Knowledge Management Systems: Surveying the Landscape

Transcription

1 FRAMEWORK PAPER Knowledge Management Systems: Surveying the Landscape R. Brent Gallupe, Queen s University Queen s University at Kingston, October 2000 Queen s Management Research Centre for Knowledge-Based Enterprises 1

2 KNOWLEDGE MANAGEMENT SYSTEMS: SURVEYING THE LANDSCAPE Abstract Knowledge management systems (KMS) are the tools and techniques that support knowledge management practices in organizations. The study of these systems consists of a small but growing body of literature. In the last two years alone, at least four books, two special editions of journals, and a number of academic and practitioner articles have been published related to this area. However, much of the work that has been published has been in the form of isolated survey studies, or anecdotal case studies into particular aspects of KMS. This has made it difficult to build a cumulative body of knowledge into the development, use and management of these systems. The purpose of this paper is to survey the current landscape of KMS, and provide a framework for research into the development and use of these systems in organizations. The intent is to highlight areas where gaps exist in what we know about knowledge management systems and suggest ways to close those gaps. Keywords: knowledge management systems, knowledge tools, knowledge technologies 2

3 INTRODUCTION Knowledge Management has become the new mantra of modern organizations seeking to compete in an increasingly turbulent and competitive world. It is becoming accepted that the only true competitive advantage for organizations over the long term is knowledge: that is, how organizations create or acquire knowledge, how organizations retain and store knowledge, how organizations disseminate and use knowledge, and how organizations protect and manage the knowledge they have. All organizations need and use knowledge. Whether they are private or public, big or small, services, manufacturing or resources, every enterprise takes the knowledge embedded in its employees and its processes, and attempts to create value for itself and society. The degree of knowledge use varies from organization to organization but effective knowledge management, even for enterprises that seem to use little knowledge, has become an important management mandate. Knowledge management systems (KMS) are seen as the means to aid organizations in creating, sharing and using knowledge. In the past three years, firms have invested millions of dollars in these types of systems in order to create competitive value. The sustainable advantage that can be achieved by the effective and efficient generation, distribution and application of knowledge within an organization is not being lost on today s modern managers. In the last two years, an increasing amount has been written in a variety of subject areas about knowledge and knowledge management. What is clear is that research in this area is still in its infancy. Definitions of terms and concepts are many and varied. Frameworks, models and theories are being developed and are struggling to gain acceptance. Nowhere is this more apparent than in the area of knowledge management systems (Alavi and Leidner, forthcoming). Although still a young area, an increasing number of studies are being published examining issues related to the development, use and management of knowledge management systems. In general, most of these studies have either been conceptual studies that define terms, studies that identify important issues (where the researcher(s) survey practitioners to determine what they feel are the key issues in this area), or anecdotal case studies that have described a particular development of a knowledge management system (Davenport and Pruzak, 1998; Germeraad and Morrison, 1998). A survey of the knowledge management system literature indicates that there appears to be no systematic framework guiding KMS research. It appears that current KMS research is being driven by temporal, hot issues in the field and not by a structured approach to knowledge accumulation. What is needed is a general organizing framework for the study of KMS. In a sense, this framework could be thought of as an agenda for research into KMS. This agenda should help guide KMS research and challenge KMS researchers and practitioners to look at their field from a broad perspective. 3

