Three Basic Approaches to Sales Forecasting (1693 Words)

Read this article to learn about the three basic approaches to sales forecasting!

Forecasting, rudiment point of planning, from a marketing standpoint, is the tactics of predicting alterations in the market­ing environment, so that organizations can contrive strategies to encounter them when they occur.

The sales forecast is an anticipation of sales, in monetary or physical unit for a defined period of time, in a specified marketing circumstances and geographical extent under a particular set of marketing pro­gramme. E.W. Cundiff and R.R. Still define sales forecast as an estimate of sales during a specified future period, which estimates is tied to a proposed marketing plan and which assures a particular set of uncontrollable and competitive forces.

There are three basic approaches to sales forecasting: the opinion approach which is based on experts judgements; the historical approach, which is based on past experience and knowledge; and the market testing approach, which is based on testing market through survey and research. No one technique of sales forecasting can be applied to all organizations, nor all factors that set a sales forecast be supplied by one individual or statistical department.

Depending upon the type of problem involved, and the degree of accuracy needed a concern selects the approach which may be more suitable to achieve the predetermined goal. In the following lines, an attempt has been made to make a brief study of the various approaches of sales forecasting.

I. Opinion approach:

The opinion approach is based on cogitation of executives, experts and specialists. Experts’ opinions, views of sales force composite and survey of buyers’ intentions are all used in the option approach. Let us analyze them briefly:

(i) Experts opinion:

In this technique information’s are amassed from experts including economists, marketing consultants, suppliers, distributors and trade associa­tions, inside or outside the concern. One or more experts forecast future sales based on personal cognition, from discussing with other experts, through customer contacts or through reciting resplendent reports related to national economy and industrial state.

The advant­ages of this method of forecasting are that different points of view are achieved quickly and inexpensively. But the greatest drawback of this method is subjectivity and hence they lack scientific validity and can be deceptive.

(ii) Sales-force composite:

The sales force composite is a forecast arrived at by gathering estimates from each salesperson of the organization products. Sales managers presumably know more about their own territory or region than others in the organization.

Salesmen have first hand information because they are indirect contact to buyers. Each and every salesman submits his sales estimation to be hopped in his region. The summation of the estimates of all salespersons is named sales forecasting. The estimates may be submit­ted annually at the start of the annual forecast or continuously in what marketers call rolling forecasts. Several arguments favour sales-force composites.

First being closest to the customers, salesman may have more knowledge than any other. Second if the sales force is actually involved in forecasting, it has a greater incentive to achieve the desired sales quotas. Finally, this method is easy, economical, consistent and reliable. The weaknesses of sales-force composite method are: First, salesperson has keen interest in sales and they dan make hasty estimates which may be disastrous also.

Some salesmen may be over-pessimistic or over- optimistic regarding future sale opportunities. Second after salesperson are unknown about economic fluctua­tions for that they unable to predict long term trends. Third if the quota of salesmen is fixed then they will estimate low quoting.

(iii) Survey of buyers’ intention:

Since sales forecasting is the art of anticipating what buyers are likely to do under a given -set of conditions, it is most useful to take a survey of the opinions of potential buyers themselves. Buyers are solicited to communicate their buying intentions in forthcoming period. Here information can also be gathered from governmental agencies, trade associations and educational institutions.

For example, American Airlines conducts regular polls of its passen­gers and comprising the results with general industry information and government statistics to predict future levels of air traffic. If buyers’ purchase estimates are accurate, our sales forecasts may be useful. But experi­ence has shown that a market survey approach is really practical only when concern is selling specialized costly goods.

The market survey approach is of value basically for industrial products and consumer durable products where advanced planning is required and for new products where past data do not exist. Another objection raised to this method is that in the case of consumer convenience goods, it would be prohibitively costly in terms of money and time, to pay a personal call on every customer. But his problem can be solved by statistical sampling.

II. Historical approach:

Another approach for sales forecast is to employ the quantitative data from past sales results for predicting future. The popular methods of correlating data include time series pro­jections and statistical projections. Let us analyze them briefly.

