Business Processes and Knowledge Management

INTRODUCTION

Knowledge has been a subject of interest and enquiry for thousands of years, since at least the time of the ancient Greeks, and no doubt even before that. “What is knowledge” continues to be an important topic of discussion in philosophy.
More recently, interest in managing knowledge has grown in step with the perception that increasingly we live in a knowledge-based economy. Drucker is usually credited as being the first to popularize the knowledge-based economy concept, for example, by linking the importance of knowledge with rapid technological change in Drucker (1969). Karl Wiig coined the term knowledge management (hereafter KM) for a NATO seminar in 1986, and its popularity took off following the publication of Nonaka and Takeuchi’s topic “The Knowledge Creating Company” (Nonaka & Takeuchi, 1995). Knowledge creation is in fact just one of many activities involved in KM. Others include sharing, retaining, refining, and using knowledge. There are many such lists of activities (Holsapple & Joshi, 2000; Probst, Raub, & Romhardt, 1999; Skyrme, 1999; Wiig, De Hoog, & Van der Spek, 1997). Both academic and practical interest in KM has continued to increase throughout the last decade.
In this article, first the different types of knowledge are outlined, then comes a discussion of various routes by which knowledge management can be implemented, advocating a process-based route. An explanation follows of how people, processes and technology need to fit together, and some examples of this route in use are given. Finally there is a look towards the future.


BACKGROUND

Types of Knowledge: Tacit and Explicit

Nonaka and Takeuchi’s topic (1995) popularized the concepts of tacit and explicit knowledge, as well as KM more generally. They based their thinking on that of Michael Polanyi (1966), expressed most memorably in his phrase “we know more than we can tell”.
It is, however, most important to realize that tacit and explicit knowledge are not mutually exclusive concepts. Rather, any piece of knowledge has both tacit and explicit elements, as shown in Figure 1. The size of the inner circle represents the proportion of tacit knowledge: the “tacit core” at the heart of the knowledge that we “cannot tell”. Figure 1(a) shows a case where the knowledge is almost entirely tacit, as in riding a bicycle. Figure 1(b) shows mainly explicit knowledge, where the tacit core is very small, for example, how to process a claim for travel expenses in an organization. Figure 1(c) shows an intermediate case, such as making a piece of furniture, where substantial amounts of both tacit and explicit knowledge are involved.

Figure 1. The relationship between tacit and explicit knowledge

The relationship between tacit and explicit knowledge

The Role of KM Systems

KM systems represent a deliberate, conscious attempt to manage knowledge, usually in an organization. Hansen, Nohria, and Tierney (1999) identified that there are two fundamental KM strategies, codification and personalization. Codification concentrates more on explicit knowledge (often relying very heavily on information technology), personalization more on tacit knowledge. Again, it is important to realize that these are not mutually exclusive, and that a strategy combining elements of both is likely to be the most successful.

ROUTES TO IMPLEMENTING KM

Many organizations have found it difficult to implement knowledge management systems successfully. Identifying “who”, “what”, and “why” – who is involved in knowledge management, what knowledge is being managed, and why is it being managed – can be problematic. The routes they have attempted to follow can be put into five generic categories, which will now be described.

Knowledge World Route

A substantial amount of the literature on knowledge management addresses knowledge at the level of the whole organization, or in a “world of knowledge” that is not specifically linked to the activities that a particular organization carries out. On an abstract level, such discussion of knowledge management can be extremely valuable. However, it has weaknesses in terms of practical implementation. For example, it is necessary not only to understand how individuals learn, but also how they learn in a given organization, and how the organizational systems may help or hinder the individual’s learning process. The same issue applies even more forcefully to group learning, since the organization provides a crucial element of the group’s context.
The practical focus in Nonaka and Takeuchi (1995) was very much on knowledge creation. As a result, organizations attempting to follow their principles for other aspects of KM, such as sharing or retaining knowledge, have sometimes found it difficult to make a specific connection from abstract ideas about knowledge to what the organization actually does, or could do, or should do.
Often only the “why” is present, not the “who” or even the “what”. Something more concrete is needed.

IT-Driven Route

This route assumes that the fundamental requirement is for the codification of as much knowledge as possible. Advocates of this approach sometimes refer to this as “extracting” the knowledge from the people who possess it; see for example Johannsen and Alty (1991). This is an inadvisable term to use, for two reasons. First, it is logically incorrect; their knowledge is being shared, not extracted. The people still have the knowledge after the “operation” has taken place. Second, it gives the people the wrong impression – that their knowledge is being taken away. This is not a recipe to encourage their cooperation. For an organization of any size, such a codification task evidently requires IT support, and the thrust of this route is that once the “correct” form of IT support for managing knowledge has been chosen, it is simply a matter of a great deal of hard work.
This technology-driven route only works well in a limited range of situations where the “what” questions are most important, for example, where the main KM task is managing the knowledge held by a company in the form of patents. In other circumstances, it may not achieve any improvement in knowledge management at all. One example of this from the author’s experience is of a heavy manufacturing firm. Knowledge management in this organization was seen solely as an information systems issue; the KM group was part of the information systems department. The “solution” was seen in terms of the implementation of a knowledge sharing system based on Lotus Notes . However, there was no real consideration as to who would share what knowledge or for what specific purpose. Consequently, the eventual use of the installed IT was poor; the only really successful use was by the knowledge management project team itself, where the “who” and “why” questions had been properly addressed, as well as the “what” questions.

