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One of the
methods in formulating strategies is Adaptive Search Method.
This method uses a search procedure in arriving at a strategy.
This is accomplished through a ‘cascade’ approach: at the outset
possible decision rules are formulated in gross terms and are
then successively refined through several stages as the solution
proceeds.
For example, a civil contractor may analyze its past performance
and prospects and arrive at a decision to seek diversification.
As the second step it would decide that a closely related
industry is the natural direction to follow and pick real estate
development as its preferred arena. This would be followed by a
detailed analysis of the firm in relation to the competitive
characteristics of real estate developers. The end product would
be specific decision rules such as the competitive and joint
effect interactions desired for the new entry. Thus armed with a
concept of the business it wishes to become, the firm would
begin to seek out, create, and evaluate opportunities.
Another important characteristic of this process is feedback.
Since the cascade is a process of search for the best solution,
information may develop at later stages which cast doubt on
previous decisions.
Thus the civil contractor may discover that it does not have as
good a match with the real estate business as appeared on
preliminary rough examination. It will then re-examine the
previous choice of the product-market scope. The procedure
within each step of the cascade is similar:
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a
set objectives is established,
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the difference (the gap) between
the current position of the firm and the objectives is
estimated,
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one or more courses of action
(strategy) are proposed,
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these are tested for their
‘gap-reducing properties’.
A course is accepted if it
substantially closes the gap; if it does not, new alternatives
are tried.
To continue the simple example, the civil contractor may choose
12 per cent annual rate of return on investment (ROI) as its
sole objective (this may be highly unlikely in real life, but
helps the example). It finds that past history and current
trends show that 8 per cent ROI is the best that can be attained
with maximum effort in the civil contracting business. The gap
is 4 per cent.
Trends in the real estate industry indicate an average 14 per
cent return for the industry. To attain a 12 per cent average, a
certain size of acquisition is needed. A test is made to see
whether an acquisition of such size within a reasonable period
of time is within the firm’s resources.
If the answer is yes, the real estate industry is selected; but
the result is provisional, because later stages of analysis may
show that the civil contractor's chances of doing as well as the
average in the real estate industry are not very great, or that a
much larger investment will be needed than was originally
anticipated.
The example points to the feature of the method which introduces
the word ‘adaptive’ into the title of this article.
Suppose that the firm cannot find any industry through which it
can attain a 12 per cent ROI. In that case the goal will have
to be revised downward. Or a more happy event, suppose the real
estate entry looks so promising that even 15 per cent would be
reasonable. Up goes the goal. Thus the method has what Reitman
calls ‘open constraint’ property; both the objectives and the
evaluation of the present position are subject to revision as a
result of insights obtained in the process of solution.
To summarize briefly, the adaptive search method described above
is its application in the formulation of a business
strategy of a firm. Its salient characteristics are:
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a ‘cascade’ procedure of
successive narrowing and refining the decision rules,
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feed-back between stages in the
cascade,
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a gap-reduction process within
each stage, and
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adaptation of both objectives
and starting-point evaluation.
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