Exploring expert system success factors for business process reengineering

Abstract Business process reengineering (BPR) has become the buzzword representing dramatic changes to the business processes of organizations trying to quickly preempt or react to market opportunities and competition. Much of the changes are enabled by computer-based technology such as expert systems (ES) providing a unique opportunity to study significant implementations of the technology within a relatively short time. Eight ES implementation success factors proposed in the literature were empirically tested in this study in terms of their direct and indirect importance to the benefits from using ES in BPR. Sixty-two ES applications within E.I. Dupont de Nemours dealing with business process changes significant enough to be called BPR were used. Despite the relatively small sample size, four of the eight success factors were corroborated: user satisfaction with the ES, the difficulty of the business problem addressed, the degree of user involvement in the ES implementation process, and characteristics of the ES shells.

[1]  E. Balagurusamy,et al.  Expert Systems for Management and Engineering , 1991 .

[2]  Donald Smith,et al.  Implementing real world expert systems , 1988 .

[3]  Terry Anthony Byrd,et al.  Implementation and Use of Expert Systems in Organizations: Perceptions of Knowledge Engineers , 1992, J. Manag. Inf. Syst..

[4]  Jay Liebowitz,et al.  Design and development of expert systems and neural networks , 1993 .

[5]  Terry Anthony Byrd,et al.  Expert Systems in Production and Operations Management: Results of a Survey , 1993 .

[6]  Edward G. Carmines,et al.  Reliability and Validity Assessment , 1979 .

[7]  David S. Prerau,et al.  Developing and managing expert systems , 1989 .

[8]  Thomas J. Beckman,et al.  Selecting expert-system applications , 1991 .

[9]  Frederick Hayes-Roth,et al.  The state of knowledge-based systems , 1994, CACM.

[10]  Walter Hamscher AI in Business-Process Reengineering , 1994, AI Mag..

[11]  J. Daniel Couger,et al.  Motivation Norms of Knowledge Engineers Compared to Those of Software Engineers , 1987, J. Manag. Inf. Syst..

[12]  Richard G. Vedder PC‐based expert system shells: some desirable and less desirable characteristics , 1989 .

[13]  Paul Harmon,et al.  Expert systems: tools and applications , 1988 .

[14]  R. Hauser,et al.  The Decomposition of Effects in Path Analysis , 1975 .

[15]  Efraim Turban,et al.  Expert systems and applied artificial intelligence , 1992 .

[16]  Louis Raymond,et al.  Organizational Characteristics and MIS Success in the Context of Small Business , 1985, MIS Q..

[17]  Timothy L. Acorn,et al.  Smart: Support: Management Automated Reasoning Technology for Compaq Customer Service , 1992, IAAI.

[18]  Larry Kerschberg,et al.  Developing knowledge-based systems: reorganizing the system development life cycle , 1989, CACM.

[19]  Jack W. Fellers,et al.  Skills and Techniques for Knowledge Acquisition: a Survey, Assessment, and Future Directions , 1987, ICIS.

[20]  Mike Carr,et al.  Embedded AI for Sales-Service Negotiation , 1994, IAAI.

[21]  Mary Czerwinski,et al.  COMPAQ QuickSource: Providing the Consumer with the Power of Artificial Intelligence , 1993, IAAI.

[22]  William J. Doll,et al.  The test-retest reliability of user involvement instruments , 1994, Inf. Manag..

[23]  Tor Guimaraes,et al.  A Guide to Selecting Expert Systems Applications , 1989 .

[24]  Sammy W. Pearson,et al.  Development of a Tool for Measuring and Analyzing Computer User Satisfaction , 1983 .

[25]  James R. Slagle,et al.  A Method for Evaluating Candidate Expert System Applications , 1988, AI Mag..

[26]  Ting-Peng Liang,et al.  Critical success factors of decision support systems: An experimental study , 1986, DATB.

[27]  Richard G. Vedder Five PC-based Expert Systems for Business Reference: An Evaluation , 1989 .

[28]  W. Doll,et al.  A discrepancy model of end-user computing involvement , 1989 .

[29]  J. Keyes,et al.  Why expert systems fail , 1989 .

[30]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[31]  William J. Doll,et al.  A Congruence Construct of User Involvement , 1991 .

[32]  Elias M. Awad,et al.  The systems analyst as a knowledge engineer: can the transition be successfully made? , 1990, SIGBDP '90.

[33]  D. Leonard-Barton,et al.  Managerial influence in the implementation of new technology , 1988 .

[34]  J. Casey,et al.  Picking the right expert system application , 1989 .

[35]  R. Sitgreaves Psychometric theory (2nd ed.). , 1979 .

[36]  Dorothy Leonard-Barton,et al.  The case for integrative innovation: an expert system at Digital , 1993 .

[37]  Henry C. Lucas,et al.  Empirical Evidence for a Descriptive Model of Implementation , 1978, MIS Q..

[38]  John J. Sviokla An examination of the impact of expert systems on the firm: the case of XCON , 1990 .

[39]  Donald D. Pierson,et al.  Diagnostic Yield Characterization Expert (DYCE) - A Diagnostic Knowledge Based System Shell for Automated Data Analysis , 1993, IAAI.

[40]  Enid Mumford,et al.  XSEL's Progress: The Continuing Journey of an Expert System , 1989 .

[41]  M. K. Raja,et al.  Knowledge acquisition skills and traits: A self-assessment of knowledge engineers , 1994, Inf. Manag..

[42]  Craig K. Tyran,et al.  The implementation of expert systems: a survey of successful implementations , 1993, DATB.

[43]  R. Duda,et al.  Expert Systems Research. , 1983, Science.

[44]  Lien Tran,et al.  OPERA: A Highly Interactive Expert System for Outside Plant Engineering , 1993, IAAI.

[45]  Ignizio Introduction to expert systems , 1985 .

[46]  J. Daniel Couger,et al.  Information systems curriculum recommendations for the 80s: undergraduate and graduate programs , 1982, CACM.

[47]  William J. Doll,et al.  The measurement of end-user software involvement , 1990 .

[48]  Tor Guimaraes,et al.  Exploring the Factors Associated with Expert Systems Success , 1995, MIS Q..

[49]  Pamela K. Coats Why Expert Systems Fail , 1988 .

[50]  Joseph McManus,et al.  Expanding the Utility of Legacy Systems , 1993, IAAI.

[51]  Tor Guimaraes,et al.  The Determinants of DSS Success: An Integrated Model* , 1992 .

[52]  Victoria Y. Yoon,et al.  Selection of a good expert system shell for instructional purposes in business , 1992, Inf. Manag..

[53]  Donald E. Hardaway,et al.  Identifying long-term success issues of expert systems , 1994 .

[54]  Daniel G. Bobrow,et al.  Expert systems: perils and promise , 1986, CACM.

[55]  Larry Press,et al.  The global diffusion of the Internet: patterns and problems , 1994, CACM.

[56]  H Brody,et al.  Transparency: informed consent in primary care. , 1989, The Hastings Center report.

[57]  Robert Plant,et al.  Expert systems shell benchmarks: The missing comparison factor , 1994, Inf. Manag..

[58]  Donald A. Waterman,et al.  A Guide to Expert Systems , 1986 .

[59]  Stephen B. Sloane,et al.  The Use of Artificial Intelligence by the United States Navy: Case Study of a Failure , 1991, AI Mag..