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432 Alternative decision-support systems
of whom may also be unfamiliar with computers. Successful systems
must be able to interface effectively with their users in order to:
(1) Gain the information needed to test the rules;
(2) Give understandable advice in plain English and justify the logic
and reasoning underpinning the advice given or decision made.
Psychologists, rather than computer programmers, have the sort of
skills necessary to build appropriate interfaces. Consequently, successful
knowledge engineers integrate both computing and psychological skills.
Overall, expert systems are often developed to reproduce experts’
decision-making processes in relatively narrow speciality areas. The
way in which expertise is represented in the systems has most often
been in terms of production rules, since these are easily programmable.
Two types of expert systems can be distinguished. The first are basically
academic research projects where difficult, or potentially unsolvable,
problems are tackled so that new ways of representing or eliciting
knowledge must be developed. The second set of systems are those built
by consultants utilizing commercially developed expert system shells.
These are easily programmable in the same way that word-processing
programs and spreadsheets provide easy-to-use tools for the office
environment. Consultant-built expert systems have tended to focus on
problems where uncertainty is not present. This is because Bayes’ theorem
is not easily understood by non-statisticians. Even for statisticians,
the computations become complex when data contain dependencies.
Indeed, in practical applications of expert system technologies, expert
judgment is often represented in terms of decision trees without uncertainty
nodes. Such tree representations of knowledge lend themselves
to straightforward programming. In the next section, we focus on expert
systems that have potential commercial applications in marketing and
financial services. As we shall see, not all commercially focused system
development has produced or, as we shall argue, was ever likely to
produce commercially successful applications.
Commercially oriented expert system applications in marketing
and financial services
Wright and Ayton 4 have differentiated two key indicators of whether
an expert system can be built within a reasonable time frame. These are: