On the Convergence of Knowledge Management and Groupware Sajda Qureshi1, Vlatka Hlupic2, and Robert O. Briggs3 1 Department of Information Systems and Quantitative Analysis College of Information Systems &Technology University of Nebraska Omaha, The Peter Kiewit Institute Omaha, NE 68182-0392 squreshi@mail.unomaha.edu 2 Brunel University, Department of Information Systems and Computing Uxbridge, Middlesex UB8 3PH, UK Vlatka.Hlupic@brunel.ac.uk 3 Delft University of Technology, The Netherlands CMI, University of Arizona, USA 85721 bbriggs@groupsystems.com Abstract. As successful organizations recognize that they need to convert their intellectual resources into customized services, the value of electronic collaboration has increased. Current efforts in managing knowledge have concentrated on producing; sharing and storing knowledge while business problems require the combined use of these intellectual resources to enable organizations to provide innovative and customized services. This paper argues that knowledge management and collaboration have common, mutually interdependent purposes and practices. It develops a framework that demonstrates this interdependence, mapping collaboration technologies to knowledge management activities. It concludes with a call for the convergence of these two streams for the benefit of researchers, practitioners, and organizations. 1 Introduction Organisations increasingly see their intellectual assets as strategic resources that must be harnessed and managed effectively to achieve competitive advantage and to survive. An organisation’s intellectual assets consist of the knowledge held in the minds of its members, embodied in its procedures and processes, and stored in its (non)digital media that could be useful for achieving its strategic ends [26]. It is or the sum of everything everybody in a company knows that gives it a competitive edge [22]. With its strategic intellectual resources, an organisation can minimise its costs, create innovative products, improve production procedures, improve quality, respond to dynamic market conditions, and improved customer service. The effective performance and growth of knowledge intensive organisations requires integrating and sharing knowledge that is otherwise highly distributed [26]. Distributed knowledge is often personalised, residing in isolated pockets and communities within and outside of the organisation. It has been suggested that problems which stem from traditional business environments that hoard knowledge is an obstacle which is preventing knowledge management efforts from being a complete sucG.-J. de Vreede et al. (Eds.): CRIWG 2004, LNCS 3198, pp. 25–33, 2004. © Springer-Verlag Berlin Heidelberg 2004 26 Sajda Qureshi, Vlatka Hlupic, and Robert O. Briggs cess [11]. In addition, Vance [24] suggests that the reason information and knowledge may not be easily transferred from the holder to the person needing it may be because much of it is tacit, ingrained in the holder’s mind, but difficult to articulate. Nunamaker et al., [16] and Qureshi et al., [18] suggest that an organisation’s potential to create value through the use of its intellectual capital is a function of the extent to which people can understand data, information, knowledge, and wisdom, and can collaborate. Technologies for knowledge management may enable improved capture and conveyance of understanding that might otherwise be inaccessible in isolated pockets; technologies collaboration may enable communication and reasoning among people who use knowledge to create value. It may therefore be that a convergence of knowledge management and collaboration technologies could increase an organizations ability to create value with knowledge. Developments in collaborative technology are increasingly focusing on technology for geographically distributed teams. This means that instead of bringing groups together in a meeting room equipped with computers, people can accomplish some kinds of tasks online in virtual workspaces. This type of electronic collaboration has become a powerful means of capturing, exchanging, exploiting, and managing knowledge. In this way, electronic collaboration becomes instrumental in capitalising on an organisation’s intellectual capital. This paper is to bring together key concepts in groupware and knowledge management to develop a framework that demonstrates the interdependence of knowledge management and collaboration. The framework may also provide guidance to researchers and practitioners seeking to tap into diverse, yet disparate knowledge resources. This framework may be a useful basis for developing or choosing groupware tools specifically designed for knowledge management activities. 