Demand Forecasting: Need, Objectives and Methods

 

Some of the popular definitions of demand forecasting are as follows:

According to Evan J. Douglas, “Demand estimation (forecasting) may be defined as a process of finding values for demand in future periods.”

In the words of Cundiff and Still, “Demand forecasting is an estimate of sales during a specified future period based on the proposed marketing plan and a set of particular uncontrollable and competitive forces.”

Demand forecasting enables an organization to take various business decisions, such as planning the production process, purchasing raw materials, managing funds, and deciding the price of the product. An organization can forecast demand by making its own estimates called guess estimates or by taking the help of specialized consultants or market research agencies.

Need of Demand Forecasting

Demand plays a crucial role in the management of every business. It helps an organization to reduce risks involved in business activities and make important business decisions. Apart from this, demand forecasting provides insight into the organization’s capital investment and expansion decisions.

(i) Fulfilling objectives

Implies that every business unit starts with certain pre-decided objectives. Demand forecasting helps in fulfilling these objectives. An organization estimates the current demand for its products and services in the market and moves forward to achieve the set goals.

For example, an organization has set a target of selling 50, 000 units of its products. In such a case, the organization would perform demand forecasting for its products. If the demand for the organization’s products is low, the organization would take corrective actions, so that the set objective can be achieved.

(ii) Preparing the budget

Plays a crucial role in making a budget by estimating costs and expected revenues. For instance, an organization has forecasted that the demand for its product, which is priced at Rs. 10, would be 10, 00, 00 units. In such a case, the total expected revenue would be 10* 100000 = Rs. 10, 00, 000. In this way, demand forecasting enables organizations to prepare their budget.

(iii) Stabilizing employment and production

Helps an organization control its production and recruitment activities. Producing according to the forecasted demand of products helps in avoiding the wastage of the resources of an organization. This further helps an organization to hire human resources according to requirements. For example, if an organization expects a rise in the demand for its products, it may opt for extra labour to fulfil the increased demand.

(iv) Expanding organizations

Implies that demand forecasting helps in deciding about the expansion of the business of the organization. If the expected demand for products is higher, then the organization may plan to expand further. On the other hand, if the demand for products is expected to fall, the organization may cut down the investment in the business.

(v) Taking Management Decisions

Helps in making critical decisions, such as deciding the plant capacity, determining the requirement of raw material, and ensuring the availability of labour and capital.

(vi) Evaluating Performance

Helps in making corrections. For example, if the demand for an organization’s products is less, it may take corrective actions and improve the level of demand by enhancing the quality of its products or spending more on advertisements.

(vii) Helping the Government

Enables the government to coordinate import and export activities and plan international trade.

Objectives of short-term demand forecasting 

  • Production policy: Short-term demand forecasting is used to evolve a suitable production policy which can avoid the problems of overproduction and short supply.

  • Expenditure pattern: It helps the firm in purchasing. Knowledge of near-future economic conditions helps the firm in reducing the costs of purchasing raw materials and controlling inventory.

  • Sales policy: Demand forecasting helps the firm in evolving a suitable sales policy.

  • Price policy: Sales forecasting is useful in determining pricing policy. When the market conditions are expected to be weak, the firm can avoid a price increase and vice-versa.

  • Sales targets, controls and incentives: Short-term demand forecasting is used to set sales targets and for establishing controls and incentives.

  • Financial requirements: It is useful in forecasting short-term financial requirements. Cash requirement depends on production and sales levels. Hence sales forecasts help the firm to make arrangements for necessary funds well in advance.

Objectives of long-term demand forecasting 

  1. New unit or expansion: Long-term demand forecasting helps in the planning of a new unit or expansion of an existing unit of a business organization.

  2. Financial requirements: It is useful in long-term financial planning. The long-term sales forecast is necessary to estimate long-term financial requirements.

  3. Manpower planning: Long-term demand forecasting enables the firm to make arrangements for training and personnel development. Demand forecasting is also useful to the Government in determining import and export policies.

Objectives Of Demand Forecasting In Business Economics are well recognized by business organizations that want to produce goods at optimum levels. The objectives of short-term demand forecasting are different from those of long-term demand forecasting.

