Techniques and Methods of Business Forecasting

Everything you need to know about the techniques of business forecasting. Forecasting is an important component of Business Management.

It is essentially a technique of anticipation and provides vital information relating to the future. It is the basis of all planning activities in an organisation. It involves collecting valuable information about past and present and estimating the future. Forecast is an estimate of what is expected to happen in some future period.

According to Fayol-the father of modern management— “Forecasting is the essence of management. The success of a business greatly depends upon the efficient forecasting and preparing for future events.”

The techniques of forecasting can be grouped under:- 1. Qualitative Techniques 2. Quantitative Techniques 3. Time Series Techniques of Forecasting 4. Causal Modeling 5. Technological Forecasting.

Some of the qualitative techniques of forecasting are:-

(i) Market Research Techniques (ii) Past Performance Technique (iii) Internal Forecast (iv) Deductive Method (v) Direct vs. Indirect Methods (vi) Jury of Executive Opinion (vii) Historical Analogy (viii) Delphi Technique (ix) Market Survey (x) Judgemental Forecasting (xi) Sales Force Composite Method (xii) User’s Expectation Method (xiii) Brain Storming.

Following are the important quantitative techniques used for the purpose of forecasting:-

(i) Business Barometers Method (ii) Trend Analysis Method (iii) Extrapolation Method (iv) Regression Analysis Method (v) Economic Input Output Model Method (vi) Econometric Model (vii) Expectation of Consumer (viii) Input and Output Analysis.

The time series techniques of forecasting are:- i. Trend Projection ii. Moving Average iii. Exponential Smoothing.

The causal modeling techniques of forecasting includes:- i. Regression Analysis ii. Econometric Models iii. Economic Indicators.

The technological forecasting techniques are:- i. Cross-Impact Analysis ii. Morphological Analysis iii. Substitution Effect.

Some of the other techniques of forecasting are:- 1. Direct Method 2. Indirect Method 3. Joint Opinion Method 4. Scientific Analysis 5. Similarity Events Method 6. Survey Method 7. Sales Person’s Opinion.

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Techniques and Methods of Business Forecasting

Techniques of Business Forecasting – Classified as Qualitative and Quantitative Techniques

In the recent years, large numbers of techniques of forecasting have been evolved to handle different types of forecasting problems. Each technique has its special use and the manager has to select that which one is most suitable for application to his problem.

The factors to be considered for making the choice of techniques for forecasting are as follows:

(a) The purpose of forecast.

(b) The degree of accuracy desirable.

(c) The time period to be forecast.

(d) Cost and benefit of the forecast to the company.

(e) The time available for making the analysis.

(f) Component of the system for which forecast has to be made.

Basic forecasting techniques may be classified as:

(1) Qualitative and

(2) Quantitative.

(1) Qualitative Techniques:

A brief description of some of the qualitative techniques of forecasting is as follows:

(i) Market Research Techniques:

Under this technique, polls and surveys may be conducted to find out the sale of a product. This may be done by sending questionnaires to the present and prospective consumers. In addition, this may also be interviewed personally, though questions and interviews, the manager can find out whether the consumers are likely to increase or reduce their consumption of- the product and if so, by what margin. This interviews etc., and hence this method is somewhat costly and time consuming.

(ii) Past Performance Technique:

In this technique the forecasts are made on the basis of past data. This method can be used if the past has been consistent and the manager expects that the future will resemble the recent past.

(iii) Internal Forecast:

Under this technique indirect data are used for developing forecasts. For Example—For developing sales forecasts, each area sales manager may be asked to develop a sales forecast for his area. The area sales manager who is in charge of many sub-areas may ask his salesmen to develop a forecast for each sub-area in which they are working. On the basis of these estimates the total sales forecast for the entire concern may be developed by the business concern.

(iv) Deductive Method:

In the deductive method, investigation is made into the causes of the present situation and the relative importance of the factors that will influence the future volume of this activity. The main feature of this method is that it is not guided by the end and it relies on the present situation for probing into the future. This method, when compared to others, is more dynamic in character.

