Applications of statistics in management, Operation Research

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In a business, statistics is used to study the demand and market characteristics of the product or service being sold. In fact, market research has evolved into a separate discipline. The planning process, whereby the firm seeks to match its future activities with expected future conditions and developments, can be facilitated by the use of statistical probability. In the performance evaluation of personnel, machinery, departments, etc. measures of central tendency and dispersion can be used to provide a certain degree of objectivity. Coming to finance, statistics can be used to reveal long-term trends and seasonal variations in sales, expenses and incomes. Statistics is useful in the management of inventories and receivables. In the management of investments, statistics can be used to determine the alternative that provides the highest return per unit risk. Statistics can also be used to test the validity of various tools that are said to be useful in investment selection.

Firms often study their profits over the years and attempt to find clues for future performance. Investors compare expected rates of return on various investment alternatives to determine where to place their money. Merchant bankers study the projected profits of their client companies to advise on the right price at which equity issues may be made. Credit rating agencies consider various factors related to the creditworthiness of issuers of debt in order to estimate the likelihood of default.

In the above mentioned cases, statistics is being used to examine real life situations for a description and assessment of what is happening and to obtain some pointers to an uncertain future. Statistics is all about number crunching and the ultimate number cruncher - the computer - has placed statistics in the center spot in today's business environment.

Box 1: Compile, Compare, Conclude


Statistics may be used to reveal, conceal, guide and misguide.

PCS Data Products Ltd. is engaged in the manufacture of computer hardware and copper clad laminates. In 2002-03 its sales were Rs.29.86 crore which were double the previous year's sales. Suppose another company Shady Ltd. (an imaginary company), claims that it has outperformed PCS Data Products because its sales increased by 200% whereas PCS sales increased by only 100%. Such a statement should be treated with extreme caution. For example, Shady Ltd. may have had very low sales in the previous year, say sales of Rs.10,000 only. If they increased to Rs.30,000 in 2002-03 the growth rate would be 200% which is higher than the growth rate of PCS. However, at Shady's low level of sales, such a high growth rate is totally unimpressive as compared with the growth rate of PCS. In general, when comparing growth rates, it is always useful to keep in view the amounts involved. Otherwise, even a growth from zero to Re.1 can be claimed to be an infinite growth rate!

Suppose Shady Ltd. wants to make a public issue of equity shares. In deciding whether to invest in Shady's shares, the public would consider the profits earned by it. If Shady has incurred a loss, the public would be reluctant to take up its shares. In such a case Shady may extend its current accounting year to a period of say 15 months in the hope of covering up the loss with the earnings in the additional three months. It may also use various window-dressing measures to inflate its profits so that it displays a higher profitability than PCS. In such cases the data provided by Shady cannot be compared with the data provided by PCS.

A mediocre company like Shady is likely to produce mediocre products. Hence it would resort to fair and unfair means to sell its product. Here too statistics may be used to distort the truth. For example, Shady may claim that on the basis of a survey it was found that Shady's products were considered the best available. The truth could be that the survey covered only friends and relatives of Shady's management.

Even without an intent to deceive, statistics may mislead if its implications are not clearly understood.


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