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454 Alternative decision-support systems
these rules into an optimal set or sequence for execution when the system
is used.
In common with bootstrapping models, expert systems are most useful
in repetitive decision or advice-giving situations. The reason for this is
simple: if the conditions that lead to a decision or piece of advice
are rarely encountered then the knowledge engineering time needed
to model that ‘leg’ of the decision tree may not be cost effective. In
many commercial applications it is far better if the need for extrasystem
human expertise is recognized by the system and a complex
problem is handed over to an expert for resolution. For example, in
the life underwriting system outlined above, infrequent combinations
of medical conditions and medical treatments that could, potentially,
indicate that a proposal concerns a poor life risk are dealt with by the
chief underwriter.
Overall, there are several differences in the domain of applicability of
decision analysis, scenario planning, bootstrapping models and expert
systems. One commonality to all is the primacy of human judgment. As
we saw in Chapter 9, human judgment is likely to be good when practice
and useful feedback provide conditions for the quality of judgment to
be evaluated. In decision analysis practice the decision analyst working
on (what is usually) a unique decision can only check the reliability
of the decision maker’s inputs of probability and utility. Questions
to do with the validity (e.g. calibration) of the assessments are much
more difficult to evaluate for one-off assessments given by non-practiced
assessors. Fortunately, sensitivity analysis provides a fallback that at least
allows identification of critical inputs. Decision conferencing techniques
allow further analysis and discussion of these inputs. Clearly, in the
absence of ‘the truth’ an achievable alternative of a group consensus
or, at least, knowledge of the variability in the groups’ estimates is
useful knowledge.
We have argued previously that decisions, once made, are often
‘made’ to work. For this reason, questions to do with the validity of
decision analyses are often raised but seldom answered. Most often, the
question of validity is sidestepped and questions concerning the ‘valuation’
of decision analysis are raised instead, as we saw in Chapter 12
when considering decision conferencing. Questions on the validity of
linear modeling are more easily answered, since the method is most
useful under conditions of repetitive decision making. As we have
seen, this method has shown evidence of incremental validity over
the holistic judgments/predictions of the judge on whom the model
was based.