Good sales forecasts arrival for effective marketing management. Without a realistic estimate of future sales, the marketing manager is badly handicapped in his planning. To start with a budget which shows projected operations cannot be developed without a careful sales forecast. Forecasting is needed for control, too, since it is practically impossible to evaluate performance without a measure of what was anticipated.

While sales forecasts are needed bye the marketing manager and probably are his responsibility ,they are needed by others, too. Accountants and financial officers base their planning and budgeting work on sales forecasts. Production schedules and purchasing plans may hinge on sales forecasts. In fact, when a business organization is viewed as a single system, all the activities are interrelated and actual and anticipated sales keep the system going.

There are two kinds of forecasts; short-run forecasts for a year or less and long-run forecasts covering periods of two or more years. Our concern here will be primarily with short-run forecasts. The same methods are useful for long-run forecasts, hut generally more things can change and so more assumptions must be made about future conditions.

The first step in developing a sales forecasts is to determine why sales fluctuate. This is the most difficult and time consuming aspect of sales forecasting. Unless this is known, it is difficult to predict which way and how far sales will move. Once it is known why sales fluctuate, it usually is relatively easy to develop a specific forecast just as the execution function follows naturally from planning.

Determining why requires considerable ingenuity, plus the use of all available research tools. If a company had a single product and sold it to a single, customer, perhaps a large company or the federal government, the forecasting job would be merely one of estimating what is going to happen to that customer's business. But this would be unusual Normally farmers, miners, retailers, wholesalers and manufacturers have many  customers, all with various economic forces operating upon them.

The great variety of economic forces complicates the forecasting task. Usually, fluctuations in the level of the whole economy have a bearing on the forecasts, since this affects and is affected by-families personal income and employment, business investment and government expenditures. Many more detailed factors also may be involved, such as births (for baby food or infant products) and housing starts (for furniture and house furnishings) other factors include the rate or growth of the industry involved, the rate of substitution of one product for another and generally speaking, the marketing mixes being offered by the firm's many competitors.

It is normally impossible to isolate all of the reasons for economic fluctuations, since the economic world is too complex. Judgment, to some extent, is needed. But the isola­tion of basic factors can be of real assistance in developing a sales forecast, and represents an important part of the sales forecaster's task.

The basic factors affecting a particular product's sales are not all equally significant. Some affect the whole economy some only the industry and some the specific company or product's sales. For this reason, a common approach to sales forecasting-and the one we follow-is to:

1-   Develop an economic forecast for the whole economy and use this in,

2-  Developing an  industry sales forecasts, which  in turn  is used to,

3-  Develop a specific company ox product forecast.

Several methods can be used for each these forecasts. Ironically, this proves to be advantage, since forecasts are so important that management prefers to develop forecasts in two or three different ways and then reconcile the differences before preparing a final forecast.

5.1. Developing Industry Sales Forecasts

Once an aggregate forecast for the   whole economy has been made, the next step is to make a lower-level forecast, for industry sales. Frequently the two are closely related. Automobile sales, for example are related to the level of national income, since automobile sales normally rise as national income rises.

When developing industry sales forecasts, marketing analysts look for the same type of leading series as they did in aggregate economy forecasts. Some model building techniques have been developed by individual companies, although these are confidential.

Industry forecasts merely provide an upper limit on the sales which can be obtained by a specific firm. Since we are stressing the development of unique marketing strategies, we will not dwell on industry forecasts. Where such fore-casts make sense, the techniques are similar to those used in developing national economy forecasts.

The idea of an industry forecast makes sense for such industries as steel, cement, plywood and housing. But the more a specific firm seeks to cater to the customers in smaller and sınailer market grid boxes, the less important the industry sales forecast becomes. In the extreme case, the firm might be the industry. Then the firm would be more concerned with developing a company forecast.