Methods of Demand Forecasting

There is no easy or simple formula to forecast the demand. Proper judgment along with the scientific formula is needed to correctly predict the future demand for a product or service. Some methods of demand forecasting are discussed below:

1. Survey of Buyer’s Choice

When the demand needs to be forecasted in the short run, say a year, then the most feasible method is to ask the customers directly what are they intending to buy in the forthcoming period. Thus, under this method, the potential customers are directly interviewed. This survey can be done in any of the following ways:

  • Complete Enumeration Method: Under this method, nearly all potential buyers are asked about their future purchase plans.

  • Sample Survey Method: Under this method, a sample of potential buyers are chosen scientifically and only those chosen are interviewed.

  • End-use Method: It is especially used for forecasting the demand for the inputs. Under this method, the final users i.e. the consuming industries and other sectors are identified. The desirable norms of consumption of the product are fixed, the targeted output levels are estimated and these norms are applied to forecast the future demand for the inputs.

Hence, it can be said that under this method the burden of demand forecasting is on the buyer. However, the judgments of the buyers are not completely reliable and so the seller should take decisions in the light of his judgment also.

The customer may misjudge their demands and may also change their decisions in the future which in turn may mislead the survey. This method is suitable when goods are supplied in bulk to industries but not in the case of household customers.

2. Collective Opinion Method

Under this method, the salesperson of a firm predicts the estimated future sales in their region. The individual estimates are aggregated to calculate the total estimated future sales. These estimates are reviewed in light of factors like future changes in the selling price, product designs, changes in competition, advertisement campaigns, the purchasing power of the consumers, employment opportunities, population, etc.

The principle underlying this method is that as the salesmen are closest to the consumers they are more likely to understand the changes in their needs and demands. They can also easily find out the reasons behind the change in their tastes.

Therefore, a firm having good sales personnel can utilize their experience to predict the demands. Hence, this method is also known as the Salesforce opinion or Grassroots approach method. However, this method depends on the personal opinions of the sales personnel and is not purely scientific.

3. Barometric Method

This method is based on the past demands of the product and tries to project the past into the future. The economic indicators are used to predict the future trends of the business. Based on future trends, the demand for the product is forecasted. An index of economic indicators is formed. There are three types of economic indicators, viz. leading indicators, lagging indicators, and coincidental indicators.

The leading indicators are those that move up or down ahead of some other series. The lagging indicators are those that follow a change after some time lag. The coincidental indicators are those that move up and down simultaneously with the level of economic activities.

4. Market Experiment Method

Another method of demand forecasting is the market experiment method. Under this method, the demand is forecasted by conducting market studies and experiments on consumer behaviour under actual but controlled, market conditions.

Certain determinants of demand that can be varied are changed and the experiments are done keeping other factors constant. However, this method is very expensive and time-consuming.

5. Expert Opinion Method

Usually, market experts have explicit knowledge about the factors affecting demand. Their opinion can help in demand forecasting. The Delphi technique, developed by Olaf Helmer is one such method.

Under this method, experts are given a series of carefully designed questionnaires and are asked to forecast the demand. They are also required to give suitable reasons. The opinions are shared with the experts to arrive at a conclusion. This is a fast and cheap technique.

6. Statistical Methods

The statistical method is one of the important methods of demand forecasting. Statistical methods are scientific, reliable and free from biases. The major statistical methods used for demand forecasting are:

  • Trend Projection Method: This method is useful where the organization has a sufficient amount of accumulated past data on sales. This date is arranged chronologically to obtain a time series. Thus, the time series depicts the past trend and based on it, the future market trend can be predicted. It is assumed that the past trend will continue in future. Thus, based on the predicted future trend, the demand for a product or service is forecasted.

  • Regression Analysis: This method establishes a relationship between the dependent variable and the independent variables. In our case, the quantity demanded is the dependent variable and income, the price of goods, the price of related goods, the price of substitute goods, etc. are independent variables. The regression equation is derived assuming the relationship to be linear. Regression Equation: Y = a + bX. Where Y is the forecasted demand for a product or service.

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