FYBCOM Economics Sem 1 Chapter 4 Notes | FYBAF | FYBMS | Mumbai University

FYBCOM Economics Sem 1 Chapter 4 Notes
(Demand Estimation and Forecasting)

1) What is demand forecasting? Explain its importance.

Answer: Demand forecasting means estimation of demand for the product for a future period. Demand forecasting enables an organization to take various decisions in business, such as planning about production process, purchasing of raw materials, managing funds in the business, and determining the price of the commodity.

A business organization can forecast demand for his product by making own estimations called guess or by taking the help of specialized consultants or market research agencies. Thus, a demand forecasting is meant to guide business policy decision. The significance of demand forecasting are as follows:

1. Fulfils the objective: Demand forecasting implies that every business unit starts with certain pre-determined objectives.
   Demand forecasting helps in fulfilling these objectives. An organization estimates the current demand for its products and
   services in the market and move forward to achieve the set goals.
2. Production planning: Demand forecasting is important to forecast the future production plan of business firm. There is a gestation period between production of goods and services and demand for it. Demand forecasting help to eliminate those gaps
   between demand and supply of goods preventing shortages and surplus.
3. Distribution and avoidance of wastage of resources planning: The business firm has to take decision regarding the distribution of capital, machinery, raw material in the production process. So that if there is any shortage of those resources can
   be arranged prior through estimation. Making a right and correct estimation of using resources reduces the usage of it.
4. Sales distribution policy: Sales of goods and service gives revenue to the firm’s demand. Forecasting is nothing but estimating the sales of the product. To formulate realistic sales targets and to make arrangements for the movement of production for the movement of product region wise, demand forecasting is very essential. This can help to formulate an effective sales policy, and therefore, to increase sales revenue.
5. Price policy: The firm has to make decision regarding the price of goods and services which is a critical job. The firm has to
   make appropriate price policy so that there is no price fluctuation in the future.
6. Reduce business risk: Every business has certain risk. Demand forecasting help the business firm to make appropriate business decision to reduce such risk and uncertainty to a certain extent.
7. Inventory planning: Inventories are goods and raw materials held by the firm future sale. Demand forecasting helps in devising appropriate inventory management policies.

2) Discuss the steps to be taken to estimate demand forecasting.

Answer: The demand forecasting finds its significance during largescale production of goods and services. During such period of time firms may often face difficulties in obtaining a fairly accurate m estimation of future demand. Thus, it is essential for a firm tomforecast demand systematically and scientifically to arrive at desired objective. Therefore, the following steps are to be taken to facilitate a systematic demand forecasting:

1. Determining the objective: The very first step in demand forecasting is to determine its objective of forecasting. The objective for which the demand forecasting is to be done must be clearly specified. The objective of forecasting may be defined in terms of; long-term or short-term demand, the whole or only the segment of a market for a firm’s product, overall demand for a product or only for a firm’s own product, firm’s overall market share in the industry, etc. The objective of the demand must be determined prior in the process of demand forecasting begins as it will give direction to the whole research.
2. Nature of forecast: After determining the objective of forecasting the second important step is to identified the nature of demand forecasting. Its based on the nature of forecasting.
3. Nature of commodity: While forecasting it is important to understand the nature of the product whether it is consumer goods or producer goods, perishable goods or durable goods. If the good is perishable the forecasting is to be done in a short period of time and for durable goods it may be done in long run.
4. Determinants of demand: Determinants of demand play an important role in determining the forecasting as different commodity have different factor determination of demand which depends upon the nature of commodity and nature of forecasting. The important determinants are price of the commodity, price of related goods, income of a consumer etc.
5. Identifying the relevant data: Necessary data for the forecasting are collected, then tabulated, analysed and crosschecked by the firm. The data are interpreted by applying various statistical or graphical techniques, and then to draw necessary deductions there from. The forecaster has to decide whether to choose primary or secondary data. The primary data are the first-hand data which has never been collected before. While the secondary data are the data already available. Often, data required is not available and hence the data are to be adjusted, even manipulated, if necessary, with a purpose to build a data consistent with the data required. Then after collecting the relevant data from different sources and proceed for the further step.
6. Selecting the method: After collecting the relevant data the firm choose the appropriate method of forecasting the demand.
   Appropriate method of sales forecasting is selected by the company considering the relevant information, purpose of forecasting and the degree of accuracy required. The choice of method has to be appropriate and logical. If the required data is not available toward the method, the forecaster may force to use less reliable method. The forecaster should use a method which should not be too time consuming and it should be reliable for long term.
7. Testing accuracy: After making a choice of method the forecaster needs to test the accuracy of it. There are various methods choose to test the accuracy. This testing helps to reduce the margin of error and thereby helps to improve its validity for the purpose of decision making
8. Evaluation and conclusion: the last and final step are to evaluate the forecasting and to draw a conclusion from it.