5.2. Developing Company Forecasts

Company and specific product forecasts require that the company's marketing mix-the four P's-be considered. The aggregate estimates for the economy or the industry provide the framework within which the firm operates. But new products-or place, promotion and/or price changes-may drastically change the company's share of the market. Here both the above and new techniques are needed to estimate the sales prospects.

5.3. Forecasts For Established Products

Trend extension and leading series. If conditions are not changing rapidly, trend extension and leasing series analysis may   be useful in forecasting sales for established products.D  i   f   f  e   r  e  n  t  leading series will be needed perhaps, but theserelatively mechanical approaches may provide sound forecasts and   these can be compared against forecasts obtained by other methods. In some cases, even when the firm is practically synonymous with the industry, for example, some firms spe­cialize in particular products, but their marketing mix does not change radically or frequently. To them, these approaches might be appropriate.

Salesmen's estimates. Where competition is more dynamic and change more likely, a sales force estimate may be useful in anticipating changes in competitors' marketing mixes. I lie sales force is more likely than home office analysts to be familiar with customer reactions and to hear about what competitors are doing. Salesmen's estimates, product by product and customer by customer, can be reviewed with the sales manager and then aggregated in the home office. Salesmen's estimates are especially useful industrial goods markets, composed of a limited number of customers who are well known by the salesmen. But even a good retail clerk may have a "feel" for the market and his observations should not be ignored.

Since salesmen normally are not intimately familiar with expected changes in the national economic climate (and probably not even proposed changes in the company's marketing mix), their estimates usually are adjusted by the home office in light of national and industry forecasts and other facts.

Sales force estimates must be used with care, however. If the turn over of salesmen is high, their estimates cannot be expected to be too reliable. Some salesmen's forecasts, moreover, are related to a subsequent measure of their perfor­mance, to the firm's compensation system or to the promotion budgeted to each territory. In these cases, it is only human to expect that a salesman will tend to adjust his forecast to his advantage. Where such considerations are not relevant, however, sales force estimates may provide another estimate for comparison before final forecasts are developed.

Surveys, panels and market tests. Instead of relying heavily upon salesmen to estimate customer's intentions, it may be desirable to use marketing research techniques. Special surveys of final buyers, retailers and wholesalers, may be illuminating. Some firms use panels of stores or final consumers to keep track of buying behavior and to determine when the use of simple trend extension may have become completely inadequate.

These survey techniques are sometimes combined with market tests when the company wants to estimate the reaction of customers to possible changes in the marketing mix. In one market test, a product gained 10 percent in its share of the market as a result of a 1 cent price differential between itself and the remainder of the market. This extra business was quickly lost, however, when the price was increased 1 cent above the competition. Such market experiments may enable the marketing manager to make realistic estimates of future sales when one or more of the four P's are changed.

Sales analysis. Where there is a lag between the purchases of final consumers and receipt of orders by a manufacturer because their purchases must be reflected through retailers' and wholesalers' inventories, rapid analysis of retail sales may be helpful in forecasting future sales. Some firms analyze their incoming warranty cards for a measure of goods at the final customer level.

Wholesalers and manufacturers can work together for mutual benefit. Some wholesalers handling major appliances, for example send in weekly reports ofsales, by model, to guide the manufacturer and enable him to forecast sales trends. Here the whole salers have agreed to accept automatically shipments from the manufacturer which replace units sold. Sometimes more rapid processing of current sales records provides data which can be extended accurately for a month or two in advance. This may be especially important when seasonal influences are strong. Speedy electronic data processing of current sales data may enable the firm to anti­cipate what the customer is likely to do; this was far more difficult when only old sales data was available.

5.4. Forecasts For New Products

Forecasting sales for new products is themes difficult and most risky task of all. If the products is really new, there is no relevant historical data which can be extended and no experience to know which leading series might be relevant, furthermore, as noted in the last chapter, it is unrealistic to expect potential customers for even salesmen to have valid opinions about things they know little or nothing about. The situation is not hopeless, however. The substitute method may be helpful, marketing research on the potential market grid may be suggestive and market tests can be useful.