Price, R. K.
International Institute for Infrastructural, Hydraulic and Environmental Engineering, IHE Delft, The Netherlands
Corresponding Address: P. O. Box 3015, 2601 DA Delft, The Netherlands
Telephone: 31-15-215 18 71
Fax: 31-15-212 29 21
E-mail: rkp@ihe.nl
Abstract: knowledge management is normally associated with business and commerce. however, the insights being gained by knowledge management in these areas are just as applicable to the water sector. the paper explores how knowledge management is relevant to water management, and how it complements hydroinformatics.
1 INTRODUCTION
'Knowledge management' is becoming in management circles what business re-engineering and total quality management were less than a decade ago. Perhaps it will follow the same path and be a 'seven day wonder'. But there is little doubt that it will leave a very significant impact on different sectors, not least the water sector. What knowledge management does is provide a rational for better management of knowledge, regarded increasingly as a collection of objects rather than something to be 'known' by the knower. This shift in cultural thinking has brought with it a whole series of implications for how we acquire, archive, analyse, generate, apply, share, assimilate and dispose of knowledge. In other words, there is a knowledge cycle (or knowledge value chain) associated with knowledge management. ICT forms a crucial role in helping us work with such a cycle and to apply it to our particular sector.
Hydroinformatics considers water systems from an information point-of-view. Yet we frequently make reference to the importance of knowledge. Much of this knowledge is associated with the accumulated experience of 'experts'. For example, we refer to software modelling systems as encapsulated knowledge systems; that is, they embody knowledge about the real world in terms of solving equations describing physical processes within well-defined geometrical domains. This is in contrast to data-driven modelling systems where the encapsulated knowledge is only concerned with the connection of different data sets, such as through (artificial) neural networks or fuzzy logic generators, and not with the physics of the processes. (This is not to say that a good physical understanding is needed for a successful application of data-driven modelling).
The knowledge we are talking about here is second-hand; that is, it has been made explicit, having originally been implicit, or tacit, in the sense of residing in somebody's mind or experience; see Fig. 1. Following Nonaka and Takeuchi (1995) we can say that, besides being encapsulated in tools such as modelling systems and decision support systems, knowledge is also encapsulated in (multi-media) documents. Indeed, documents containing text, drawings, etc are a standard way of transferring knowledge. Many published (and therefore 'quality assured') documents are stored in libraries, and we use the insights of information science to manage the information they contain. There are also many more documents containing knowledge and information, such as reports, manuals, papers, memos, even emails that never become archived within a library system. This grey literature (with minimal 'quality assurance') forms a very important part of the communication process between individuals and groups. Any document is evidence of the knowledge encoding process during which tacit knowledge has been made explicit. Similarly, when documents are brought together or tools are developed we can speak of a synthesising process.
Fig. 1 knowledge sharing (after Nonaka and Takeuchi (1995))
Often the preferred way of transferring information is through face-to-face communication using voice and body language (socialisation). This is especially true in forms of education or learning that depend on apprenticeship. Much learning, however, makes use of explicit knowledge, again in the form of documents and tools, in order for somebody to assimilate the associated knowledge into their world-view. Complementary to this form of learning is the apprenticeship system whereby a junior acquires tacit knowledge by working alongside an 'expert'. This form of learning has long been recognised in consulting engineers and other organisations.
Although we benefit from explicit knowledge in our individual learning process, it is also true that we are heavily dependent on each other. Learning is as much a group process as an individual process, and is also heavily dependent on accumulated knowledge of previous generations. In other words, we are all part of one or more communities, whether of interest, practice or intention. Engineers working within the urban water sector can view themselves as working in (long-term) communities of practice, while being temporarily assigned to virtual teams that have responsibilities for specific (short-term) projects.
The knowledge cycle that Nonaka and Takeuchi highlighted can be assumed to be a description of the status quo. However, the communication of knowledge from one part of the cycle to another has as its objective the transformation of existing knowledge from one form to another (as involved in the acquisition process) and the generation of new knowledge. Organisations today are increasingly aware that they have to pay more attention to how they manage their knowledge as their key asset. For example, although a water company may have significant underground and structural assets, their knowledge of those assets and their ability to manage and operate them efficiently may be more critical to their financial and perhaps commercial success. If this is so, the organisation will be vitally concerned to ensure that time and money are not wasted in 'reinventing the wheel'. In addition they will want existing knowledge to be acquired from both inside and outside the organisation. Again, innovation in knowledge generation should be encouraged at all levels, and a person's knowledge should be disseminated effectively to others, and so on. In other words, the organisation has as one of its primary objectives the efficient and effective management of the particular knowledge that is critical to its (business) focus.
