Methods of Sales Forecasting

Following are the methods generally employed for sales forecasting:

1. Survey of Buyers’ Views

This is direct method for making forecasting for short-term, in which the customers are asked what they are thinking to buy in near future say, in the coming year. In this method all the burden is with consumers, which may misjudge or mislead or may be uncertain about the quantity to be purchased by them in near future.

The disadvantages of this method are as follows:

• Consumer’s buying intentions are irregular.
• When consumers have to select between different alternatives, they are unable to foresee their choices.
• Buyers may be anxious for purchasing the products but due to certain limitations they may be unable to purchase them.

2. Collective Opinion or Sales Force Polling

In this method forecasting depends upon the salesman’s estimation for their respective areas, because the sales-man are closest to the customers, hence can estimate more properly about the consumers’ reaction about the product and their future requirements.

All the estimates of salesmen are consolidated to know the total estimate of the sales. This final estimate then goes through severs checking to avoid undue imagination which is done many times by the salesmen.

The revised estimates are then again examined in the light of factors like expected change in design, change in prices, advertisements, competition, purchasing power of local people, employment, population etc.

This method of collective opinion takes advantages of collective wisdom of salesmen, senior executives like production manager, sales manager, marketing officials and managers.

Advantage of Collective Opinion or Sales Force Polling

• This method is simple and requires no statistical technique.
• The forecasts are based on the knowledge of salesmen, who are directly responsible for the sales.
• In practice, this method is much useful in the case of new products.

Disadvantage of Collective Opinion or Sales Force Polling

• This method is useful only for short-term forecasting, i.e. maximum for one year.
• As the forecasting is dependent upon the salesmen’s estimation and if sales quotas are fixed then they, in general under-estimate the forecast.
• As Salesmen have no knowledge about the economic changes, the estimate by them are not so correct many times.
• As the estimation is full time job, the quality to look into the future must be with the salesmen.

3. Trend Projections

Well-established firms which have considerable data on sales, these data are arranged in a chronological order, known as ‘time series’. Thus ‘time series’ are analysed before making the forecasts.

There is a common method known as ‘Project the trend’. In this method the trend line is projected by some statistical method, generally, by least square method.

The time series forecasts are the demand characteristics over time. These time series data are analysed for forecasting future activity levels. Time series data refer to a set of values of some variables measured at the equally spaced time intervals such as monthly production levels, demands in the market etc.

The demands have following patterns:

(i) Constant Pattern

In this pattern demand remains constant throughout the period.

(ii) Trend Pattern

It refers to the long-term growth or decline in the average level of demand.

(iii) Seasonal Pattern

It refers to the annually repetitive demand fluctuation that may be caused by weather, tradition or other factors.

(iv) Cycle Pattern

Business cycle refers to the large deviation to actual demand values due to complex environmental influences. These are similar to the seasonable components except that seasonality occurs at regular intervals and is of constant durations whereas it varies in both time and duration of occurrence.

(v) Combination of Different Pattern

In long term forecast (more than 2 years) seasonal factors are ignored and focus is given on trend component with a minor emphasis on business cycle. In medium term forecasts (few months to 2 years), the trend factor becomes less important and the seasonal and random factors are given more importance.