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Comparisons 453
‘broken leg’ cues occurring is pronounced, bootstrapping systems will
be less successful and may be best overridden by holistic judgment.
By contrast with decision analysis, scenario planning makes the assumption
that subjective probability assessments for unique, one-off events
are of poor quality. The focus of scenario planning is the construction of
a range of plausible futures and the subsequent evaluation of strategic
choices against these futures. Here, the focus is on creating a robust
strategic decision that performs well across the range of futures. In
many ways, choice using scenario planning is analogous to the maximin
decision principle. However, the process of scenario planning also creates
conditions for the creation and evaluation of new decision options.
Additionally, even if robust decisions cannot be identified or created,
scenario planning’s process of ‘rehearsing the future’ serves to sensitize
the decision maker to the occurrence of the early events entailed in
the unfolding of particular scenarios. Such early warnings are likely to
prompt swift deployment of contingency action.
Overall, the process of scenario planning is, we believe, likely to
promote multiple framings of the future. Such reframing is, we feel,
likely to provide suitable conditions that will prompt recognition of
inertia in strategic decision making, or mechanization of thought. By
contrast, decision analysis contains no process methodology to aid
such reframing. For this reason, our view is that scenario planning
is a useful non-quantitative precursor to a quantitative decision tree
analysis. Additionally, we detailed a new method which combines
scenario planning with multi-attribute value theory. This combination
provides an approach to decision making that is fully complementary to
decision tree analysis, but places little reliance on the decision maker’s
ability to provide inputs of subjective probabilities for unique events. As
we have argued, subjective probability assessment for such events can
only be achieved by the use of heuristic principles which may produce
bias. Nevertheless, both decision tree analysis and scenario planning
are predicated on the notion that the decomposition, and subsequent
recomposition, of judgment is thought to produce an improvement over
unaided, holistic decision making.
Expert systems, in contrast, are predicated on the assumption that
expert, informed holistic decision making is valid. 55 Conventional approaches
to assessing the adequacy of a system focus on the convergence
between the system’s decision/diagnosis/advice and that of the expert
who is modeled in the system. Although expert decision making is
conventionally decomposed into if/then production rules, no normative
theory or statistical technique oversees the aggregation or selection of