Making A Broad Market Assessment

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Making a broad market assessment

In the case of each user industry, both during desk research and during field work, the researcher endeavours to locate some factors which:

can be related to reliable published data covering the industry as a whole;

also bear a reasonably close and consistent relationship to purchases, by establishments in the sample, of the products under investigation.

The approach is perhaps best illustrated by taking one of the most commonly accepted indicators - numbers of employees.

It will be realized that this particular approach is based on two principal assumptions. First, that establishments' purchases of the product under survey are proportionate to size of establishment, and second, that size is adequately measured for this purpose by numbers of employees.

On the face of it these appear to be eminently commonsense assumptions. A few seconds further thought, however, will show that a number of dangers are inherent in this approach. The extent of mechanization/automation, or the ratio of indirect/direct employees, can radically affect the value of the employee indicator. Further, establishments are usually classified to only one SIC category, that which accounts for the greater part of their production; yet it is, of course, not unusual for a single establishment to manufacture several different products covering several SIC

- categories. Some allowance must also be made for establishments which manufacture the survey product as a secondary line, and are thus classified to other SIC categories. Finally, while the industrial researcher is now working necessarily by establishments, companies' purchasing policies may be partially or wholly centralized at head offices and may relate to the enterprise as a whole.

Clearly, to accept blindly the approach outlined in the example would be a highly dangerous proceeding. Some of the dangers, however, can be eliminated by really competent field work, while the basic assumptions can be checked to a large extent by correlation tests. Usually data will be adequate for simple tests of linear correlation, and on really major surveys it may be possible to investigate further for non-linear relationships. Often there will be no real need even for this degree of sophistication. The existence of a reasonable straight-line relationship (between establishment's purchases and the number of employees at the establishment) can be checked merely by plotting on a graph.

Whether or not the employee indicator provides a satisfactory correlation, it is important to use as many other indicators as possible, in order to provide cross-checks. Possible indices are turnover, output in quantity terms, raw material consumption, or rateable values. Each of these is applicable to certain situations. Many other indicators are possible, depending on the product under survey - there is again scope for ingenuity.

To sum up, the use of such indicators, with adequate field work, proper safeguards, cross-checks against background control data, and just a modicum of common sense and experience, offers an additional method of arriving at a reasonable estimate of market size. So far, where direct comparison of methods has proved possible, results have been satisfactory.

Such indicators are, of course, the last resort after all other approaches have failed. What happens if these methods, too, fail to give satisfactory results?

In such cases, our. managing director must simply face the unpalatable fact that in certain industrial market research situations it is just not possible to obtain at economic cost any reliable estimate of market size.

It may, ironically, be of some consolation to him to know that professional industrial researchers themselves are in the same boat. Despite praiseworthy efforts by some practitioners, the industrial researcher is still woefully short of reliable data on the market for his own service&


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