(v) Direct vs. Indirect Methods:

In the case of direct method, the different sub­ordinate units on departments prepare estimates and the company takes the aggregate of these departmental estimates. This method is also called bottom up method of forecasting.

On the other hand, in the case of indirect method of forecasting, first estimates are made for the entire trade or industry and then the share of the individual units of that industry is ascertained. This method is also called as “top down” method of forecasting.

(vi) Jury of Executive Opinion:

In this method of forecasting, the management may bring together top executives of different functional areas of the enterprise such as production, finance, sales, purchasing, personnel, etc., supplies them with the necessary information relating to the product for which the forecast has to be made, gets their views and on this basis arrives at a figure.

(2) Quantitative Techniques:

Quantitative techniques are known as statistical techniques. They focus entirely on patterns and on historical data. In this technique the data of past performance of a product or product line are used and analysed to establish a trend or rate of change which may show an increasing or decreasing tendency.

Following are the important quantitative techniques used for the purpose of forecasting:

(i) Business Barometers Method:

This is also called Index Number Method. Just as Barometer is used to measure the atmospheric pressure similarly in business Index numbers are used to measure the state of economy between two or more periods. When used in conjunction with one another or combined with one or more index numbers, provide an indication of the direction in which the economy is heading.

For example—a rise in the amount of investment may bring an upswing in the economy. It may reflect higher employment and income opportunity after some period.

Thus, with the help of business activity index numbers, it becomes easy to forecast the future course of action projecting the expected change in related activities within a lag of some period. This lag period though difficult to predict precisely, gives some advance signals for likely change in future.

The forecasts should bear in mind that such barometers (index numbers) have their own limitations and precautions should be taken in their use. These barometers may be used only when general trend may reject the business of the forecasts. It has been advised that different index numbers should be prepared for different activities.

(ii) Trend Analysis Method:

This is also known as ‘Time Series Analysis’. This analysis involves trend, seasonal variations, cyclical variations and irregular or random variations. This technique is used when data are available for a long period of time and the trend is clearly visible and stable. It is based on the assumption that past trend will continue in future. This is considered valid for short term projection. In this different formulas are used to fit the trend.

(iii) Extrapolation Method:

Extrapolation method is based Time series, because it believes that the behaviour of the series in the past will continue in future also and on this basis future is predicted. This method slightly differs from trend analysis method. Under it, effects of various components of the time series are not separated, but are taken in their totality. It assumes that the effect of these factors is of a constant and stable pattern and would also continue to be so in future.

(iv) Regression Analysis Method:

In this method two or more inter-related series are used to disclose the relationship between the two variables. A number of variables affect a business phenomenon simultaneously in economic and business situation. This analysis helps in isolating the effects of various factors to a great extent.

For example- there is a positive relationship between sales expenditure and sales profit. It is possible here to estimate sales on the basis of expenditure on sales (independent variable) and also profits on the basis of projected sales, provided other things remain the same.

(v) Economic Input Output Model Method:

This is also known as “End Use Technique.” The technique is based on the hypothesis of various sectors of the economy industry which are inter-related. Such inter-relationship is known as co­efficient in mathematical terms. For example—Cement requirements of a country may be well predicted on the basis of its rate of usage by various sectors of economy, say industry, etc. and by adjusting this rate on the basis of how the various sectors behave in future.

As the data required for this purpose are easily available this technique is used in forecasting business units.

(vi) Econometric Model:

Econometric refers to the science of economic measurement. Mathematical models are used in economic model to express relationship among various economic events simultaneously. To arrive at a particular econometric model a number of equations are formed with the help of time series. These equations are not easy to formulate. However, the availability of computers has made the formulation of these equations relatively easy. Forecasts can be solved by solving this equation.

To conclude, it can be said that all these techniques qualitative and quantitative, may give different results in making forecasting. An organisation may choose any of these techniques, considering the size and nature of the business accuracy required and the cost benefit factor.