The activities of generating and disseminating knowledge are nothing new to most areas of human society. However, the discipline of managing activities to do with human knowledge has only emerged as an important subject in its own right towards the end of the 20th century. This is in keeping with radical changes taking place in society as we move from a manufacturing to a service-based economy. Commercial organisations, in particular, are turning to better management of their knowledge assets as a means of re-engineering their businesses in order to survive the increasingly discontinuous changes in their markets. The knowledge economy is becoming a reality for the 21st century.
Hydroinformatics is now being seen as a socio-technological area of activity (Abbott (1999)). It therefore has to at least touch on how knowledge management is introduced into research and practice in the water sector. This is because knowledge management is as much about people and their social and cultural interaction as it is about their use of technological tools to address issues of understanding and managing water-based systems in the natural and urban environments (Price (2000)).
2 DEFINITION OF KNOWLEDGE MANAGEMENT
Plato defined knowledge succinctly as 'justified true belief' ; knowledge management for an organisation requires a longer definition:
Such a definition contains the essential elements of knowledge management that are perceived to be important for a organisation and reflects some of the latest published views on the nature and implementation of knowledge management in various sectors. There are dangers however, in even making such a definition in that it might unnecessarily constrain the corporate development of a concensus (ownership) on knowledge management. There are nevertheless, some important underlying issues that inevitably have to be addressed to secure the implementation of a suitable knowledge management process.
3 KNOWLEDGE SHARING AND COLLABORATIVE WORKING
Fundamental is a knowledge sharing culture that should pervade all activities of the organisation. Such a culture recognises that knowledge generation begins (and ends) with people. The principal challenge is to encourage and enable the sharing of tacit knowledge accumulated in the experience, understanding and beliefs of an individual that may be difficult for him or her to make explicit; see Fig. 1. Traditional working practices tend to limit such knowledge sharing. New organisational activities have therefore to be introduced through change management to facilitate the process of knowledge sharing, especially by creating an interaction between individuals grouped in communities of practice, by making appropriate use of advanced ICT facilities, and by providing adequate recognition and prestige to participants. These activities also encourage better, more efficient collaborative working, which is viewed as another essential process for the organisation.
4 INNOVATION AND LEARNING
Coupled with the cultural notions of knowledge sharing and collaborative working are the twin aspects of innovation and learning. Innovation is negatively about not 'reinventing the wheel' and positively about enhancing the natural capacity of human beings to be inventive. This is partly a psychological matter that can, for example, be approached using the coaching insights of Neuro Linguistic Programming (see, for example, O'Connor and Seymour (1993)), and partly a matter of adopting tools that replicate and complement the way in which the mind works, such as mind or concept mapping. Similarly, learning is now being recognised as a continuous, life-long process both for the individual and the organisation rather than a discrete, initial or even subsequent event. The organisation is a learning organisation in the sense that it builds objectively on its experience to accumulate further research insights and understanding to enhance the achievement of its objectives.
5 ROLE OF ICT
The importance of ICT in complementing knowledge management at the human level cannot be overestimated. Indeed, the rapid developments in ICT during the last 40 years have gone hand-in-hand with the corresponding cultural changes in society. The possibilities of almost instantaneous access to huge amounts of data, information and knowledge, to powerful search and data mining facilities, to sophisticated modelling, decision support and education systems, and to collaborative working networks, will radically affect the speed and efficiency of knowledge generation and dissemination. In turn, these will influence developments in working practices and social interaction.
Many countries world-wide are now developing ICT systems for knowledge management within different sectors. The European Commission regards the information society as a strategic concept for the future of Europe, and is therefore investing heavily in research and development in this area. There are also many other initiatives being taken in North America and the Far East to develop knowledge management systems. Most developments are being made in the commercial, health and education sectors; there are comparatively few reported in civil engineering sector.
6 CULTURAL DIMENSION
Enough has been said above to indicate that knowledge management has two important dimensions; see Fig. 2, which is due to de Vuijst (1998). The first is cultural and addresses how human beings can adopt ways of being and working that promote specific practices such as sharing, collaboration, innovation and learning. Knowledge management begins with the results of human thought and experience, and therefore with human culture. The second dimension acknowledges that we live in a digital world in which ICT is bringing about the 'death of distance' (see Cairncross (1997)) and is facilitating the handling of knowledge as a set of objects rather than something that has to be 'known' by the individual for its value to be appreciated. The cultural aspects begin with the difficulty of sharing knowledge as described above. For application of knowledge to be effective.
Fig. 2 Dimensions of knowledge management (after de Vuijst (1998))
there needs to be effective working together, or collaboration. If this can be achieved then there are distinct possibilities that innovation as a result of the sharing and collaboration becomes the norm. This puts the organisation in an attractive position vis-ŕ-vis the external market and its competitors.