4 The purpose of this paper is to provide a research framework that will help identify the gaps in KMS research and provide a foundation for future research. It is appropriate at this time to propose such a framework because, although research into KMS is just beginning, sufficient KMS research has now been conducted and published to show where important areas have been missed and potentially productive areas have been untouched. To do so, we survey and analyse all the major studies published to date related to KMS, apply them to the framework, and use the results of our analysis as a guide for future research. This paper is written from an information systems perspective. Research into information systems in organizations has been conducted for over thirty years. This field has made many contributions to what we know about planning, developing and using information systems. Knowledge management systems share many similarities with information systems and many of the tools and techniques of knowledge management are related to information systems. It is believed that the research conducted in information systems can inform the development and execution of research in knowledge management systems. The paper proceeds as follows. First, some concepts are defined to establish the context for a discussion of KMS. Next, a review of possible KMS frameworks is described indicating the appropriate application of the frameworks and why a research framework is needed. Next, the Framework for Knowledge Management Systems Research is described and the KMS studies are assigned to the framework. Finally, the Framework is discussed in such a way as to highlight areas where KMS research needs to be done DEFINITIONS: SETTING THE CONTEXT There is no commonly accepted definition of knowledge management systems. Most definitions refer to tools or technologies that support knowledge management. However, only a few provide a comprehensive definition of tools or technologies, or combine those definitions with explanations of how knowledge is systematically managed. Knowledge: In terms of defining knowledge management systems, a starting point might be the definition of knowledge itself. There are a number of definitions of knowledge in the literature but a working definition might be (knowledge)... is information combined with experience, context, interpretation and reflection (Davenport, 1998). Knowledge is thought to be of two types, explicit and tacit (Polanyi, 1967). Explicit knowledge is that knowledge that is codifiable and is capable of being stored in machines. Tacit knowledge is thought to be in people s head s and very difficult to codify and store in machines. KMS typically focus on explicit knowledge but increasing attention is being given to how KMS might support tacit knowledge capture and transfer. Knowledge can be defined in terms of the function it serves (from Zack, 1999). That is, knowledge may be declarative or descriptive in describing what something is. Knowledge may also be procedural or process-oriented in describing how something is done. Finally, knowledge may also be causal describing why something happens. Knowledge management 4

5 systems are attempting to support all three functional types of knowledge but the most predominant type appears to be declarative knowledge. Knowledge can also be described in terms of its specificity. That is, some knowledge is of a general nature that can be used as background or context for many situations. Other knowledge is more specific and applicable to only a very narrow context. Knowledge management systems again should be able to handle both types of knowledge. In summary, knowledge management systems must be capable of handling and securing knowledge. Knowledge is a real asset of the firm, and like any other asset, it must be managed effectively. Knowledge can come in a variety of types and formats, and serve a variety of purposes. Knowledge is considered an extension of information in that knowledge is embedded with context. This makes it more challenging to manipulate and manage in a systematic way than just information. Knowledge Management Systems: The second fundamental concept providing the basis for KMS is the systems concept. In general, a system is defined as a set of elements that interact to achieve some common goal (Webster s Dictionary, 1995). In terms of organizations, systems are typically composed of people, technologies and data/information. These components interact with one another for some specific purpose (e.g. product distribution system). Feedback and control are used to keep the system working in the way it is intended. In terms of knowledge management systems, the components of people (knowledge workers, managers, etc), technologies (manual and computer-based technologies) and knowledge itself, interact to comprise a knowledge management system. Feedback and control aspects of KMS are those processes that ensure the KMS is performing the knowledge management tasks intended. Knowledge management systems are defined as systems designed and developed to give decision makers/users in organizations the knowledge they need to make their decisions and perform their tasks (Davenport, 1998). These systems extend beyond the traditional information systems in that they must provide context for the information presented. Examples of some current computer-based systems that practitioners are calling knowledge management systems are some applications of Lotus Notes and intranets. Knowledge management systems are concerned with the management of knowledge in the organization. Essentially, management is the stewardship of a resource; that is, the generation or acquisition of that resource, the storing of the resource, and the caring, security and on-going support of that resource. Typically, most KMS s fulfil a number of these functions. A potentially useful way of looking at knowledge management systems is to consider three levels of knowledge management technologies (see Figure 1) (adapted from Sprague, 1970). In the Levels Model of KMS, Level 1 is the knowledge management tools. These are tools such as expert systems languages (e.g. EXSYS), database/document languages (e.g. Oracle Pl/SQL) or programming languages (e.g. C++) that provide the fundamental building blocks for a knowledge management system. Level 2 are knowledge management system generators such as Lotus Notes that can be used to build a variety of particular KMS s. Level 3 are the specific knowledge 5

