Demand Forecasting CA Foundation Notes | EduRev

Business Economics for CA Foundation

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DEMAND FORECASTING 
Meaning : Forecasting, in general, refers to knowing or measuring the status or nature of an event or variable before it occurs. Forecasting of demand is the art and science of predicting the probable demand for a product or a service at some future date on the basis of certain past behaviour patterns of some related events and the prevailing trends in the present. It should be kept in mind that demand forecasting is no simple guessing, but it refers to estimating demand scientifically and objectively on the basis of certain facts and events relevant to forecasting.
Usefulness 
The significance of demand or sales forecasting in the context of business policy decisions can hardly be over emphasized. The effectiveness of the plans of business managers depends upon the level of accuracy with which future events can be predicted. Forecasting of demand plays a vital role in the process of planning and decision-making, whether at the national level or at the level of a firm. The importance of demand forecasting has increased all the more on account of mass production and production in response to demand. A good forecast enables the firm to perform efficient business planning. Forecasts offer information for budgetary planning and cost control in functional areas of finance and accounting. Good forecasts help in efficient production planning, process selection, capacity planning, facility layout and inventory management. A firm can plan production scheduling well in advance and obtain all necessary resources for production such as inputs, and finances. Capital investments can be aligned to demand expectations and this will check the possibility of overproduction and underproduction, excess of unused capacity and idle resources. Marketing relies on sales forecasting in making key decisions. Demand forecasts also provide the necessary information for formulation of suitable pricing and advertisement strategies.
It is said that no forecast is completely fool-proof and correct. However, the very process of forecasting helps in evaluating various forces which affect demand and is in itself a reward because it enables the forecasting authority to know about various forces relevant to the study of demand behaviour.
Scope of Forecasting 
Demand forecasting can be at the international level depending upon the area of operation of the given economic institution. It can also be confined to a given product or service supplied by a small firm in a local area. The scope of the forecasting task will depend upon the area of operation of the firm in the present as well as what is proposed in future. Much would depend upon the cost and time involved in relation to the benefit of the information acquired through the study of demand. The necessary trade-off has to be struck between the cost of forecasting and the benefits flowing from such forecasting.
Types of forecasts
(1) Macro-level forecasting deals with the general economic environment prevailing in the economy as measured by the Index of Industrial Production (IIP), national income and general level of employment etc.
(ii) Industry- level forecasting is concerned with the demand for the industry’s products as a whole. For example, demand for cement in India.
(iii) Firm- level forecasting refers to forecasting the demand for a particular firm’s product, say, the demand for ACC cement.
(2) Based on time period, demand forecasts may be short-term demand forecasting and long-term demand forecasting.
(i) Short-term demand forecasting covers a short span of time, depending of the nature of industry. It is done usually for six months or less than one year and is generally useful in tactical decisions.
(ii) Long-term forecasts are for longer periods of time, say two to five years and more. It provides information for major strategic decisions of the firm such as expansion of plant capacity.
Demand Distinctions 
Business managers should have a clear understanding of the kind of demand which their products have. Before we analyse the different methods of forecasting demand, it is important for us to understand the demand distinctions which are as follows:
a) Producer’s goods and Consumer’s goods
b) Durable goods and Non-durable goods
c) Derived demand and Autonomous demand
d) Industry demand and Company demand
e) Short-run demand and Long-run demand

