Contrasting successful and unsuccessful Expert Systems

Many Expert Systems are unsuccessful in that they are never fully implemented, or when implemented quickly fall into disuse, or are not used to the extent originally envisioned. Alternatively, some systems have become very successful, supposedly saving or generating considerable amounts of money for the organizations that developed them. This paper reports on research aimed at investigating why some Expert Systems are more successful than others. It considers four cases which describe Expert Systems developed in (or under the auspices of) two leading technological companies; two are very successful, two less so. The systems deal with problems in manufacturing scheduling, computer customer support, engineering design and commercial lending. The authors employ a factor-oriented analysis where discussions with developers were used to ascertain the importance of user motivation, software and hardware platform, project planning methods, and other factors generally considered as relevant to success. The cases reveal that six key factors differentiate the successful from the less successful applications, namely demonstrable benefits, adequate development resources, commitment to implement, rapid turnaround of users’ requests, understanding and control of data, and growth in the underlying application.