(i) Time-series projections:

Under this method forecasts are made on the basis of statistical-mathematical analysis of past data. The logic underlying this approach is that past data are an expression of enduring causal relationships that can be uncovered through quantita­tive analysis. Changes in a time series are attributable to many components, which can be classified into four major heads, according to the nature of these factors, as

(a) Secular Trend (T) the result of long term basis developments in population, production, money in circulation and technology;

(b) Cyclical Variations (C) Oscillatory movements related to change in business cycles (prosperity, recession, depression and recovery) from time to time;

(c) Seasonal Variations (S) a recurrent pattern of sales within the year, whether it be on a seasonal, quarterly, monthly, weekly or even hourly basis;

(d) Erratic Variations (E) random nature and arise on account of sporadic factors e.g., strikes, lock­outs, fires, wars, riots etc. All the four components interact with the original sales series (Y) in the following way:

Y=f(T, C, S, E)

In this case T is stated in absolute values and C, S, E are stated as percentages. Two models are commonly used for the dis-composition of a time series into its components. According to additive model time series can be expressed as Y=T+C+S+E and according to multiplication model Y=T x C x S x E. The multipli­cation model assume in more realistic way that C, S, and E are proportional to the trend level of sales.

The time series projection does not take into considera­tion effect of marketing programmes, which must be built into the final forecast, but for most companies the time-series projection in the objective and quantitative method most frequently used. This type of model has gained its greater acceptance is business concerns.

(ii) Statistical projections:

Time series projection treats past and future sales of any product as a function of period of time, rather than of any authentic demand factors. Various real factors also affect the sale of any product. A statistical projection is a correlation bet­ween past sales and various factors relating to market demand.

The concern tries to discover the most important factors affecting the sales of a product and to understand how these factors can be predicted and related to future sales. This method brings out hidden relationship that the organization had not thought to consider but that may have an important impact on sales.

The factors related to consumer, which are most commonly analyzed are income, population, price-levels and promotion expenditures. The basic formula for statistical demand analysis is as follows:

Y=f(X₁, X₂, X₃…… X_n)

Here the procedure consists of expressing sales (Y) as a dependent variable and trying to explain sales variation as a consequence of variation in a number of independent demand variables X₁, X_2…. X₃ . . . X_n. The demand equations are derived by trying to fit the ‘best equation’ to historical data. This method is easy, economical, reliable and conspicuous but to find out economic indicators of related sales is much difficult and we cannot apply this method for new products.

III. Market testing approach:

Under this approach for testing market the product is sold for a definite period of time under actual conditions. The goal of market testing is to validate the results obtained from prototype testing and early consumer research by prolonging these results to a representative sample of the market.

Test marketing is the stage where all the product and marketing plans is tried out for the first time in a small number of well chosen and authentic sales environments. Thus the sales forecast is made for a year on the basis of the result obtained from a real sale in a part of the market.

This method is more suitable for new products and the can sure of the market can also be removed because the real position of the market is known to the executives. We may thus, conclude that sales forecast determines the expected level of sales based on a chosen marketing plan and environmental conditions.

Sales forecast is the core of the arch of structure of modern marketing research. For marketing department accurate and authentic sales forecast is the key to the planning of promotion policies, to management of inputs for reallocation of sales territories and quota for establishing control and incentives to reducing marketing risk, for setting budgetary contrivances and to all other activities of marketing.

Adequate marketing planning will become essential quanon for integrated marketing action. Since the gigantic mansion of market planning is fabricated on the support of sales forecast­ing, it seems palpable that for developing more adequate and reliable sales forecasts, a growing amount of time and money will be invested by organizations.

Sales are forecasted on the basis of historical data and various changing factors. At present in our developing economy it is difficult to forecast the future tendencies.

Generally these- forecasting are made by some specialized agencies. From opera­tional point of view permanent staff should be appointed for MR and sales forecasting so that they will be known about each and every factor and authentic results can be expected. On the place of moment research for market measurement continuous information flow is needed.