therefore to create a learning organisation. It does this through the proper organisation of knowledge and through knowledge creation. Currently, we have a somewhat imprecise view of the elements that make up this balance, with an over-emphasis on knowledge organisation. This is primarily because this aspect is more firmly rooted in the view of knowledge as scientific knowledge that we are, or seem to be, more ready to adopt. Ironically, the identification of knowledge as a valuable resource is related to the need to move away from this position and recognise the importance of being able to respond within a context of rapid and continual change. To do so requires us to focus on our ability to act knowledgeably, rather than to seek to create stores of knowledge.

Figure 3 – a theoretical perspective of KM

Figure 3 identifies the consequences of adopting an imbalanced view of knowledge. On the one hand, if there were too much emphasis on scientific knowledge, there would be a focus on the principles of knowledge organisation. This has led to a technology-based view of KM with emphasis on information systems. On the other hand, too much emphasis on narrative knowledge would certainly create knowledge, but would neglect the mechanisms that are necessary to exploit it.

Balanced KM, as figure 3 suggests, is concerned with ensuring that we work with as rich and as deep an appreciation of knowledge as possible. In doing this we will ensure that we maximise knowledge creation and are able to fully exploit this creation through the effective exploitation of information systems. The view of knowledge as scientific knowledge – what we can now call first-generation KM – limits both knowledge itself and the purpose of information systems. For example, information systems can be applied to knowledge creation and can support organisational learning. Yet where knowledge is defined as scientific knowledge in isolation, the purpose of information systems reverts to a more traditional information-management model of data and information storage, manipulation and movement.

Moving forwards

The challenge for KM practitioners is to manage knowledge. To do so there is a need to appreciate the characteristics of knowledge. In the past, there has been a tendency to define knowledge as scientific knowledge. As a consequence, KM has focused on characteristics associated with knowledge organisation and first-generation KM. The theories of knowledge creation and second-generation KM define knowledge as narrative knowledge, or knowledge that is less structured and formal than scientific knowledge. In defining it in this way, we are able to highlight the importance of organisational culture and, in particular, learning. Each of these different views of knowledge requires a quite distinct form of KM. What we call KM today is essentially the management of scientific knowledge. If KM seeks to encompass all of the characteristics associated with both scientific and narrative knowledge, it needs to re-examine its current limited view of what knowledge actually is.

References

1.Lyotard, J-F., The Postmodern Condition: A Report on Knowledge(Manchester University Press, 1984)

2. Polanyi, M., The Tacit Dimension (Peter Smith, 1983)

Roderick Smith is course leader for the MSc in Knowledge Management at the Aberdeen Business School. He can be contacted at s.burnett@rgu.ac.uk