2 Methodology To develop the framework, we examined groupware literature: 1) that had wellgrounded theoretical foundations; 2) that had rigorous empirical findings, and 3) that explored pragmatic, practical organizational applications. We analyzed the knowledge management literature to identify the basic activities to which knowledge management technology was applied. We then mapped modes of collaboration to the knowledge management activities, and mapped collaboration onto the intersections of collaboration and KM to illustrate how these technologies might improve KM performance. We focused on practical application of groupware and knowledge management activities; philosophical and theoretical notions of knowledge were beyond the scope of this paper. 3 Knowledge Management in the Context of Collaboration The concept of knowledge management (KM) is still in its formative stages. Until recently, the KM literature tended to have strongly technical focus [23] More recently, researchers have begun to focus not only on knowledge management (KM) technology [e.g. 2,7, 17,20], but on the human practices and activities of knowledge management. [e.g. 9,10]. At this point, different KM authors use the same terms to label different concepts, and different labels for the same concept. Nonetheless, common understandings of On the Convergence of Knowledge Management and Groupware 27 KM activities have emerged. For example, according to Angus and Patel [1], knowledge gathering refers to: • bringing in of information and data • organising related concepts to ensuring that the knowledge is easily accessible by giving it context through linking items to subjects • adding value to knowledge by identifying new relationships, abstracting, synthesising and sharing. Yet Kramer [13] limits the concept knowledge gathering to the process of collecting knowledge, and posits knowledge organizing as a separate concept that involves classifying knowledge to give it meaning so that it can be easily located by those searching for it. Kramer [13] defines knowledge distribution as yet another separate KM activity. Nonetheless, there is significant overlap in the concepts identified by these and other authors. Table 1 synthesizes generic KM activities from exemplars in the literature on KM practices. These are defined as follows: • Create. Develop new understandings and procedures from patterns, relationships, and meanings in data, information, and prior knowledge. • Collect. Acquire and record knowledge in a medium from which it can later be retrieved. • Organize. Establish relationships among knowledge items through synthesis, analysis, generalization, classification, or affiliation. Create context so that collected knowledge can be easily accessed and understood by those who need it. • Deliver. Grant access to people who should have access to knowledge, while blocking access to those who should not. Search for and share knowledge. Present knowledge in a medium and format that minimises cognitive load while maximising understanding of those who need it. • Use. Bring knowledge to bear on a task that creates value for an organization. Table 1. Knowledge Management Activities identified in KM literature Source Synthesis of Literature Ruggles [19] Angus and Patel [1] Kramer [13] FerranUrdaneta [6] Jackson [12] Knowledge Management Activities Create Collect Organize Generation Codification Gathering Organizing/ Refining Gathering Organizing Creation Legitimisation Gathering /Storage Macintosh [14] Developing Preserving Synthesis Deliver Use Transfer Disseminating Distributing Sharing Collaboration Dissemination Communication Sharing The KM literature tends to conceive of the activities in Table 1 in terms of individuals interacting with a KM system. Yet, each of the activities corresponds closely to activities used by teams to achieve their mutual goals. It is therefore likely that collaboration could improve KM activities, and that KM could improve collaboration activities. Indeed, it may be that collaboration activities and KM activities are the same. 28 Sajda Qureshi, Vlatka Hlupic, and Robert O. Briggs Nunamaker et al. [16] suggest that “we are moving towards an age of any time any place collaboration”. Fuelled by the exponential growth of the Internet, the World Wide Web, and local area networks, there are various communication technologies that enable this flexible form of collaboration. These include combinations of electronic mail, real time conferencing, and multicast audio and video used to support, for example, internet-based concerts and presentations [8, 21]. Any time any place collaboration can also be achieved through information sharing technologies such as digital whiteboards, computer bulletin boards and threaded discussion groups, document management systems that provide for the creation and reuse of documents as well as the control of access, concurrency, and versioning [5,25]. Such suites of collaborative technologies are now in use in organizations and universities around the world. Such advanced collaboration environments can be used for multiple tasks that cross temporal, spatial and social distance. 