6 management systems that have been built. An example is an auditing KMS built using Lotus Note to support auditors across Canada in their auditing engagements. Specific KMS can be built from KMS generators and/or KMS tools. In summary, knowledge management systems can be thought of as systems composed of people, tools and technologies, and knowledge that interact to provide knowledge to people in the organization who need it. Level 3 (Specific KMS) Figure 1: Levels Model of Knowledge Management Systems Specific KMS 1 Specific KMS 2 Specific KMS 3 Level 2 (KMS Generators) Generator A Generator B Level 1 (KMS Tools) Tool 1 Tool 2 Tool 3 Knowledge Management Tools and Generators: Knowledge management tools and generators are the technologies that are used to acquire, store, and distribute knowledge. As Ruggles (1997) notes, not all knowledge tools need be computer-based (such as a pencil and paper) but most modern knowledge technologies have some computer component. It is important to note the difference between knowledge management tools and information management tools. Tools for knowledge management should be capable of handling the richness, the content, and the context of the information and not just the information itself. There are a number of types of computer-based tools/technologies to support knowledge management in modern organizations (see Table 1). Table 1 Tools to Support Knowledge Management Systems Intranets Information Retrieval Programs Database Management Systems Private internet-based networks using Webbrowsers to share knowledge Tools to search corporate knowledge/data bases as well as external knowledge sources to provide access to a wide variety of knowledge Combine with intranets and information 6

7 network tools to provide a platform to build specific knowledge management tools Document Management Software Provide the means for capturing, storing, and distributing knowledge in the form of documents as opposed to discrete data Groupware Software and hardware that enables workgroups to communicate and collaborate. Groupware tools typically have features that enable groups to perform such tasks as generating ideas (create new knowledge) and reaching consensus Intelligent Agents Software programs that can filter out the knowledge that the user really needs. This may be particularly important in knowledgeintensive situations where particular knowledge sources need to be monitored. Knowledge-Based or Expert Systems Store the knowledge of experts in the form of rules or cases and then provide that knowledge to novices or other experts. Knowledge management tools are the basic technological building blocks of any specific knowledge management system. Individual tools can be combined or integrated to form a specific knowledge management system that performs particular functions such as knowledge storage and retrieval. Another specific KMS may be comprised of tools to generate ideas and share those ideas among a work group. Knowledge management generators are defined as those technologies that are self contained that can be used to generate or build a variety of specific KMS. These technologies typically consist of a number of tools such as document management, intelligent agents, and groupware that can be customized to the knowledge management application required. LotusNotes is an example of a knowledge management generator. It contains a number of knowledge management features than can be combined in various ways to make different KMS. In summary, knowledge management systems consist of people, knowledge, and knowledge tools or technologies. The Levels Model of KMS is a structural model of knowledge management systems that attempts to show how the components of these systems are related to one another. There are many types of knowledge tools available to build specific KMS. Most of the tools have their genesis as information management tools but, as knowledge has gained ascendancy as an important organizational commodity, the tools have been adapted to handle knowledge. KMS RESEARCH FRAMEWORKS Research frameworks have been used in a number of fields to guide research in those areas (Snow & Thomas, 1993, Thomas & Dewitt, 1996; Shaw, Gardner & Thomas, 1997). This 7

8 is particularly true of information systems. The information systems field has used research frameworks for the past twenty to thirty years in order to identify where research was being done and where research was not being done (Gorry & Scott Morton, 1971; Ives, Hamilton & Davis, 1980; Nolan & Wetherbe, 1981). Indeed, one of the main benefits of a framework is to establish boundaries around the phenomena being studied. Another benefit is the identification of the main components or sub-factors that make up the object under study so that relationships can be examined and new knowledge generated. Finally, one of the main benefits of these frameworks has been to identify the gaps in the knowledge that has been accumulating in that field. A good research framework provides an overall perspective for the researcher that may point to potentially important and productive research areas that have been under studied. These criteria for a framework should also be met for knowledge management systems. The framework should scope out what is, and what is not, a knowledge management system. The framework should identify the major components of knowledge management systems and the research conducted-to-date into those components. That is, it should be as inclusive as possible. A KMS framework should also indicate where potentially productive areas of research exist. A final criterion for a KMS framework is that it should attempt to provide the reader/researcher with a novel perspective on the object being studied. A number of research frameworks could be proposed to guide research into knowledge management systems. First is the General Systems Framework (Figure 2). This framework treats a knowledge management system as any other information system. These systems can be studied in terms of their inputs, processes and outputs. In other words, a systems approach can be used to provide a basis for research programs in KMS. For example, a research program could study the inputs to a knowledge management system (type, form, etc.). The advantage of this framework is, not only its simplicity, but also its inclusiveness. All major components for a KMS can be included in this model. The main disadvantage of this framework is that it doesn t highlight the importance of knowledge bases/repositories, or the critical nature of knowledge transfer between people. Figure 2: General Systems Framework for Knowledge Management Systems Inputs: Knowledge People Tools Feedback Process: Interaction of Knowledge, People and Tools Outputs: Useful Knowledge The second framework is the Four Component Model of KMS. This framework is based on the model of Group Decision Support Systems developed by DeSanctis and Gallupe (1985). This model shows a KMS as being made up of four components: a knowledge base or repository 8