3) Explain the survey methods of demand forecasting.

Answer: Survey method: This method is also called as qualitative method of demand forecasting. This method is one of the most common and direct method of demand forecasting in the short run.

In this method the future purchase plans of the consumers and their aims are included.

An organization conducts these surveys with consumers to determine the demand of their existing products and services and forecast the future demand of their product accordingly.

The forecaster may undertake the following survey methods:
a) Expert’s opinion: This method is based on the opinion of expert who predict the demand for a product based on his experiences and his knowledge in the particular specialised field. The expert may be from the same organisation or may be hired from outside.

They may be salesman, sales manager, marketing expert, market consultant etc they act as experts who can assess the demand for the product in different areas, regions, or cities. This method involves the opinion of three or four experts.

Each expert will be asked about his opinion regarding the demand for the product and the expert through his personal experience give his opinion for the product and forecast the demand. This method is very simple to use and it requires less statistical work.

Due to expert’s personal views the time for forecasting is short and the cost involve is also low. On the other side as its expert’s personal opinion or guess where its likely to be biased.

b) Delphi method: Delphi method is a group decision-making technique of forecasting demand. In Delphi method, a group of experts gives their opinion on the demand for the products of individual firm in future based on questions which have been asked by the firm.

These questions are repeatedly asked until a result is obtained. In addition, each and every expert is provided information regarding the estimates made by other experts in the group, so that he/she can revise his/her estimations with respect to others’ estimates. In this way, the forecasters cross check among experts to reach more accurate decision making.

The main advantage of this method is that it is time and cost effective as a number of experts are approached in a short time without spending much time on other resources. However, this method may lead to appropriate decision making. This method allows the forecaster to solve the problem to the experts at once and have instant response. But the success of this method depends upon the skills, experience, knowledge, and aptitude of the expert.

c) Consumer survey method: In this method, the consumers are directly approached to unveil their future purchase plans. This method is the most direct method because forecasting is done by interviewing all consumers or a selected group of consumers out of the relevant population through various other methods of survey.

The firm may choose for complete enumeration method, sample survey method and end use method for sample surveys depending upon the nature of forecasting. The following methods are described in brief below:

i) Complete enumeration method: Under the Complete Enumeration Survey, the forecaster undertakes the survey of the whole population who demand for the commodity. The firm may go for a door to door survey by making questionnaire to get the data requires.

This method has an advantage of first hand data, unbiased information, yet it has its share of disadvantages also. The major limitation of this method is that it requires lot of resources, manpower and time period.

There may be a chance where the consumer or the population may give false statement or may deliberately misguide the investigators due to which there may be chance of data error. In this method, consumers may be unwilling to reveal their purchase plans due to personal privacy or commercial secrecy.

ii) Sample survey method: This method is also known as test market. In this method the forecaster selects the samples of consumer from the relevant population instead of considering the whole population. If sample is the true representative of data, there is likely to be no significant difference in the results obtained by the survey.

Apart from that, this method is less tedious and less costly then the complete enumeration method. A sample survey technique is a variant of test marketing. Product testing basically involves employing the product with a number of users for a set of periods of time.

Their reactions to the product are noted after a period of time and an estimate of likely demand is made from the result. These are suitable for new products or for completely modified old products for which there is no prior data available.