a) Producer’s goods and Consumer’s goods : Producer’s goods are those which are used for the production of other goods - either consumer goods or producer goods themselves. Examples of such goods are machines, plant and equipments. Consumer’s goods are those which are used for final consumption. Examples of consumer’s goods are readymade clothes, prepared food, residential houses, etc.
b) Demand for Durable goods and Non-durable goods : Goods may be further sub-divided into durable and non-durable goods. Non durable goods are those which cannot be consumed more than once. Raw materials, fuel and power, packing items etc are examples of non durable producer goods. Beverages, bread, milk etc are examples of non-durable consumer goods. These will meet only the current demand. On the other hand, durable goods do not quickly wear out, can be consumed more than once and yield utility over a period of time. Examples of durable consumer goods are: cars, refrigerators and mobile phones. Building, plant and machinery, office furniture etc are durable producer goods. The demand for durable goods is likely to be derived demand. Further, there are semi-durable goods such as, clothes and umbrella.
c) Derived demand and Autonomous demand : The demand for a commodity that arises because of the demand for some other commodity called ‘parent product’, ‘is called derived demand. For example, the demand for cement is derived demand, being directly related to building activity. In general, the demand for producer goods or industrial inputs is derived demand. Also the demand for complementary goods is derived demand. If the demand for a product is independent of the demand for other goods, then it is called autonomous demand. It arises on its own out of an innate desire of the consumer to consume or to possess the commodity. But this distinction is purely arbitrary and it is very difficult to find out which product is entirely independent of other products.
d) Demand for firm’s product and industry demand : The term industry demand is used to denote the total demand for the products of a particular industry, e.g. the total demand for steel in the country. On the other hand, the demand for firm’s product denotes the demand for the products of a particular firm, i.e. the quantity that a firm can dispose of at a given price over a period of time. E.g. demand for steel produced by the Tata Iron and Steel Company. The demand for a firm’s product when expressed as a percentage of industry demand signifies the market share of the firm.
e) Short-run demand and Long-run demand : This distinction is based on time period. Short-run demand refers to demand with its immediate reaction to changes in product price and prices of related commodities, income fluctuations, ability of the consumer to adjust their consumption pattern, their susceptibility to advertisement of new products etc. Long-run demand refers to demand which exists over a long period. Most generic goods have long- term demand. Long term demand depends on long-term income trends, availability of substitutes, credit facilities etc. In short, long-run demand is that which will ultimately exist as a result of changes in pricing, promotion or product improvement, after enough time is allowed to let the market adjust to the new situation. For example, if electricity rates are reduced, in the short run, the existing users will make greater use of electric appliances. In the long-run, more and more people will be induced to use electric appliances. The above distinction is important because each of these goods exhibit distinctive characteristics which should be taken into account while analysing demand for them.
Factors affecting demand for non-durable consumer goods: There are three basic factors which influence the demand for these goods:
(i) Disposable income: Other things being equal, the demand for a commodity depends upon the disposable income of the household. Disposable income is found out by deducting personal taxes from personal income.
(ii) Price: Other things being equal, the demand for a commodity depends upon its own price and the prices of related goods (its substitutes and complements). While the demand for a good is inversely related to its own price and the price of its complements, it is positively related to the price of its substitutes.
(iii) Demography: This involves the characteristics of the population, human as well as non-human, using the product concerned. For example, it may pertain to the number and characteristics of children in a study of demand for toys and characteristics of automobiles in a study of the demand for tyres or petrol.
Non-durables are purchased for current consumption only. From a business firm’s point of view, demand for non-durable goods gets repeated depending on the nature of the non durable goods. Usually, non durable goods come in wide varieties and there is competition among the sellers to acquire and retain customer loyalty.

Factors affecting the demand for durable-consumer goods: Demand for durable goods has certain special characteristics. Following are the important factors that affect the demand for durable goods.
(i) A consumer can postpone the replacement of durable goods. Whether a consumer will go on using the good for a long time or will replace it depends upon factors like his social status, prestige, level of money income, rate of obsolescence etc.
(ii) These goods require special facilities for their use e.g. roads for automobiles, and electricity for refrigerators and radios. The existence and growth of such factors is an important variable that determines the demand for durable goods
(iii) As consumer durables are used by more than one person, the decision to purchase may be influenced by family characteristics like income of the family, size, age distribution and sex composition. Likely changes in the number of households should be considered while determining the market size of durable goods.
(iv) Replacement demand is an important component of the total demand for durables. Greater the current holdings of durable goods, greater will be the replacement demand. Therefore, all factors that determine replacement demand should be considered as a determinant of the demand for durable goods.
(v) Demand for consumer durables is very much influenced by their prices and credit facilities available to buy them. 