9 subsystem, a user-interface subsystem, a group support or knowledge transfer subsystem, and the user/knowledge generators themselves (Figure 3). This framework shows the inter-relatedness of the main components of a KMS. It also highlights the importance of both the user of a KMS, both as a generator of knowledge and a user of knowledge. The main disadvantage is that it may not be detailed enough to highlight the areas where research into KMS may be productive. Figure 3: The Four Component Framework of Knowledge Management Systems Knowledge Base Management Sub-system Knowledge Communication Support Subsystem User Interface Subsystem Knowledge User/ Knowledge Generator A third framework is the Knowledge Life Cycle framework (Figure 4). This framework follows knowledge through the stages of its life cycle from creation to disposition (Ruggles, 1997, Liedner and Alavi, 1999). At each stage, knowledge management systems can be created and studied to examine their impact on knowledge within each stage. Research programs could look at KMS for each stage. This framework has the advantage of being conceptually simple in that KMS can be categorized and studied through identifiable stages. The main disadvantage is that it does not provide for the richness inherent in KMS and does not show where research might be lacking. 9

10 Figure 4: Knowledge Life Cycle Framework Knowledge Creation or Acquisition Knowledge Codification and Storage Knowledge Transfer or Dissemination Knowledge Use The final framework, and the one chosen for this paper, focuses on KMS to support knowledge management practices (Figure 5). This framework treats what organizations actually do (their knowledge management practices) as central to the framework and highlights the type and form of KMS that can support that practice. This framework incorporates the process and structures inherent in the General Systems and the Four Components models, respectively. In addition, it implicitly uses the Knowledge Life Cycle Model to help categorise knowledge management practices and uses of KMS. The Knowledge Management Practice framework is based on the work of Gray and Chan (1999). This framework examines knowledge management practices along two dimensions. The first dimension is the process to be supported (problem recognition or problem solving). The second dimension is the class of problem being solved (new or unique, previously solved). The integration of these dimensions results in four types of knowledge management practices that may be supported by KMS. We define problems in this context as desired states. That is, problems may be opportunities, threats or simply an undesired state that needs changing. The first type of practices are those that seek to identify new problems by encouraging creativity and the generation of new knowledge (talk rooms, chat rooms, brainstorming). Once problems 10

11 are identified they can be solved. The second type of practices are those to solve new problems by creating and storing knowledge related to these problems (communities of practice, knowledge forums). Once problems have solved, the knowledge to solve the problems needs to be stored. The third type of practices seeks to use knowledge to address previously solved problems (repositories, maps). Once knowledge has been stored for previously solved problems it needs to be transferred to others. The fourth type of practices involves transfer of knowledge to individuals to support problem recognition with pre-existing problems (formal and informal training). KMS and research into KMS should focus on what these systems actually support. Therefore, the research framework consists of Figure 1, the Levels Model of KMS, and the KM Practices Framework. These combined models scope the field and provide the potential to identify gaps in existing research. They also provide a novel perspective not seen in KMS literature to date. Figure 5: Knowledge Practices Framework for Knowledge Management Systems Class of Problem New / Unique Previously Solved Problem Process Problem Recognition Problem Solving Encouraging Serendipity (1) Knowledge Creation (2) Mentoring & Training (4) Knowledge Acquisition (3) REVIEW OF KNOWLEDGE MANAGEMENT SYSTEMS LITERATURE A review of the knowledge management systems literature was conducted in the Summer and Fall of A search was made for books, articles (in both academic and practitioner journals) and Web-based sites and material related to KMS. The books reviewed included those in the general knowledge management area as well as those in organizational learning. The knowledge fields that were searched included knowledge management, information systems, computer science, general management, and organizational behaviour. Key words used in searches on the Internet included knowledge management, knowledge management systems, knowledge tools, and knowledge technologies. The search resulted in the identification of over 15 books, over 40 articles (both academic and practitioner) and many Web sites that were related to knowledge management systems. Of these, 11