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Techniques of Business Forecasting – Used in Business Enterprises

A large number of forecasting techniques are used in business enterprises. These can be classified into four broad categories: qualitative, time-series, causal models, and technological forecasting.

A few of them are dis­cussed below:

1. Qualitative Techniques:

A qualitative forecasting technique relies on indivi­dual or group judgment. When quantitative data are not available, the use of ‘informed experts’ can be made. Sometimes the opinions of many “experts” are analysed to predict some future occurrences.

Four approaches are used in this category:

i. Panel of Executive Opinion:

It is also called as a jury-of-expert-opinion ap­proach. It consists of combining and averaging top man­agement’s views about the future event. In this approach, generally the executives from different areas such as sales, production, finance, purchasing are brought to­gether. Thus, a varied range of management viewpoints can be considered. Forecasts can be prepared quickly without elaborate data.

ii. Historical Analogy:

This method is most commonly used. It is based on the belief that future trends will develop in the same direction as past trends. It assumes that the future will remain as in the recent past. Hence, past trends are plotted on a graph or chart to show the curve.

Three forms of this method are in use:

(a) Taking the current years’ actual performance as base for future prediction;

(b) Increasing certain percentages with the last year’s actual performance to predict the future events; and

(c) Averaging the actual performance of the previous few years.

iii. Delphi Technique:

This is another judgmental technique. It polls a panel of experts and gathers their opinions on specific topics. The forecasting unit decides the experts whose opinions it wants to know. Each expert does not know who the others are. The experts make their forecasts and the coordinator summarizes their responses. Here, the ex­perts express their views independently without knowl­edge of the responses of other experts.

On the basis of anonymous votes, a pattern of response to future events can be determined. His technique is used to reduce the “crowd effect” or “group think” in which everyone agrees with “the experts” when all are in the same room.

iv. Market Survey:

Another type of qualitative forecast is the market survey. In this approach, the forecaster can poll, in person or by questionnaire, customers or clients about expected future behaviour. For example- people can be asked about their probable future purchases of cars. This method is effective if the right people are sampled in enough num­bers. It asks a set of “experts”—consumers or potential consumers—what they will do.

2. Time Series Techniques of Forecasting:

These techniques are based on the assumption that the “past is a good predictor of the future.” These prove useful when lot of historical data are available and when stable trends axe apparent. These techniques identify a pattern representing a combination of trend, seasonal, and cyclical factors based on historical data. These meth­ods try to identify the “best-fit” line by eliminating the effect of random fluctuations.

This category includes the following:

i. Trend Projection:

This method projects past data into the future. This can be done in a table or a graph. This method fits a trend line to a mathematical equation and then projects it into the future by means of this equation.

ii. Moving Average:

In this method, the average of a limited number of significant results is calculated and updated as new results become available by adding the latest result and dropping off the oldest.

iii. Exponential Smoothing:

This technique is similar to the moving average, except that it gives more weight to recent results and less to earlier ones. This is usually more accurate than moving average.

3. Causal Modeling:

In this category of forecasting techniques, causal models are constructed to explain the relationships bet­ween the factor to be forecasted (sales) and other factors (price, advertising or product availability).

The following methods are included in this category:

i. Regression Analysis:

Regression models are equations created to predict one variable on the basis of known other variables. For example- we might predict auto sales based on the economic levels, personal income, price, and time.

ii. Econometric Models:

This method makes use of several multiple-regres­sion equations to predict major economic shifts and the potential impact of those shifts on the organization. This method is useful in answering the “what if questions. It helps investigate the impact of various changes in the environment and in major segments of the enterprise.

iii. Economic Indicators:

Economic indicators are data that can forecast the future state of the economy. Examples of such indicators include the current rates of national productivity, infla­tion, cost-of-living index, and level of unemployment.