4 Groupware for Knowledge Management Activities The generic activities of knowledge management are closely intertwined with collaboration concepts. Briggs & Vreede, [4] argue that regardless of task, there are five patterns of collaboration that generally characterize a team interactions: 1. Diverge: To move from having fewer concepts to having more concepts. The goal of divergence is for a group to identify or create concepts that have not yet been considered. The Generate KM activity would be an instance of divergence. 2. Converge: To move from having many concepts to having a focus on, and understanding of, fewer concepts worthy of further attention. The goal of convergence is for a group to reduce their cognitive load by reducing the number of concepts they must address. The Gather KM activity would be an instance of convergence. 3. Organize: To move from less to more understanding of the relationships among the concepts. The goal of organization is to increase understanding reduce the effort of a follow-on reasoning. The Organize KM activity is an instance of such a process. 4. Evaluate: To move from less to more understanding of the benefit of concepts toward attaining a goal, considering one or more criteria. The goal of evaluation is to focus a group’s discussion or inform a group’s choices. 5. Build consensus: To move from having less to having more agreement among stakeholders on courses of action. The goal of consensus building is to let a group of mission-critical stakeholders arrive at mutually acceptable commitments. There is substantial correspondence among the patterns of collaboration identified by Briggs and Vreede [4] and the KM activities identified in this paper. Diverge has to do with brainstorming and idea generation, and corresponds closely with Create, which has to do with generating new knowledge. The Converge and Organize collaboration patterns correspond closely to the Organize KM activity. The Evaluate and Build Consensus patterns may be part of the Organize activity, and would clearly be part of the Use activity, as would all the other patterns. Briggs [3] argues that there are three cognitive processes underlying group interactions: communication, deliberation, and information access. Communication refers to conceiving, delivering, receiving, and decoding communication stimuli. These same cognitive processes underlie the Deliver KM activity. Deliberation refers to goaldirected thinking and reasoning, which is congruent with the Organize and Use KM activities. Information access refers to finding, acquiring, and coming to understand On the Convergence of Knowledge Management and Groupware 29 information. This is the essence of the Gather and Organize, and Deliver KM activities. Given that KM technology is mean to communicate knowledge and information in support reasoning Nunamaker et al. [16] suggest that there are three modes of collaboration that may be made more effective through the use of various collaborative technologies: 1) collective effort, people work on their own and group productivity is simply the sum of individual efforts; 2) coordinated effort, people make individual efforts, but productivity depends on the level of individual effort and on the coordination among those efforts; 3) concerted effort all members must make their effort in synchrony with other members and the performance of any member directly affects the performance of the other members. The generic KM activities can be conducted in all of these modes. Further, people working in all these modes require knowledge to support their deliberations that they could derive from KM technology. Support for co-ordination among individuals carrying out a collaborative work process requires a different combination of technologies than do concerted collaboration efforts. Collaborative (or group) task is defined as the behaviour requirements needed to accomplish stated goals (i.e. create value), via an explicit process, using given information [27]. 5 A Framework of Interdependence for KM and Collaboration Various authors have suggested taxonomies for the classification of groupware applications and products; see e.g. [5,8,15]. This section presents a framework based on those taxonomies to demonstrate the interdependence of KM and Collaboration. The framework achieves this purpose by mapping collaboration technologies to KM activities against several dimensions of collaboration. Because the framework is multidimensional, it is presented here as a series of tables. Table 2 maps collaboration technologies to KM activities by mode of collaborative work. The first column of the table lists the five generic KM activities synthesized from the KM literature in Table 1. The top row of the table lists the three modes of collaboration. Each cell of the table contains exemplars of one or more collaboration technologies that that could be used by teams in the work mode represented by the column to support the KM activity represented by the row. Table 2. Collaboration technologies mapped to KM activities by Collaborative Work Mode KM ACTIVITIES Create Collect Organize Deliver Use COLLECTIVE Individual Productivity Suites (e.g. MS Office) Individual productivity suites (e.g. MS Office), team document repositories Statistical analysis packages, spreadsheet, database queries. Team document repositories, shared workspaces All of the above COLLABORATIVE WORK MODE COORDINATED CONCERTED Web-based forms GSS brainstorming and convergence tools Team Database, Forms, GSS GSS brainstorming, discusdiscussion tools, Team Calenda- sion, and convergence tools, ring, Project management Simulation Modelling GSS Classification & outlining GSS Classification and tools, team calendaring, Project outlining tools Management GSS, on-line discussion Multi-user databases, notice tools, simulation and modelboards, newsgroups, E-mail, ling tools shared workspace All of the above All of the above 30 Sajda Qureshi, Vlatka Hlupic, and Robert O. Briggs Table 3. Collaboration Technology for KM activities organized by pattern of collaboration KM DIVERGE ACTIVITIES GSS BrainsCreate torming Tools; Online News Group; E-mail GSS BrainCollect storming tools, Online database forms Organize Deliver Use Statistical analysis packages, spreadsheet, database queries Document repositories, shared workspaces, All of the above CONVERGE ORGANIZE EVALUATE GSS classifica- Shared Outlines, Online Polling tion tools; Elec- GSS classifica- tools; Structured tronic polling tion tools discussion tools tools GSS classification tools, electronic polling tools GSS outlining tools, GSS classification tools GSS classification & outlining tools, team calendaring, Project Management Multi-user database, notice boards, newsgroups, E-mail, shared workspace All of the above GSS classification & outlining tools GSS, on-line Discussion Tools, simulation and modelling tools All of the above BUILD CONSENSUS Electronic polling tools, GSS assumption surfacing tools Online polling tools, structured discussion tools GSS polling & discussion tools used with goal alignment & conflict resolution methods GSS classification GSS classification & outlining tools, structured reading methods, tools used with clarification and simulation & review methods modelling tools Relevanceweighted AI Collaborative Query Tools (Quantitative and Qualitative) All of the above Collaborative query tools & GSS discussion tools used with argumentation & review methods All of the above Regardless of which KM activities a team performs, the activity will require that the team engage in one or more of the five patterns of collaboration. Table 3 illustrates the interdependence of KM and Collaboration by mapping collaboration technology to KM activity by the pattern of collaboration the technology can foster. Regardless of which KM activity a team performs, they must divide their limited attention resources among the three cognitive processes required for collaboration: communication, deliberation, and information access. Table 4 illustrates the interdependence of KM and collaboration by mapping collaborative technologies to KM activities organized by cognitive process. 6 Discussion The multidimensional framework presented in the tables above demonstrates the interdependence of knowledge management activities and collaboration concepts. The correspondence between collaboration and KM is not surprising when you consider that a) the purpose of an organization is to create value for its stakeholders that the stakeholders cannot create for themselves as individuals; b) the purpose of collaboration is to achieve a goal through joint effort, thus, creating value; and c) the purpose of Knowledge Management is to make relevant knowledge available to people who seek to create value for organizations. Organizations consist of people working together toward value-creation goals; both KM and collaboration technology exist to make them more effective and efficient. On the Convergence of Knowledge Management and Groupware 31 Table 4. Collaboration Technology for KM Activities organized by Cognitive Process