FORECASTING TECHNIQUES

Forecasting technique can be classified into two major categories:

(i) Qualitative forecasting technique.

(ii) Quantitative forecasting technique. 

  • Qualitative Techniques

1. Jury or Executive opinion (Dolphi Technique)

2. Sales force estimates.

3. Customer expectations. 

  • Jury or Executive Opinion

The jury of expert opinion sometimes referred to as the Dolphi technique; involves soliciting opinions or estimates from a panel of “experts” who are knowledgeable about the variable being forecasted. In addition to being useful in the creation of a sales or demand forecast this approach is used to predict future technological developments. This method is fast less expensive and does not depend upon any elaborate statistics and brings in specialized viewpoints. 

  • Sales Force Estimates

This approach involves the opinion of the sales force and these opinions are primarily taken into consideration for forecasting future sales. The sales people, being closer to consumers, can estimate future sales in their own territories more accurately. Based on these and the opinions of sales managers, a reasonable trend of the future sales can be calculated. These forecasts are good for short range planning since sales people are not sufficiently sophisticated to predict long-term trends. This method known as the “grass roots” approach lends itself to easy breakdowns of products, territory, customer etc., which makes forecasting more elaborate and comprehensive.

  • Customer Expectations

This type of forecasting technique is to go outside the company and seeksubjective opinions from customers about their future purchasing plans. Salesrepresentatives may poll their customers or potential customers about the future needsfor the goods and services the company supplies. Direct mail questionnaires ortelephone surveys may be used to obtain the opinions of existing or potential customers.This is also known as the “survey method” or the “marketing research method” whereInformation is obtained concerning. Customer buying preferences, advertisingeffectiveness and is especially useful where the target market is small such as buyers ‘ofindustrial products, and where the customers are co-operative.

7.8.2 Quantitative Techniques 

Quantitative techniques are based on the analysis of past data and its trends.

These techniques use statistical analysis and other mathematical models to predict futureevents. Some of these techniques are:

1. Time series analysis.

2. Economic models.

3. Regression analysis.

Time Series Analysis 

Time series analysis involves decomposition of historical series into its variouscomponents, viz., trend, seasonal variations, cyclical variations and random variations.Time series analysis uses index numbers but it is different from barometric technique. In barometric technique, the future is predicted from the indicating series, which servebarometers of economic change. In time series analysis, the future is taken as some sortof an extension of the past. When the various components of a time series are separated,the variations of a particular phenomenon, the subject under study stay say price, can beknown over the period of time and projection can be made about future. A trend can beknown over the period of time, which may be true for future also. However, time seriesanalysis should be used as a basis for forecasting when data are available for a longperiod of time and tendencies disclosed by the trend and seasonal factors are fairly clearand stable.

Economic Models 

Utilize a system of interdependent regression equations that relate certaineconomic indicators of the firm’s sales, profits etc. Data center or external economicfactors and internal business factors interpreted with statistical methods. Oftencompanies use the results of national or regional econometric models as a major portionof a corporate econometric model. While such models are useful in forecasting, theirmajor use tends to be in answering “what if”? Questions. These models allowmanagement to investigate and in major segments of the company’s business on theperformance and sales of the company.

Regression Analysis 

Regression Analysis are statistical equations designed to estimate some variablessuch as sales volume, on the basis of one or more ‘independent’ variables believed tohave some association with it.