4. Technological Forecasting:

It focuses on predicting what future technologies are likely to emerge and how they are likely to prove econom­ically feasible. It deals with technological changes that can affect the organization. In fact, some technological advancements, such as word processing, computers, lasers, and pace technologies, have greatly affected the operations of business.

The most widely used methods are:

i. Cross-Impact Analysis:

This method attempts to identify and determine the significance of relationships and interactions between specific events. To know this impact, a two or three- dimensional matrix is developed. For example- an energy company can use this technique to know the impact and value of solar heating.

ii. Morphological Analysis:

This technique is useful in finding the multiple uses of any recent technology. It identifies various dimensions of the object. It evaluates all varieties and combinations of those dimensions to find the practical uses for them.

iii. Substitution Effect:

This technique assumes that one technology that shows a relative improvement in performance over the older technology will ultimately be substituted for the factor with the lower performance. It indicates a patterned fashion for certain technologies.

Each of these forecasting techniques has inherent limitations. Hence, managers should validate one source of forecast information with more additional sources.

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Techniques of Business Forecasting – Direct Method, Indirect Method, Historical Method, Joint Opinion Method, Deductive Method, Scientific Analysis

Following are the important methods of Business Forecasting:

(1) Direct Method:

This method is also known as “Bottom-up-method.” In this method every department, every section, every unit and every branch is authorized to make the forecasting for itself. These forecasting are collected. On the basis of forecasts of different units of different sections of a department, forecasts are made for the department as a whole. After this, on the basis of forecasts of various departments forecasts are made for the business enterprise as a whole. That is why this method is called the “Bottom up method.”

(2) Indirect Method:

This method is also known as “Top down Management” of forecasting. Here forecasts are made for the whole enterprise. These forecasts are made by the top level management. After making the forecasts for the whole business enterprise, the forecasts are made for different departments of the enterprise. After making estimates at departmental levels, the forecasts are made for the different sections and units of a department.

(3) Historical Method:

This method of forecasting is based on the assumption that history repeats. In this past experiences are analysed and interpreted. It assumes that the same results will be obtained in some particular circumstances as have been obtained in the past in the same circumstances. A relationship between past events, their circumstances and causes and their results is established. On the basis of such relationship, forecasting is made for the future.

(4) Joint Opinion Method:

Under this method, a committee of experts is formed. The members of this committee make surveys of the circumstances. After that, opinions of all the experts are taken and these opinions are analysed. The forecasting’s are made on the basis of such opinions.

For example – The opinions of all the salesmen may be collected for making the sales forecasting. After this the average of all these forecasting may be calculated and such average may be the sales forecasting of the enterprise.

(5) Deductive Method:

This method does not consider the past. It starts with the present. A careful study and analysis is made of the present circumstances and situations. Here forecasting is based on the assumption that the results obtained in past in some particular circumstances cannot be the base for the same circumstances in future, because many factors change in the course of time due to the changes in economic, social, political circumstances and trade cycle.

In this all the facts and information’s are analysed and then the future trends are decided keeping in view the factors which are likely to influence the future decisions.

(6) Scientific Analysis:

This method is the Latest Approach to making the business forecasts. Under this method, the principles of economics, mathematics, statistics, etc. are applied. Business models are prepared on the basis of these techniques and these models form the basis of business forecasting.

Scientific method of forecasting involves the following questions:

(a) What is the relationship between causes and effect?

(b) What is the reason of such relationship?

(c) What is the possibility of the existence of this relationship in future?

(d) What are the changes which may take place in economic, business, social and political conditions?

(e) Will these changes affect the future trends?

(f) What is the other factors affecting the future forecasts?

On the basis of all these questions, attempts may be made to make forecasts for future.

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Techniques of Business Forecasting – Used in the Field of Business for Making the Forecasting Effective

Various techniques of forecasting are used in the field of business because the future of any business can never be predicted with certainty. An accurate forecasting may reduce the degree of uncertainty. However, no technique can be considered as a correct one which universally applicable. In practice, more than one technique can be combined for making the forecasting effective.

