From Data to Knowledge and Back Again: Understanding the Limitations of KMS

The mixed results reported in the studies mentionedindicate a fundamental problem in the ISfield’s approach to the concept of knowledge. Supportfor this assertion comes from Galliers andNewell (2001) who voice deep-seated concernsabout the knowledge-management paradigm andits influence on the IS field.
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From Data to Knowledge and Back Again: Understanding the Limitations of KMS Knowledge and Process Management Volume 10 Number 3 pp 144–155 (2003) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/kpm.180&From Data to Knowledge and Back Again:Understanding the Limitations of KMSTom Butler*Business Information Systems, University College Cork, Ireland Researchers in the field of information systems (IS) view IT-enabled knowledge management solutions as novel approaches to the stimulation of creativity and innovation in post-industrial organizations; hence, the focus by researchers on the role of information and communication technologies (ICT) in enabling and supporting knowledge work. However, despite some suc- cess stories, recent research indicates that the majority of knowledge management systems (KMS) have been unsuccessful. This situation has led some to voice deep-seated concerns about the knowledge management paradigm and its influence on the IS field—particularly the belief that IT can help capture, store and transfer knowledge. This paper’s objective is to deepen the IS field’s understanding of the limitations and capabilities of knowledge management systems. A case study of an Irish software vendor’s experiences in developing KMS using case-based reasoning technologies is undertaken to help achieve this objective. The findings of this study illustrate that: (a) the KMS developed in the organization studied did not meet the claims of their creators, as the applications provided a poor approximation of the ‘horizons of under- standing’ of domain experts whose knowledge these systems purported to capture, store and transfer; (b) the ontological and epistemological perspectives of developers were overtly functionalist in orientation and were insensitive to the socially constructed and institutional nature and context of knowledge. The findings lend weight to the claim that information tech- nology deals with data only, and knowledge management requires social as opposed to tech- nical support, in that appropriate institutional mechanisms, rather that technological solutions, constitute the corporate memory. Copyright # 2003 John Wiley & Sons, Ltd.INTRODUCTION such technologies include, for example, decision support, groupware and computer-mediated colla-Knowledge management systems (KMS) are boration applications, data warehouses, videoviewed as novel approaches to the stimulation of conferencing, intranets, the Internet, artificial intel-creativity and innovation in post-industrial organi- ligence (AI) based applications, and so on (Daven-zations (Davenport and Pruzak, 1998; Kanter, 1999; port and Prusak, 1998; Carlsson et al., 2000; AlaviLaudon and Laudon, 2000). Researchers in the IS and Leidner, 1999, 2001; Damsgaard and Schee-field have therefore focused on the role of informa- pers, 2001). The application of such technologiestion and communication technologies (ICT) in underpins a new breed of IS called knowledgeenabling and supporting knowledge work (see management systems: such systems range fromDavenport et al., 1996; Sviokla, 1996). Examples of directories/databases of domain experts and key knowledge workers in organizations, to systems that purport to capture, store, and transfer the*Correspondence to: Tom Butler, Business Information Systems,O’Rahilly Building, University College Cork, Cork City, Ireland. knowledge of organizational actors for access byE-mail: tbutler@afis.ucc.ie others within the organization for decision support.Copyright # 2003 John Wiley & Sons, Ltd.Knowledge and Process Management Recent research indicates that many knowledge Section 5 provides a discussion of the findingsmanagement systems are unsuccessful (see and offers several conclusions.Schultze and Boland, 2000), with Storey andBarnett (2000) reporting failure rates of over 80%;nevertheless, Davenport et al. (1996) catalogue a KNOWLEDGE MANAGEMENTnumber of success stories. While there is much OR DATA PROCESSING SYSTEMS?debate, theorizing, and writing of a normative nat-ure on the topic, there is a paucity of in-depth The IS field is concerned with the development,empirical research on the development and imple- implementation and use of systems to informatementation of KMS. Inconclusive findings and a organizational actors and automate business pro-dearth of empirical evidence has led some to voice cesses (Checkland and Howell, 1998). However,deep-seated concerns about the knowledge man- Boland et al. (1994) argue that information systemsagement paradigm and its influence on the IS field. have been less successful at informating—that is,Of particular concern are the belief that KMS con- supporting the cognition and decision-making ofstitute a new type of information system (as organizational actors—than in automating—thatopposed to DSS, GDSS, EIS and expert systems, is, removing all opportunities for individual deci-etc.) and the claims that they can capture, store, sion making and learning. The problem here liesand transfer knowledge within organizational con- in the prevailing image of organizational actorstexts. ...