KM ACTIVITIES Create Collect Organize Deliver Use COMMUNICATION Voice, Video, IM, Chat, E-mail, Online News Group, GSS discussion tool All of the above COGNITIVE PROCESS DELIBERATION GSS classification and outlining tools, Shared diagramming tools, group decision support tools INFORMATION ACCESS Team Database, Online Document Repository, GSS transcript repository; collaborative query capability All of the above All of the above, plus Online forms, Document and transcript repositories, GSS Classification and outlining tools, Multi-user database, Notice boards, Newsgroups, E-mail, Shared workspace GSS classification and outlining All of the above GSS Shared Outline tools, Shared diagramming Tools, tools, group decision support GSS Concept Classification Tools, supported by tools; Collaborative simulation the tools mentioned above and modelling tools All of the above Virtual Workspace, Docu- Virtual Workspace, Document ment & transcript reposi- & transcript repositories, Team Databases, Remote Presentation tories, Team Databases, Capabilities, Collaborative Remote Presentation simulation and modelling tools Capabilities All of the above All of the above All of the above 6.1 Implications for Research There are several implications of this framework for researchers. First, KM and collaboration are currently separate research streams with few points of overlap. The framework we offered argues the interdependence of collaboration and KM, which suggests that KM and collaboration are two views of a larger underlying concept. The framework offered here does not illuminate the nature of the underlying concept, nor does it articulate a rigorous theoretical foundation for integrating these two lines of research. More research is required to reveal the nature of the underlying concept, and to explain how and why KM and collaboration technologies could or should be integrated. This research must identify and articulate the phenomena and outcomes of interest that the newly integrated research stream could or should address. 6.2 Implications for KM and Collaboration Technology Designers Collaboration technology typically focuses on group process – sense-making, alternative identification and evaluation, decision making, planning, action, and after action review. Collaboration technologists typically deliberately exclude considerations of content. KM technology typically focuses on content – understanding and delivery of data, relationships, information, patterns, procedures, and knowledge. KM technologists typically do not focus on group process. Yet, to achieve their goals, teams and organizations must have effective and efficient collaboration processes, and they must be able to bring the intellectual capital of an organization to bear on their task. It might therefore be useful for KM and Collaboration technologists to find ways to 32 Sajda Qureshi, Vlatka Hlupic, and Robert O. Briggs integrate both kinds of capabilities into a single process-and-knowledge system to support joint effort toward a goal. 6.3 Implications for Practitioners The framework offered here was developed to illustrate the interdependence of collaboration and KM. It is also useful for organizational practitioners. First, it provides as a useful way to understand the variety contributions a given collaboration or KM technology could make to team and organizational productivity. A practitioner could, for example, consider whether the technology were better suited to collective, coordinated, or concerted work, and whether it offered support for communication, deliberation, or information access. The practitioner could consider the variety of collaboration patterns that one could evoke with a given technology. In like manner, the framework might be useful for comparing two or more KM/collaboration technologies to one another, and for positioning collaboration technologies in the market space. Current technology comparisons are usually based on feature checklists. However, feature comparisons are perhaps less informative than comparisons of mode, pattern, and cognition support. Finally, practitioners may find the framework for choosing which mix of technologies might be must useful for addressing a particular collaboration/KM need. The need could be characterized in terms of the dimensions of the framework (what work modes are required, what patterns are required, what cognitive processes are required, what KM activities are necessary?). That characterization could then become a basis for selecting the mix of technologies to address the need. 7 Conclusions The framework offered in this paper illustrates the interdependence of KM and collaboration. These domains are clearly closely related to each other and to organizational