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Expert systems 433
(1) That the subject domain has been formalized. One measure of
formalization is that manuals exist. Of course, the expert may have
devised short cuts through a manual and/or internalized it.
(2) That the subject domain is amenable to verbal expression. One measure
of this is that the expert should feel confident that he/she could
communicate his/her expertise to a novice over a telephone link.
Wright and Ayton argue that if these two key indicators are satisfied
then both the process of eliciting the knowledge from the expert and
subsequent programming of this knowledge, as rules, are relatively
straightforward.
Alternatively, Rangaswamy et al. 5 provide a checklist of four criteria
for selecting problems suitable for expert systems. These are:
(1) That the key relationships in the domain are logical rather than
arithmetical;
(2) That the knowledge domain is semi-structured rather than structured
or unstructured;
(3) That the knowledge domain is incomplete;
(4) That problem solving in the domain requires a direct interface
between the manager and the computer system.
As we shall discuss in the following section, we believe that the second and
third criteria are inappropriate for designing and delivering commercially
viable expert systems. For the moment, note that Wright and Ayton’s
first indicator for success in expert system development is in conflict
with Rangaswamy et al.’s second and third checklist items.
The appropriateness of the marketing domain for expert system utilization
is, to a degree, disputed. Undoubtedly, there are problems which
are intrinsic to the marketing discipline which make the application of
an expert system difficult. Mitchell et al. 6 identify the following three as
of major importance:
(1) The relatively loose nature of the causal structure that relates market
factors to observed sales, a result of intelligent human ‘opponents’
marketing competing products.
(2) The lack of definitive expertise to model, since the potential usually
exists for multiple interpretations of the same market data.
(3) The problem of the importance of the more general world knowledge
which marketers possess, but which is impossible to incorporate
within the narrow limits of expert system knowledge bases.