Adaptive Search Method For Strategy Formulation

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:

  • a set objectives is established,
  • the difference (the gap) between the current position of the firm and the objectives is estimated,
  • one or more courses of action (strategy) are proposed,
  • 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:

  • a ‘cascade’ procedure of successive narrowing and refining the decision rules,
  • feed-back between stages in the cascade,
  • a gap-reduction process within each stage, and
  • adaptation of both objectives and starting-point evaluation.

(By Peter Frans – Managing Partner)

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