value creation, but the nature of those relationships is not ye plain. The theoretical arguments that link them have yet to be articulated. The framework has implications beyond the purpose for which it was originally developed, serving useful purposes for researchers, technologists, and practitioners. However, it cannot substitute for a rigorous theoretical foundation. The development of that theoretical foundation is the next logical step in an effort to improve value creation in organizations by integrating KM and collaboration initiatives. References 1. Angus, J., Patel, J.: Knowledge Management Cosmology. InformationWeek, March 16, 59. (1998) 2. Borghoff, U.M., Pareschi, R. (eds.): Information Technology for Knowledge Management. Springer. (1998) 3. Briggs, R.O.: Focus Theory of Group Productivity, Doctoral Dissertation, University of Arizona. (1994) 4. Briggs, R.O., Vreede, G.J. de, Nunamaker, J.F. Jr.: Collaboration Engineering with ThinkLets to Pursue Sustained Success with Group Support Systems, Journal of Management Information Systems, 19, 4, (2003) 31-63 On the Convergence of Knowledge Management and Groupware 33 5. Ellis, C.A., Gibbs, S.J., Rein, G.L.: Groupware: Some Issues and Experiences. Communications of the ACM, (1991). 39-58 6. Ferran-Urdaneta, C.: Teams or Communities? Organizational Structures for Knowledge Management. Proceedings of the 1999 ACM SIGCPR conference on computer Personnel Research. (1999) 128-134 7. Gamble, P. R., Blackwell, J.: Knowledge Management: A state of the art guide. Kogan Page. (2001) 8. Grudin, J., Palen, L.: Why Groupware Succeeds: Discretion or Mandate? In Proceedings of ECSCW’95, Kluwer. (1995) 263-278 9. Gupta, A. K., Govindarajan, V.: Knowledge Management's Social Dimension: Lessons From Nucor Steel. Sloan Management Review. (2000) 71-80 10. Hansen, M.T., Oetinger, B., von.: Introducing T-shaped Managers: Knowledge Management's Next Generation. Harvard Business Review. March (2001) 107-116 11. Hibbard, J. and Carillo, K.M.: Knowledge Revolution – Getting employees to share what they know is no longer a technology challenge – it’s a corporate culture challenge. InformationWeek. (1998) 663 12. Jackson, C. Process to Product: Creating Tools for Knowledge Management. [www document] URL http://www.brint.com/members/online/120205/jackson/. (1999) 13. Kramer, M.: Knowledge Management Becomes Catch Phrase but Eludes Easy Definition. PC Week, December, (1998). 95. 14. Macintosh, A.: Knowledge Management. [www document]. URL http://aiai.ed.ac.uk/~alm/kamlnks.html. (1999) 15. Nunamaker, J. Briggs, R., Mittleman, D., Vogel, D., & Balthazard, P.: Lessons from a Dozen Years of Group Support Systems Research: A Discussion of Lab and Field Findings, Journal of Management Information Systems. Winter 1996-97, 13 (3), (1997) 163- 207 16. Nunamaker, J.F. Jr., Briggs, R.O., Vreede, G.J. de,: From Information Technology To Value Creation Technology, in: Dickson, G.W., DeSanctis, G. (eds). Information Technology and the Future Enterprise: New Models for Managers, New York: Prentice-Hall. (2001) 17. Quinn, J.B.: Intelligent Enterprise. Free Press. New York (1992) 18. Qureshi, S., van der Vaart, A., Kaulingfreeks, G., Vreede, G.J., de, Briggs, R.O., Nunamaker, J.: What does it mean for an Organisation to be Intelligent? Measuring Intellectual Bandwidth for Value Creation, The Thirty Fifth Hawaii International Conference in Systems Sciences. IEEE Computer Society Press (2002) 19. Ruggles R.: Knowledge Tools: Using Technology to Manage Knowledge Better, URL: http://www.businessinnovation.ey.com/mko/html/toolsrr.html (1997) 20. Skyrme, D. J.: Knowledge Networking: Creating the collaborative enterprise. Butterworth Heinemann, Oxford. (2000) 21. Sproull, L Kiesler, S.: Connections: New ways of working in the networked organization. The MIT Press. Cambridge, MA. (1991) 22. Stewart, T.A.: Intellectual Capital: The New Wealth of Organisations, Nicholas Brealey Publishing Limited, London. (1997) 23. Sveiby, K.E.: The New Organizational Wealth: Managing and Measuring Knowledgebased Assets. San Francisco CA, USA: Berrett-Koehler Publishers. (1997) 24. Vance, D. M.: Information, Knowledge and Wisdom: The Epistemic Hierarchy and Computer-Based Information System . Proceedings of the 1997 America's Conference on Information Systems. http://hsb.baylor.edu/ramswoer/ais.ac.97/papers/vance.htm. (1997). 25. Whitaker, R.: Computer Supported Cooperative Work (CSCW) and Groupware: Overview, Definitions, and Distinctions. www.informatik.umu.se/~rwhit/ CSCW.html. (1996) 26. Zack, M.: Developing a knowledge strategy. California Management Review, (1999) 125145 27. Zigurs, I., Kozar, K.A.: An Exploratory Study of Roles in Computer-Supported Groups, MIS Quarterly, (1994) 277-294