Factors affecting the demand for producer goods: Since producers’ goods or capital goods help in further production, the demand for them is derived demand, derived from the demand of consumer goods they produce. The demand for them depends upon the rate of profitability of user industry and the size of the market of the user industries. Hence data required for estimating demand for producer goods (capital goods) are:
(i) growth prospects of the user industries;
(ii) norms of consumption of capital goods per unit of installed capacity  

An increase in the price of a substitutable factor of production, say labour, is likely to increase the demand for capital goods. On the contrary, an increase in the price of a factor which is complementary may cause a decrease in the demand for capital.
Higher the profit making prospects, greater will be the inducement to demand capital goods. If firms are optimistic about selling a higher output in future, they will have greater incentive to invest in producer goods. Advances in technology enabling higher efficiency at reduced cost on account of higher productivity of capital will have a positive impact on investment in capital goods. Investments in producer goods will be greater when lower interest rates prevail as firms will have lower opportunity cost of investments and lower cost of borrowing. 

Methods of demand Forecasting
There is no easy method or simple formula which enables an individual or a business to predict the future with certainty or to escape the hard process of thinking. The firm has to apply a proper mix of judgment and scientific formulae in order to correctly predict the future demand for a product. The following are the commonly available techniques of demand forecasting:
(i) Survey of Buyers’ Intentions: The most direct method of estimating demand in the short run is to ask customers what they are planning to buy during the forthcoming time period, usually a year. This method involves direct interview of potential customers. Depending on the purpose, time available and costs to be incurred, the survey may be conducted by any of the following methods:
 a) Complete enumeration method where nearly all potential customers are interviewed about their future purchase plans
 b) Sample survey method under which only a scientifically chosen sample of potential customers are interviewed
 c) End–use method, especially used in forecasting demand for inputs, involves identification of all final users, fixing suitable technical norms of consumption of the product under study, application of the norms to the desired or targeted levels of output and aggregation.
Thus, under this method the burden of forecasting is put on the customers. However, it would not be wise to depend wholly on the buyers’ estimates and they should be used cautiously in the light of the seller’s own judgement. A number of biases may creep into the surveys. The customers may themselves misjudge their requirements, may mislead the surveyors or their plans may alter due to various factors which are not identified or visualised at the time of the survey. This method is useful when bulk of sale is made to industrial producers who generally have definite future plans. In the case of household customers, this method may not prove very helpful for several reasons viz. irregularity in customers’ buying intentions, their inability to foresee their choice when faced with multiple alternatives, and the possibility that the buyers’ plans may not be real, but only wishful thinking.
(ii) Collective opinion method: This method is also known as sales force opinion method or grass roots approach. Firms having a wide network of sales personnel can use the knowledge, experience and skills of the sales force to forecast future demand. Under this method, salesmen are required to estimate expected sales in their respective territories. The rationale of this method is that salesmen being closest to the customers are likely to have the most intimate feel of the reactions of customers to changes in the market. These estimates of salesmen are consolidated to find out the total estimated sales. These estimates are reviewed to eliminate the bias of optimism on the part of some salesmen and pessimism on the part of others. These revised estimates are further examined in the light of factors like proposed changes in selling prices, product designs and advertisement programmes, expected changes in competition and changes in secular forces like purchasing power, income distribution, employment, population, etc. The final sales forecast would emerge after these factors have been taken into account.
Although this method is simple and based on first hand information of those who are directly connected with sales, it is subjective as personal opinions can possibly influence the forecast. Moreover salesmen may be unaware of the broader economic changes which may have profound impact on future demand. Therefore, forecasting could be useful in the short run, for long run analysis however, a better technique is to be applied.
(iii) Expert Opinion method: In general, professional market experts and consultants have specialised knowledge about the numerous variables that affect demand. This, coupled with their varied experience, enables them to provide reasonably reliable estimates of probable demand in future. Information is elicited from them through appropriately structured unbiased tools of data collection such as interviews and questionnaires.
The Delphi technique, developed by Olaf Helmer at the Rand Corporation of the USA, provides a useful way to obtain informed judgments from diverse experts by avoiding the disadvantages of conventional panel meetings. Under this method, instead of depending upon the opinions of buyers and salesmen, firms solicit the opinion of specialists or experts through a series of carefully designed questionnaires. Experts are asked to provide forecasts and reasons for their forecasts. Experts are provided with information and opinion feedbacks of others at different rounds without revealing the identity of the opinion provider. These opinions are then exchanged among the various experts and the process goes on until convergence of opinions is arrived at. This method is best suited in circumstances where intractable changes are occurring and the relevant knowledge is distributed among experts. Delphi technique is widely accepted due to its broader applicability and ability to address complex questions. It also has the advantages of speed and cheapness.
(iv) Statistical methods: Statistical methods have proved to be very useful in forecasting demand. Forecasts using statistical methods are considered as superior methods because they are more scientific, reliable and free from subjectivity. The important statistical methods of demand forecasting are:
 (a) Trend Projection method: This method, also known classical method, is considered as a ‘naive’ approach to demand forecasting. A firm which has been in existence for a reasonably long time would have accumulated considerable data on sales pertaining to dierent time periods. Such data, when arranged chronologically, yield a ‘time series’. The time series relating to sales represent the past pattern of effective demand for a particular product. Such data can be used to project the trend of the time series. The trend projection method assumes that factors responsible for the past trend in demand will continue to operate in the same manner and to the same extent as they did in the past in determining the magnitude and direction of demand in future. The popular techniques of trend projection based on time series data are;
a) graphical method and
b) Fitting trend equation or least square method 

