Companies have always attempted to manage their knowledge, and have historically seen it as comprising the variety of skills, contacts and the general ‘nous’ that they had. So there is nothing new in the ideas behind knowledge management. However, what is new is that the volume of information has grown substantially in the last few years, and computer technology has developed to a degree which, in principle, should allow this information to be better handled. In addi- tion, communication is now much better, so that knowledge (if it has value) travels around more effectively, and the competitive advantage it gave is quickly eroded.
Certain established quality systems such as ISO 9000 attempt to con- vert the tacit knowledge of an organization into the explicit. ISO 9000 was created to help organizations reduce the failure rate in the delivery of a promised specification. Such failure was identified generally as arising from the inconsistent use of tacit knowledge used in the origi- nal meaning of the term (that is, literal information that was not as yet codified). ISO 9000 involves specifying the output desired (goods’ qual- ity), writing out all the procedures that are needed to be followed to achieve this specification, and installing tracking systems to ensure that the written procedures are followed. By ensuring that, for any given item, the procedures had indeed been followed, and by checking that the item met the specification, it follows that if on any particular occasion, it did not (that is, it ‘non-conformed’), then there must be something missing from the written procedures. A detailed investiga-
tion into the reasons behind the non-conformity therefore should allow for this missing procedure to be identified, and for yet another bit of tacit information to be made explicit, and hence the knowledge base of the organization to grow.
Total Quality Management (TQM) systems have been very effective in manufacturing environments, but although there is no reason these systems should not be just as effective in other environments, in prac- tice they do not seem to have been so. However, it is notable that the places where TQM has not been so effective are more likely to have tacit information of the modern conception (that is, conceptual infor- mation) than are manufacturing companies, where the older version of the meaning of tacit information (uncoded explicit information) is more likely to apply.
There are, however, some more fundamental and psychological reasons to explain the lower success rate in non-manufacturing environments. Arguably individuals do not want their particular knowledge to be made explicit as it reduces their perceived impor- tance and sense of personal identity within the organization. This is hardly a surprising phenomenon as it is a historically recognized way by which groups and guilds (now professional bodies) have preserved their distinctiveness and earning power. Unfortunately, these factors still seem to be undercurrents in moderating the effects of knowledge management systems.
Mechanical knowledge management
Management of knowledge (often abbreviated to KM) can take two forms. The first form is the elaborate ‘library route’ using computer-based systems to capture and help collate disparate pieces of information (both internal and external), and to automatically feed relevant information pointers to groups of people that the system has identified within the organization.
The sharing of information by common interest groups is an important aspect of knowledge management, and the very definition of these interest groups is itself an added advantage. This is because the members of these groups then know who in the organization has similar interests, and they can therefore directly contact each other when they are seeking the solution to particular aspects of their problems.
Although the creation of these computer-generated people networks is
an outcome of some of these systems, structurally they draw on the mechanical analogy of a spider’s web, rather than a more fluid ecological model to be described later. At their worst, these mechanical manage- ment systems are little more than a collection of databases with a search engine. Inevitably, this route involves very heavy IT investment, and they are generally manifest tangibly as a corporate intranet. However, their provision has again not seemed to bring the success that was hoped for. This may be because too much is expected from installing software that the providers strangely describe as ‘software solutions’, when logically this installation is only the first stage of introducing knowledge management systems into a company. In practice, it seems that such systems are information management systems, rather than real knowledge management systems.
Organic knowledge management
The second way of managing knowledge is cultural, and involves find- ing useful summarizing rules that are easy to identify with and to use.
Structurally this draws on ideas that have been developed in under- standing ecological systems, and can be thought of as being ‘organic’
rather than ‘mechanical’. There seems to be general recognition that the organic approach has to be present as well as the technological one in order to breath life into the sharing of knowledge, but it is, of course, much less easy and more time consuming to implement.
The whole of this area of knowledge management is difficult because it is all-encompassing and the boundaries of it are distinctly fuzzy.
There is, therefore, a danger that the notion of ‘knowledge manage- ment’ will become so diffuse and general that it ceases to have useful conceptual meaning. For this reason it is easier to think about separate knowledge domains, and in this book the area of particular interest is the domain that surrounds marketing.
Customer relationship management
As described in Chapter 1, some organizations take the view that their customers are their most important assets. At the ultimate level, this involves managing the relationship through monitoring customers’
behaviour at every point where they have contact with the organiza- tion, and supplementing this with additional information about them
wherever possible: for example, via list purchase, modelling and so on.
By these means, the organization attempts to construct individual mar- keting plans for each customer, with a view to retaining its customers or, preferably, taking more money off them in the face of competition.
This effectively means proactively engaging with the customer and being able to respond in a knowledgeable way when the customer has contacted the organization. Clearly, with all this codified customer behaviour on a database, it is possible to do clever analysis – but see Chapter 6 for the inherent weaknesses in this.
In this world, where customer information is taken seriously, it is to easy (but misguided) to imagine that information about customers comprises part of the knowledge of the company, and therefore cus- tomer relationship management systems and knowledge management systems are sometimes spoken of in the same breath. This can be par- ticularly the case when the customers are primarily other businesses (Adams, 2000).