So, some of the techniques are discussed below:

Technique # 1. Similarity Events Method:

It is otherwise called Historical analogy method. In this method, forecast is made on the basis of events happened in the past which are most similar to current events. For example, in analysing the changes in the attitude of employee regarding in equality, the management can find out prudential attitude of employee in the days to come by considering past attitude. The similarity of events of past and present is properly analysed in order to make an effective forecast.

Technique # 2. Jury of Executive Option:

The opinion of experts is sought under this method and the meritorious one is accepted. For example, an opinion on profitability of starting a new unit is received from various experts and decision is made on the basis of experts’ opinion. The opinion may be on the area of sales, finance, purchase and the like. Some ideas are generated which can be evaluated for their feasibility and profitability. Experts may request comment on the opinion of the others in order to arrive at a consensus of opinion. The reason for favouring a particular opinion by an expert is known to the management.

Technique # 3. Survey Method:

Field survey can be conducted to collect information regarding the attitude of people. For example, information may be collected through surveys about the savings habits of the public. Both quantitative and qualitative information may be collected. Such information is useful for proper forecasting. The demand for both new and existing products can be forecast through survey method.

Technique # 4. Sales Person’s Opinion:

The sales force of the existing product can be forecast with the help of opinions of sales persons. Sales persons are very closer to the consumers and/or customers. So, the opinions expressed by the sales persons are of great value. A reasonable sales trend can be predicted based on the opinions of sales persons.

Technique # 5. Business Barometers:

Index Numbers are used to measure the state of condition of business between two or more periods. Business trend, seasonal fluctuations of a business and cyclical movements are studied with the help of index numbers. Index numbers indicate the direction in which the business is going on. Besides these index numbers give some advance signals for likely changes in the future.

For example, a pay rise to the government employees, industrial and agricultural employees may reflect higher sales volume and higher income after some time. Thus, it is very easy to forecast the future trend of a business with the help of business activity index number. However, index numbers do not give an assurance for success. The reason is that all types of business do not follow the general trend.

Technique # 6. Expectation of Consumer:

Under this method, a survey is conducted in order to know the future needs of consumers. An overall forecast can be made on the basis of the expectations of consumers. An organisation can find out the consumer preferences, impact of advertisement on buying behaviour and the lacuna prevailing in the existing product. This is also known as “Marketing research Method.”

Technique # 7. Time Series Analysis:

In time series analysis, the future is forecast on the assumption that past activities are good indicators of future activities. In other words, future activities are the extension of the past. This method is quite accurate where future is expected to be similar to the past. Time series analysis can be applied. Only when the data are available for a long period of time. In a nutshell, forecasts are based on the assumption that the business conditions affecting its steady growth or decline are reasonably expected to remain unchanged in the future.

Technique # 8. Delphi Method:

Rand Corporation has developed the Delphi method initially in 1969 to forecast the military events. Then, it has been applied in other areas also. A panel of experts is prepared. These experts are requested to give their opinions in writing for a prescribed questionnaire. Their opinions are analysed, summarized and submitted once again to the same experts for future considerations and evaluations.

The authors of these opinions are not disclosed, so that no expert is influenced by other’s opinions. This process is continued up to the stage at which a consensus opinion is obtained. Delphi method is useful when past data are not available and where the past data do not give an indication for the future events. Delphi method is highly useful in problems like future petroleum and diesel needs, likely or probable after effects of a price expected social changes and the like.

Technique # 9. Extrapolation:

Extrapolation means estimation of future behaviour from the known data (i.e.,) past behaviour. Some of the factors are responsible for the behaviour change. Here, the effects of such various factors are taken into consideration. The reason is that it assumes that the effect of these factors is of a constant and stable pattern and would continue as such in future. It is necessary that the future behaviour is to be decided only after a very careful study of past behaviour.