(b) Graphical Method: This method, also known as ‘free hand projection method’ is the simplest and least expensive. This involves plotting of the time series data on a graph paper and fitting a freehand curve to it passing through as many points as possible. The direction of the curve shows the trend. This curve is extended into the future for deriving the forecasts. The direction of this free hand curve shows the trend. The main draw-back of this method is that it may show the trend but the projections made through this method are not very reliable.
(c) Fitting trend equation: Least Square Method: It is a mathematical procedure for fitting a line to a set of observed data points in such a manner that the sum of the squared differences between the calculated and observed value is minimised. This technique is used to find a trend line which best fit the available data. This trend is then used to project the dependant variable in the future. This method is very popular because it is simple and inexpensive. Moreover, the trend method provides fairly reliable estimates of future demand. The least square method is based on the assumption that the past rate of change of the variable under study will continue in the future. The forecast based on this method may be considered reliable only for the period during which this assumption holds. The major limitation of this method is that it cannot be used where trend is cyclical with sharp turning points of troughs and peaks. Also, this method cannot be used for short term forecasts.
(d) Regression analysis: This is the most popular method of forecasting demand. Under this method, a relationship is established between the quantity demanded (dependent variable) and the independent variables (explanatory variables) such as income, price of the good, prices of related goods etc. Once the relationship is established, we derive regression equation assuming the relationship to be linear. The equation will be of the form Y = a + bX. There could also be a curvilinear relationship between the dependent and independent variables. Once the regression equation is derived, the value of Y i.e. quantity demanded can be estimated for any given value of X. 


(v) Controlled Experiments: Under this method, future demand is estimated by conducting market studies and experiments on consumer behaviour under actual, though controlled, market conditions. This method is also known as market experiment method. An effort is made to vary separately certain determinants of demand which can be manipulated, for example, price, advertising, etc., and conduct the experiments assuming that the other factors would remain constant. Thus, the effect of demand determinants like price, advertisement, packaging, etc., on sales can be assessed by either varying them over different markets or by varying them over different time periods in the same market. The responses of demand to such changes over a period of time are recorded and are used for assessing the future demand for the product. For example, different prices would be associated with different sales and on that basis the price-quantity relationship is estimated in the form of regression equation and used for forecasting purposes. It should be noted however, that the market divisions here must be homogeneous with regard to income, tastes, etc.
The method of controlled experiments is used relatively less because this method of demand forecasting is expensive as well as time consuming. Moreover, controlled experiments are risky too because they may lead to unfavourable reactions from dealers, consumers and competitors. It is also difficult to determine what conditions should be taken as constant and what factors should be regarded as variable so as to segregate and measure their influence on demand. Besides, it is practically difficult to satisfy the condition of homogeneity of markets.
Market experiments can also be replaced by ‘controlled laboratory experiments’ or ‘consumer clinics’ under which consumers are given a specified sum of money and asked to spend in a store on goods with varying prices, packages, displays etc. The responses of the consumers are studied and used for demand forecasting.