12 surprising few actually dealt with research into knowledge management systems. Most of what has been written about KMS s is descriptive. That is, they are either studies of what an organization has done (Ernst and Young, 1997) or a description of existing knowledge tools. Therefore, this review will consider selected descriptive articles as well as specific researchoriented papers. The following section describes the main literature to date in KMS and applies it to the KM Practices Framework. Encouraging Serendipity: KMS Support for Problem Recognition (Chat Rooms...) The knowledge management practices in this quadrant focus on problem identification through the generation and sharing of knowledge. Encouraging serendipity is the notion that knowledge can be created and shared to recognize new or unique problems. Practices in this quadrant are activities such as chat rooms, environmental scanning, and passive searching. KMS s to support these practices include online chat rooms, Web search engines and general messaging systems. Relatively little research could be found for knowledge management systems that support these types of knowledge management practices. General research could be found on the use of chat rooms, search engines and other computer-based tools but very little has been written that relates those tools to knowledge management practices. Most of what has been written in this area is usually part of articles dealing with the knowledge creation process in general rather than creating or using knowledge for the recognition or identification of new/unique problems. For example, Choo (1998) looks at how organizations create knowledge. As part of this knowledge creation process, organizational members seek to identify areas where knowledge might be created and used. Fruin (1997) examines knowledge management at Toshiba. Part of this knowledge management process are practices to encourage the identification and definition of new problem areas. Technologies to support idea generation are mentioned as being useful for these practices. A final example of work in this area is Leonard s (1998) description of group innovation using tacit knowledge. Innovation processes are tied to developing insights and serendipitous cognitions. Supporting the use of tacit knowledge with technologies is seen as a possible way to encourage innovation in organizations. Knowledge Creation: KMS Support for Problem Solving (knowledge forums/communities of practice): A growing body of literature characterizes this quadrant. The knowledge management practices in this quadrant address knowledge creation to solve new problems. That is, the problems have been identified and now knowledge is being created to solve those problems. Practices that are usually placed in this quadrant include knowledge forums, communities of practice, and structured brainstorming. KMS s to support these practices include computer-based discussion forums, management of online user groups and constrained electronic brainstorming. 12

13 There appears to be growing interest in ways to support knowledge creation practices in organizations. A variety of tools have been proposed and developed (such as electronic brainstorming tools and electronic discussion boards) to aid organization members in combining existing knowledge to create new knowledge to solve new problems. General research could be found on techniques such as electronic brainstorming and structured computer-mediated discussions but again, not as much was found that looked at these in the context of specific knowledge management practices. Much of what has been written in the area of technology support for knowledge creation for solving problems relates to general knowledge creation by individuals and groups in organizations. The most prominent thinkers in this area appear to be Nonaka and his colleagues (1994, 1995, 1998). Much of their work has been directed towards developing a conceptual foundation for knowledge creation in organizations. This foundation is partially based on systems to manage the knowledge that is created. Japanese social and management concepts are used to describe how communities, practices and systems can interact to create useful new knowledge. Other examples of work done in this area include Albert (1997), who looked at experts and knowledge creation (within the context of managing knowledge in organizations). Fulmer, Gibbs and their colleagues (1998) examined the impact of new tools on learning organizations and provided some insights on knowledge creation tools. Work by Inkpen (1996), although not directly focused on knowledge creation tools, discusses ways that technology can be used to create knowledge through collaboration. Ruggles (1997) in a working paper on knowledge tools describes and speculates on the possible knowledge creation possibilities of these tools. A final example is the work of Sparrow (1998). Knowledge creation and the systems to support new knowledge are viewed a high priority in organizations are to sustain competitive competencies. Knowledge Acquisition: KMS Support for Knowledge Codification and Storage (knowledge repositories/knowledge maps): This is the quadrant where most of the writing, research and development have been conducted into KMS s. This is reasonable since the knowledge management practices in this area seem to be the most appropriate for automation. The knowledge management practices in this quadrant deal with the codification, preservation and storage of knowledge. That is, they focus on organizing knowledge, extracting tacit knowledge to make it explicit, and designing schemes to store knowledge so that it can be easily retrieved. Practices in this quadrant are processes such as knowledge/data capture, developing knowledge maps and entering knowledge into document management systems. KMS s to support these practices include KMS generators such as Lotus Notes, and tools such as database management systems. Much of the research in this quadrant comes from the information systems/computer science areas (for example, Scott (1998)). Some comes from psychology and cognitive science (for example, Brezillion and Hakima (1995)) but most deal with the problems of coding and storing organizational knowledge. There are many descriptive reports (such as Gomolski, 1997; Gardner, 1998 and Martiny, 1998) but not as many scientific research studies as might be expected. 13