It is a more scientific method of estimating like demand because it stimulates the national launch in a very closely defined geographical area. Their can be a sampling error in this method as the size of sample is small

i.e. smaller the size of sample larger the sampling error.

iii) End-use method: This method is quite useful for industries which are mainly producer’s goods and when a product is used for more than one use. In this method, the sale of the product is projected on the basis of demand survey of the industries which are using this product as an intermediate product, that is, the demand for the final product is the end user demand of the intermediate product which are used in the production of this final product is considered.

The end use method of demand estimation of an intermediate product may involve many final good industries using this product at home and abroad. It helps us to understand inter-industry’ relations.

The major efforts required by this type of method are not in its operation but in the collection and presentation of data. This will help the forecaster to manipulate the future demand.

This policy helps the government to frame many of its policies. Its major limitations are that it requires every firm to have a plan of production correctly for the future period.

d) Market experiments: This method involves collecting necessary information regarding the current and future demand for a product in the market. This method carries out the studies and experiments on consumer behaviour under actual market conditions. In this method, some areas of markets are selected with similar features, such as income level , population, cultural and political background, and tastes of consumers.

i) Actual market experiment: This method is conducted in the actual market place in several ways. One method is to select several market or stores with similar characteristics. This method is very useful in the process of introducing a product for which no other data exist.

ii) Simulated market experiment: This method is also called as consumer clinic or laboratory experiment. Under this method the firm make a set of consumers and give them a sum of money and asked them to shop in a stimulated store.

While shopping the consumer reaction towards the change in price of a product, packaging, advertisement etc are taken into consideration.

4) Examine the statistical methods of demand forecasting.

Answer: Statistical methods: This method is also called as quantitative method. Statistical method is most useful in demand forecasting. In order to key objectivity, that is, by consideration of all implications and viewing the problem from an external point of view, the statistical methods are used to forecast the demand of the product to get the accurate solution to the problems.

The following are some statistical methods which are been used now a day:

i) Trend method: A firm existing for a long time will have its own data regarding sales for past years. Such data when arranged in a chronologically manner will yield what is referred to as ‘time series.

Time series method shows the past sales with effective demand for a particular product under normal conditions. Such data can be given in a tabular or graphic form for further analysis.

This is the most popular method among business firms, partly because it is simple and cheap and partly because time series data often show a persistent growth trend.

Time series has got four types of components namely, Secular Trend (T), Secular Variation (S), Cyclical Element (C), and an Irregular or Random Variation (I).

These time elements are expressed by the equation O = TSCI. Secular trend refers to the long run changes that occur as a result of general tendency. Seasonal variations refer to the changes in the short run weather pattern or the social habits.

Cyclical variations refer to the changes that occur in industry during a depression and boom period. Random variation refers to the factors which are generally able such as wars, strikes, natural calamities such as flood, famine and so on.

When a prediction is made the seasonal, cyclical and random variations are removed from the observed data. Thus, only the secular trend is left. This trend is then projected. Trend projection fits a trend line into a mathematical equation. The trend can be estimated by using any one of the following methods:

a) The Graphical Method: Graphical method is the simplest technique to determine the trend analysis. All values of output or sale of product for different years are plotted on a graph and a smooth free hand curve is drawn passing through as many points as possible on the graph.
The direction of this free hand curve is either upward or downward and shows the possible trend.

b) The Least Square Method: Under the least square method of forecasting, a trend line can be fitted to the time series data with the help of statistical techniques such as least square method of regression. When the trend in sales over time is given by straight line, the equation of this line is in the form of: y = a + bx.

Where ‘a’ is the intercept and ‘b’ shows the impact of the independent variable. We have taken two variables i.e. the independent variable x and the dependent variable y. The line of best fit establishes a kind of mathematical relationship between the two variables v and y. This is expressed by the regression у on x.

In order to solve the equation v = a + bx, we have to make use of the following normal equations:
Σ y = na + b ΣX
Σ xy =a Σ x+b Σ x2

ii) Regression method: regression methods attempts to assess the relationship between at least two variables (one or more independent and one dependent), the purpose is to predict the value of the dependent variable from the specific value of the independent variable.

The foundation of this prediction generally is historical data. This method starts from the assumption that a basic relationship exists between two variables. An interactive statistical analysis computer package is used to formulate this mathematical relationship.

Chapters-1–2–3–4–5–6–7–8

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