(vi) Barometric method of forecasting: The various methods suggested till now are related with the product concerned. These methods are based on past experience and try to project the past into the future. Such projection is not effective where there are economic ups and downs. As mentioned above, the projection of trend cannot indicate the turning point from slump to recovery or from boom to recession. Therefore, in order to find out these turning points, it is necessary to find out the general behaviour of the economy. Just as meteorologists use the barometer to forecast weather, the economists use economic indicators to forecast trends in business activities. This information is then used to forecast demand prospects of a product, though not the actual quantity demanded. For this purpose, an index of relevant economic indicators is constructed. Movements in these indicators are used as basis for forecasting the likely economic environment in the near future. There are leading indicators, coincidental indicators and lagging indicators. The leading indicators move up or down ahead of some other series. For example, the heavy advance orders for capital goods give an advance indication of economic prosperity. The lagging indicators follow a change after some time lag. The heavy household electrical connections confirm the fact that heavy construction work was undertaken during the past with a lag of some time. The coincidental indicators, however, move up and down simultaneously with the level of economic activities. For example, rate of unemployment.

SUMMARY 
  • Buyers constitute the demand side of the market; sellers make the supply side of that market. The quantity that consumers buy at a given price determines the size of the market.
  • Demand means desire or wish to buy and consume a commodity or service backed by adequate ability to pay and willingness to pay.
  • The important factors that determine demand are price of the commodity, price of related commodities, income of the consumer, tastes and preferences of consumers, consumer expectations regarding future prices, size of population, composition of population, the level of national income and its distribution, consumer-credit facility and interest rates.
  • The law of demand states that people will buy more at lower prices and less at higher prices, other things being equal.
  • A demand schedule is a table that shows various prices and the corresponding quantities demanded. The demand schedules are of two types; individual demand schedule and market demand schedule.
  • According to Marshall, the demand curve slopes downwards due to the operation of the law of diminishing marginal utility. However, according to Hicks and Allen it is due to income effect and substitution effect.
  • The demand curve usually slopes downwards; but exceptionally slopes upwards under certain circumstances as in the case of conspicuous goods, Giffen goods, conspicuous necessities, future expectations about prices, etc.
  • Other things being equal, when the price rises and as a response, the quantity demanded decreases, it is contraction of demand. On the contrary, when the price falls and the quantity demanded increases it is extension of demand.
  • The demand curve will shift to the right when there is a rise in income (unless the good is an inferior one), a rise in the price of a substitute, a fall in the price of a complement, a rise in population and a change in tastes in favour of commodity. The opposite changes will shift the demand curve to the left.
  • Elasticity of demand refers to the degree of sensitiveness or responsiveness of demand to a change in any one of its determinants. Elasticity of demand is classified mainly into four kinds. They are price elasticity of demand, income elasticity of demand, advertisement elasticity and cross elasticity of demand.
  • Price elasticity of demand refers to the percentage change in quantity demanded of a commodity as a result of a percentage change in price of that commodity. Because demand curve slopes downwards and to the right, the sign of price elasticity is negative. We normally ignore the sign of elasticity and concentrate on the coefficient. Greater the absolute coefficient, greater is the price elasticity.
  • In point elasticity, we measure elasticity at a given point on a demand curve. When the price change is somewhat larger or when price elasticity is to be found between two prices or two points on the demand curve, we use arc elasticity
  • Income elasticity of demand is the percentage change in quantity demanded of a commodity as a result of a percentage change in income of the consumer. Goods and services are classified as luxuries, normal or inferior, depending on the responsiveness of spending on a product relative to percentage change in income.
  • The cross elasticity of demand is the percentage change in the quantity demanded of commodity X as a result of a percentage change in the price of some related commodity Y. Products can be substitutes, and their cross elasticity is then positive; cross elasticity is negative for products that are complements.
  • Advertisement elasticity of sales or promotional elasticity of demand measures the responsiveness of a good’s demand to changes in the firm’s spending on advertising.
  • Forecasting of demand is the art and science of predicting the probable demand for a product or a service at some future date on the basis of certain past behaviour patterns of some related events and the prevailing trends in the present.
  • The commonly available techniques of demand forecasting are survey of buyers’ intentions, collective opinion method, expert opinion method, barometric method, and statistical methods such as trend projection method, graphical method, least square method, regression analysis, and market studies such as controlled experiments, and controlled laboratory experiments,



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