14 Many of the articles that have been written in this area have also considered technologies to support knowledge transfer as well as acquisition and storage. A few of the papers that have considered primarily the latter are described. First, Davenport and his colleagues (1998) have examined processes and knowledge management system projects in a variety of organizations many that focus on developing and populating knowledge repositories. Work by Gardarin (1989) on relational databases and knowledge bases might be considered before its time as it addressed some of the issues that need to be addressed in developing and maintaining large knowledge bases. A paper that has had considerable influence on practitioners and how they think about technologies to support knowledge codification is the paper by Hansen and Nohria (1999) that looked at strategies for acquiring, managing and storing organizational knowledge. Another article that looked at some of the challenges in using KMS s to store and use knowledge is by Hendriks and Vriens (1999). These authors argue that there is no single way to create electronic knowledge stores and that each knowledge management situation is unique is this regard. In addition, these more general views of systems to acquire and store knowledge, various disciplines have also looked at this issue including marketing (Madhavan and Grover, 1998), information systems (Marshall, 1997), and operations (Moore and Birkinshaw, 1998). In summary, this quadrant has seen the most descriptive and analytical research work related to knowledge management systems. The reason for this is the nature of the practices that these systems support. There has been a significant amount of interest by practitioners and researchers into the best ways to capture and store organizational knowledge. This is not surprising when these knowledge stores/repositories can cost millions of dollars and consume large amounts of human time and effort to design develop and implement. Mentoring and Training: KMS Support for Knowledge Dissemination and Sharing (formal and informal training): The knowledge management practices in this quadrant focus on problem recognition of previously solved problems. These practices typically involve transferring or sharing knowledge with others. The intent is that by disseminating knowledge to others in the organization, the potential to solve a problem that has occurred before will be greater. Practices in this quadrant include mentoring programs, formal training and education programs, and formal knowledge sharing incentive schemes. KMS s to support these practices include online knowledge yellow pages, systems to track knowledge sharing through company intranets, and custom-tailored, computer-based training systems. Research into technologies to support practices in this quadrant is relatively sparse. Most articles deal with knowledge/information sharing using knowledge system generators such as Lotus Notes or knowledge tools such as intranet development tools. Another subset of articles are descriptive articles that discuss the use of primarily human resources-based systems that are used to assign mentors, track knowledge or skill sets, and monitor knowledge use and sharing activities. Examples of work in this quadrant include a study of knowledge sharing at Buckman Labs by Buckman (1998). This case study describes a culture where information sharing is the norm and 14