Functional Route

An alternative route that has the potential to address the “who”, “what” and “why” questions is to organize the implementation around the existing organizational structure. The most commonly found structural elements intended to facilitate learning and knowledge sharing in organizations are departmental groupings based on functions. These have clear advantages in terms of what might be termed professional development and allegiance. Davenport and Prusak (1998) report examples of successful knowledge transfer between groups of surgeons, and groups of tunneling engineers, among others. However, this functional route also has the disadvantage that it encourages the compartmentalization of knowledge. This problem can only worsen over time, as specialisations multiply and sub-divide. In addition, professional divisions can actively prevent sharing of knowledge. It has, for example, taken decades for hospital doctors in the UK National Health Service to allow other professionals such as pharmacists and physiotherapists to participate in decision-making about treatment of individual patients on an equal footing. On a wider scale, modern Western medical science has come to separate “diet” and “drugs”, at least until the very recent past, in a way that Chinese medicine, for example, never has done. The problems of running an organization in this manner, and the “functional silos” mentality that tends to result, were recognized by authors such as Hammer (1990) as part of the business process re-engineering movement, when KM was in its infancy.
Therefore, although the functional route to implementation will allow some improvement in KM, progress may be limited by the characteristics of the existing structure, and in the worst cases (for example, where transferring knowledge between functions is the greatest KM issue in the organization) this route may be counter-productive.

People-Centric Route

A people-centric route to KM is the essence of the Hansen et al. (1999) personalization strategy. By definition, such an approach, appropriately implemented, will answer all the “who” questions that might be involved in KM. Thus in organizations where there is general consensus on “what” knowledge is important and “why” it needs to be managed, such a route should prove effective.
However, as was mentioned in the previous sub-section, organizations have become increasingly diverse in their activities, and in the range of specialized knowledge that they need to access. This means that consensus even on what knowledge the organization has, never mind what is important, may be difficult to achieve. On the one hand, it may not be easy for a particular specialist to fully appreciate “what the organization does”. Equally, even the most conscientious senior manager will find it literally impossible to understand all the expertise and knowledge possessed by the specialists in his or her organization. To repeat the quotation from Hewlett Packard CEO Lew Platt (Davenport & Prusak, 1998, p. xii), “If HP knew what HP knows, we would be three times as profitable.”

Business Processes Route

The managers in an organization have to translate the goals of any strategic program or initiative - whether on knowledge management or something else – into practical, implementable reality. In other words, to connect with “what the organization does”. Various management thinkers have presented models of this, for example:
• Porter’s (1985) value chain,
• Earl’s (1994) view of core processes, the ones that are done directly for external customers,
• Beer’s (1985) “System Ones”, the systems that make the organization what it is,
• Core competences/competencies as espoused by Hamel and Prahalad (1994).
Although there are some significant differences between them, their common theme is that the effectiveness – indeed, the competitive advantage – of organizations depends not on how they are structured, or on what resources they have, but on what they do. In the terminology of this article, this means their underlying business processes. Note that the term business processes is used throughout, but such processes exist equally in not-for-profit organizations.
Business processes possess five characteristics that justify their use as a foundation for knowledge management in organizations.
1. Business processes have identifiable customers, whether internal or external. Knowledge is of little relevance unless put to use for a customer of some kind.
2. Business processes cut across organizational boundaries. Knowledge does not need to, and does not, obey the artificial boundaries within an organization.
3. Business processes consist of a structured set of activities. Choosing the appropriate way to structure activities is an important part of the knowledge.
4. Business processes need to be measured. Without some form of measurement as a comparison, knowledge cannot be validated.
5. While the parts of a business process are important, the overriding requirement is that the overall process works. Valid knowledge in an organizational context must take a holistic view.
An additional argument (Braganza, 2001) is that viewing knowledge management in terms of an organization’s processes gives a much-needed demand-side view of knowledge. This is complementary to the supply-side view of knowledge that stems, for example, from considerations “of data leading to information leading to knowledge”. Beer and Earl particularly concentrate on this demand-side perspective. Beer indeed goes even further, to include the informal processes and activities of the organization as well as the more formalized ones.