Following de Vuijst (1998) we can also accept that for knowledge management to be effective there needs to be market 'pull'; that is, an expressed need and involvement by end users or stakeholders. Inevitably, this means that contractors, consultants and government bodies have to be involved in at least monitoring what is done, and preferably in participating at some level in the activity itself. Consequently it is argued that knowledge management in an organisation has to include the active participation of external stakeholders. Another reason in support of this conclusion is the rapid changes that are taking place in the application sector, as in every other sector. There is real danger that unless external stakeholders are involved the organisation would end up answering the wrong or even irrelevant questions. Necessarily the active involvement of stakeholders will come about through the knowledge management activities connected with the main business. It also means, however, that those responsible for knowledge management generally have to form strong links with the water sector, partly to determine the needs and opportunities within the sector, but in addition to involve those interested stakeholders in the generic aspects of knowledge management. In turn, this helps the sector to become more experienced in knowledge management. With the emergence of organisations providing advice and knowledge brokering it is important that interested stakeholders from the sector are involved right from the beginning.
7 'COMMUNITY OF PRACTICE'MODEL
The definition for knowledge management referred to above introduces the need for organisational processes that provide a means of sharing knowledge and working collaboratively together. From this statement emerges a model that consists of communities of practice, as mentioned above, (and possibly complemented by the concepts of communities of interest and intention). This is a group of people who have a common interest in knowledge relevant to a particular domain of activity. The group is essentially voluntary; that is, people join it because they want to rather than because they are required to. It also means that the group is self regulatory: there is a real sense of commitment by the participants to its success. Such groups are formed by those involved in research or practice within a typical urban water management organisation. A number of different facilities are provided on a particular platform to enable a community to function in an efficient and effective manner, and also to form strong links when needed with other communities of practice or external individuals. Each community of practice is constructed on a common generic framework but may include different types of facility, even some that may be tailored specifically for the particular community.
A community of practice platform may include some key facilities:
The implementation of such a platform can be achieved straightforwardly through an Application Service Provider (ASP) such as TopShare (see http://www.topshare.nl/), or through the installation on one’s own server of products such as BSCW (see http://bscw.gmd.de/), LiveLink (see http://www.opentext.com/livelink/) or DocuShare from Xerox Corp (see http://docushare.xerox.com/). IHE Delft has been testing TopShare as a platform for staff, participants, external lecturers and alumni. BSCW is being tested as part of the Delft Cluster research programme along with LiveLink. The latter product is being used as the basis for a knowledge management project that is exploring the transfer of knowledge on urban infrastructure between planners and engineers.
Knowledge management as a process can be measured through appropriate questionnaires. The focus of such a measurement would be on sharing of knowledge, collaborative working, innovation and individual and organisational learning.
Necessarily this discussion on knowledge management is applicable to organisations in many sectors, let alone the water sector. However, it is argued here that it is especially appropriate for the water sector on several grounds:
8 CONCLUSIONS AND END NOTES
Water management, like many other areas of engineering, is facing a number of far reaching changes through the introduction of new forms of ICT. Hydroinformatics is the study of how ICT can influence our understanding and management of water-based systems through an appreciation of the flow of associated information. Because information is a human concept and provides the building blocks of knowledge, it is inevitable that hydroinformatics should also be concerned with the acquisition of existing knowledge and the generation of new knowledge. Again this is a human activity which is augmented by the tools available from ICT. As such hydroinformatics must be involved with knowledge management.
This paper then has reviewed how knowledge management might help organisations concerned with urban water to improve their effectiveness. As hydroinformatics evolves it must therefore become immersed in knowledge management in all its aspects. It must be stressed however, that this is not so that it will lose its identity to the much larger sphere of knowledge management, but that it may retain its focus on utilising all (ethical) means at its disposal in pursuing the understanding and management of the world's waters. Discoveries and facilities from the area of knowledge management have the potential to improve our activities. Water-based organisations should therefore ensure that both hydroinformatics and knowledge management are on their agendas for the future.
References
[1] Abbott, M. B. “Introducing hydroinformatics, ”J. of Hydroinformatics, 01(1), pp.3-20, 1999
[2] Cairncross, F (1997) The Death of Distance. Harvard Business School Press.
[3] Nonaka, I. and H. Takeuchi, “The Knowledge-Creating Company,” Oxford University Press, 1995.
[4] O'Connor, J and Seymour J (1993) Introducing Neuro-Linguistic Programming, Thorsons Price, R K, (2000) Hydroinformatics and urban drainage: an agenda for the beginning of the 21st century. Proc. J of Hydroinformatics, IWA.
[5] De Vuijst, J. “Kennismanagement vergt externe trekkers,” in "Kennismanagement in de publieke sector," Elsevier, 1999.