For complex problems, the first of
these two approaches is of course impossible. Although such an approach can be
described, it cannot be practiced except for relatively simple problems and
even then only in a somewhat modified form. It assumes intellectual capacities
and sources of information that men simply do not possess, and it is even more
absurd as an approach to policy when the time and money that can be allocated
to a policy problem is limited, as is always the case. Of particular importance
to public administrators is the fact that public agencies are in effect
instructed not to practice the first method. That is to say, their prescribed functions
and constraints - the politically or legally possible - restrict their
attention to relatively few values and relatively few alternative policies
among the countless alternatives that might be imagined. It is the second
method that is practiced.
Curiously, however, the literatures of
decision-making, policy formulation, planning, and public administration
formalize the first approach rather than the second, leaving public
administrators who handle complex decisions in the position of practicing what
few preach. For emphasis I run some risk of over-statement. True enough, the
literature is well aware of limits on man's capacities and of the inevitability
that policies will be approached in some such style as the second. But attempts
to formalize rational policy formulation - to lay out explicitly the necessary
steps in the process - usually describe the first approach and not the second.'
The common tendency to describe policy
formulation even for complex problems as though it followed the first approach
has been strengthened by the attention given to, and successes enjoyed by,
operations research, statistical decision theory, and systems analysis. The
hallmarks of these procedures, typical of the first approach, are clarity of
objective, explicitness of evaluation, a high degree of comprehensiveness of
overview, and, wherever possible, quantification of values for mathematical
analysis. But these advanced procedures remain largely the appropriate
techniques of relatively small-scale problem-solving where the total number of
variables to be considered is small and value problems restricted. Charles
Hitch, head of the Economics Division of RAND Corporation, one of the leading
centers for application of these techniques, has written:
I would make the empirical
generalization from my experience at RAND and elsewhere that operations
research is the art of sub-optimizing, that is, of solving some lower-level
problems, and that difficulties increase and our special competence diminishes
by an order of magnitude with every level of decision-making we attempt to
ascend. The sort of simple explicit model which operations researchers are so
proficient in using can certainly reflect most of the significant factors
influencing traffic control on the George Washington Bridge, but the proportion
of the relevant reality which we can represent by any such model or models in
studying, say, a major foreign-policy decision, appears to be almost trivial.2
Accordingly, I propose in this paper
to clarify and formalize the second method, much neglected in the literature.
This might be described as the method of successive limited comparisons. I will
contrast it with the first approach, which might be called the
rational-comprehensive method.' More impressionistically and briefly - and
therefore generally used in this article - they could be characterized as the
branch method and root method, the former continually building out from the
current situation, step-by-step and by small degrees; the latter starting from
fundamentals anew each time, building on the past only as experience is
embodied in a theory, and always prepared to start completely from the ground
up.
Let us put the characteristics of the
two methods side by side in simplest terms.
No comments:
Post a Comment