Figure 2. People, processes and technology in a KM system

People, processes and technology in a KM system
Completing this argument for a greater use of the business processes route, the knowledge that an organization requires must, logically, be related not just to what that organization does, but also to how it does it. Thus, people in organizations should think about this knowledge, and how to manage it, by reference to that organization’s business processes.

PEOPLE, PROCESSES AND TECHNOLOGY

From the earlier discussion, it may be seen that, whichever route is chosen, effective KM requires the consideration of both tacit and explicit knowledge. The need is to coordinate people, processes and technology successfully. The interaction of these three elements is shown in Figure 2.
Not only does a knowledge management system consist of more than technology, it is important to realize that the technology used to support KM does not have to be “KM software”. Recent studies have found that generic software such as e-mail or an Intranet may be at least as important as specific software (Edwards, Shaw, & Collier, 2004 (to appear); Zhou & Fink, 2003).

KM BY A BUSINESS PROCESSES ROUTE

As it has so far been less frequently attempted than the other routes, some examples of organizations that have implemented KM by a business processes route will now be given.
Unisys (Wizdo, 2001) have embarked upon a company-wide knowledge management initiative with an explicit process focus. Its objectives include:
• Accelerating the speed and scope of organisational learning,
• Decreasing the time it takes to reach critical mass in new markets,
• Uniting cross-boundary groups,
• Increasing innovation in product and process.
Wizdo identifies three increasingly ambitious categories of “transformation” in business: efficiency, innovation and re-invention. The Unisys knowledge management program regards a focus on processes as essential in achieving the two “higher” categories.
Objective Corporation (Fisher, 2001) changed most of their processes over a period of some five years. They found that such an emphasis not only improved knowledge management within the business, but also had a significant impact on the performance of the business itself. In this case, it was most likely the effect of a coherent training programme, with an emphasis on understanding, increasing the overall organisational performance through the people involved operating more effectively.
Both of these examples involved substantial use of information technology. However, that does not have to be the case. The author’s group has been working with a component manufacturer in the aerospace industry, whose KM initiative also has an explicit process focus. Typically, their manufacturing processes use a machine operated by one person. The operators’ choice of the best way to retain and share knowledge does not use IT at all (except for a word processor). The agreed best operating procedure, with illustrations, is put on a laminated sheet of paper mounted near the machine, which includes the names of the people who had contributed to designing the procedure. A suitable pen is provided to annotate the laminated sheet. At regular intervals, office staff come round to produce a revised version of any of the “Standard Operating Sheets” that have been annotated.

FUTURE TRENDS

A further justification for the use of business processes as the foundation for implementing knowledge management is that they are now becoming part of the mainstream of management thought. For example, the latest version of the ISO9000 family of standards for Quality Management Systems, including ISO9001: 2000, is constructed on the basis of a “process approach”. The ISO9000 term realisation process is equivalent to Earl’s core process or Beer’s primary activity as discussed earlier. Significantly, the latest editions of strategic management text topics (Johnson & Scholes, 2001) typically discuss the business process view of organizations, whereas earlier ones did not.
It seems clear, therefore, that the business processes route to implementing knowledge management is likely to become more common in future, and that this will encourage the development of ever more appropriate information technology for supporting it. Equally, new information technologies will enable new types of process. Intelligent agents, smart cards and “picture phones”, for example, all offer different possibilities for supporting KM which have only just begun to be considered.

CONCLUSION

This article has considered the implementation of knowledge management systems by looking at five different generic routes towards achieving it: knowledge world, IT-driven, functional, people-centric and business processes. While each of these routes has some merits, it has been argued that the business processes route offers potential for the greatest integration between knowledge management and “what the organization does”. It is, thus, likely to be increasingly common in the future.

KEY TERMS

Business Process: A structured, measured set of activities designed to produce a specified output for a particular customer or market (Davenport, 1993, p. 5).
Business Process Reengineering: The fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service and speed (Hammer & Champy, 1993, p. 32).
Demand-Driven View of Knowledge: A view of knowledge stemming from the requirements of the organization; for example, what knowledge is needed to carry out a particular activity and how can it be applied?
Explicit Knowledge: Knowledge that has been (or can be) codified and shared with others.
Knowledge Management: Supporting and achieving the creation, sharing, retention, refinement, and use of knowledge (generally in an organizational context).
Knowledge Management Software: Software specifically intended for knowledge management, such as data mining and “people finder” software.
Knowledge Management System: A combination of people, processes and technology whose purpose is to perform knowledge management in an organization.
Supply-Driven View of Knowledge: A view of knowl-edge stemming from the knowledge itself rather than its uses. Often related to a continuum data-information-knowledge.
Tacit Knowledge: Knowledge that is difficult or impossible to express, except by demonstrating its application.

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