15 mentoring and knowledge dissemination are rewarded. Odem and O Dell (1998) describe the case of Sequent Computer and how it uses its KMS s to publish knowledge. O Dell has also published other articles (1997,1998) that examine the transfer of internal knowledge and the practices and processes/systems that support this transfer. In terms of general guidelines and lessons learned in this area, Allee (1997) has developed a number of principles to guide the management of knowledge sharing and dissemination. In addition, Casselman (1998) provides some lessons learned in the use of intranets and knowledge management. Finally, Davenport and Prusak (1998) discuss how knowledge sharing systems might best be implemented in organizations and what incentive schemes, if any, should be developed to support the use of such systems. As in previous quadrants, most of the research is descriptive. Very few studies that investigate knowledge management systems use quantitative techniques such as surveys or field experiments. Most use case studies or conceptual argument to make their points. RESEARCH AGENDA AND CALL TO ACTION It is clear from the review of the literature on knowledge management systems that research into these systems is at an early stage. In other words, the research agenda is wide open for meaningful contributions. For practitioners, this means that most of the lessons learned are anecdotal and may only apply to the situation in which they are originally described. On the other hand, these well-reasoned, experience-based arguments and case descriptions are currently the best new knowledge we have about knowledge management systems. For researchers, this means that many important topic areas are under studied, such as knowledge creation systems, and that significant contributions can be made in those topic areas using a wide variety of research techniques. More will be said about this below. From the application of the literature to the Knowledge Practices Framework, a number of observations can be made. First and probably most importantly, this Framework has identified a gap in what we know about knowledge management systems. Very little research has been conducted into tools and technologies to support practices focusing on new or unique problems (the left side of the Framework). This is an area where knowledge management and KMS s have the potential to make the most value added. If competitive advantage is to be achieved and maintained by organizations, they must harness their knowledge and knowledge systems to identify and solve new and novel problems that will distinguish them from other organizations. Solving problems that have been previously solved by others is important but the gain is only incremental. Marshalling knowledge resources such as KMS s to solve new problems is revolutionary. The second observation, which is somewhat surprising, is that not much has been written or researched about knowledge sharing or using KMS s for training. Most general articles on knowledge management point to knowledge sharing practices and training as key success factors, yet little formal research has been conducted in this area. Again, this is an opportunity for 15

16 practitioners and researchers to determine the best practices in this area and implement them in their organizations. A third observation about the literature applied to the framework is that most of the research into knowledge management systems has been in knowledge codification and storage. Software companies who build knowledge/data base software have probably spurred this research on. As computer storage becomes less expensive, more and more explicit knowledge will be stored. Determining the most effective and efficient ways to capture, codify, store and retrieve knowledge from a knowledge repository will be an on-going problem that will engage researchers for many years to come. A second set of observations from the application of the Knowledge Practices Framework relates to the research methods used. When most fields of knowledge are in their infancy, they rely on conceptual articles and anecdotal case descriptions of use to help map the landscape. This is the case with knowledge management systems. Not only do we not agree on a definition for these systems, we have not yet developed a widely agreed upon method for categorizing or classifying these systems. It is hoped this paper moves the field along in this direction. It may be time for more rigorous studies into knowledge management systems -- studies that use accepted survey or benchmarking techniques; studies that use comparative empirical techniques such as field experiments. For example, it would be a contribution to see a rigorous benchmarking study into the best practices in KMS. It would be helpful to read about comparative case studies of organizations using similar KMS s. There is also a need for laboratory/experimental studies to examine the impact of different KMS interfaces on productivity, or to investigate the impact of different knowledge sharing incentive schemes on knowledge users. Finally, we don t know much about how KMS s fit into the larger context of organizations. For example, more work could be done on the impact of KMS s on organizational strategy. How are the benefits of KMS s measured? Also, relatively little research has been conducted into KMS development (using either tools or generators). What are the impacts on KMS developers and implementers? What are the impacts on knowledge users? These are questions that research into knowledge management systems could answer. CONCLUSION Although an increasing amount of research is being conducted into knowledge management systems, there is much work to do. This paper uses the Knowledge Practices Framework to classify and describe the major research that has been conducted into these systems up to this time. The Framework is intended to be a practical guide for practitioners and researchers in the study and use of KMS. The Framework has identified gaps where more work is required 16

17 (knowledge creation and sharing). It has also identified an area (knowledge acquisition and storage) that is relatively strong and where practitioners can access useful knowledge to solve some of their knowledge storage problems. The application of KMS literature also indicates the limited range of research that has been conducted into these systems. Case studies and anecdotal descriptions are well represented but more field studies, surveys and experimental studies would add value to the field. Finally, if knowledge management systems are to continue to have a positive impact on organizations, more study will be needed to assess the effects of these systems on the organization as a whole. We need to understand how these systems affect people and strategy. We need to determine the best practices in the assessment of the benefits of these systems. To quote an anonymous CKO (Chief Knowledge Officer): We know relatively little about Knowledge Management. We know less about Knowledge Management Practices, and we know almost nothing about Knowledge Management Systems. I sometimes wonder why I am called a Chief Knowledge Officer when I don t know anything!! 17

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