Technique # 10. Regression Analysis:

Regression analysis is used to find out the effect of changes of the relative movements of two or more inter-related variables. In other words, a change in one variable has an effect on the other inter-related variables. In the modern business conditions and situations, numbers of factors are responsible for the changes made in the variables. Here, Regression analysis helps in isolating the effects of such factors to a great extent.

For example, if we take two inter-related variables viz cost of production and profit, there will be a direct relationship prevailing between these two variables. It is possible to have an estimate of profit on the basis of cost of production, provided other things remain the same. In this way, forecasting can be made.

Technique # 11. Input and Output Analysis:

Under this method, a forecast can be made if the relationship between input and output is known. At the same time, the input requirements can be forecast on the basis of output. In other words, input can be determined on the basis of need of output. For example, power requirement of the country can be forecast on the basis of its present usage rate in various sectors viz., industry, transport, household etc., and on the basis of how the power requirements of these various sectors will increase in future. This is possible. The reason is that various sectors of economy are interrelated. Besides this, the prevailing inter relationship among the various sectors of the economy can be well established.

Technique # 12. Econometric Models:

It is otherwise called causal models. The complex relationship of various variables is responsible for the future behaviour of one variable.

For example, sales is affected by many variables, say, time, changes in personal disposable income, changes in preferences, availability of substitute products in the market, credit availability, changes in life style and the like. All these variables have produced some effects on present sales in addition to past sales. This forecasting technique is applied in projecting Gross National Product. Here, the past data have been used to know the degree of relationship prevailing among these variables.

These are some of the forecasting techniques. These techniques, broadly, can be divided into two categories viz., Qualitative techniques and Quantitative techniques. Qualitative techniques are based on human judgement. The reason is that there is no availability of sufficient information and data.

If sufficient information and data are available, quantitative technique can be applied to forecasting. Qualitative and Quantitative may help in forecasting the unexpected future events or happenings or opportunities or threats. But, a quantitative technique does not make any provision for finding out the unexpected occurrences.

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Techniques of Forecasting – Qualitative and Quantitative Forecasting

Technique # 1. Qualitative Forecasting:

i. Judgemental Forecasting:

Under this method, a panel of experts in the area is prepared. The opinions of senior executives are taken verbally or in a meeting and a consensus is reached after examining the variety of opinions which is called an estimate.

ii. Sales Force Composite Method:

Sales persons operating in various geographies are asked to give their estimate of sales in their areas. The regional sales managers collect them and send them to marketing managers who consolidate all the estimates and arrive at forecast of sales for a given period.

iii. User’s Expectation Method:

Under this method, survey is conducted in order to ascertain the future needs of consumers spread over the areas where their products are marketed. The opinion is collected either through direct interview or questionnaires sent through mail.

For example, consumers may be asked to convey their likely expenditure on various items. Both quantitative and qualitative data may be collected on the attitudes with regard to items of consumption. On the basis of the survey, the demand for various products can be projected. This method is suitable for assessing the demand of existing as well as new products.

iv. Historical Analysis:

Forecast in relation to a particular phenomenon is made in terms of analogous conditions which happened somewhere in the past. In other words, forecast is made on the basis of similar events that have happened in the past elsewhere or in the enterprise.

For example, when a product is invented in one country and is adopted in other countries, the demand forecast for the product in other countries can be made in terms of similar nature of events happening in the country of invention. Similarly, employee behaviour in future can be predicted on the basis of his response to similar behaviour in the past.

v. Delphi Technique:

Whatever opinion experts give are anonymous, and each one is asked to comment on the opinion of others. The ultimate forecast under this method, is thus the composite result of anonymous interactions, based on a common desire to benefit from others opinion.

The process of Delphi technique is as follows:

a. A panel of experts is chosen from within and outside the enterprise in question.

b. Each member is asked to give his opinion anonymously to make a forecast of what would happen in future regarding a particular problem.

c. Answers are compiled and composite initial forecast is made.

d. It is sent back to each member of the panel for his/her remarks on the forecast.

e. This process is repeated until consensus is reached on the forecast.

vi. Brain Storming:

This technique is commonly used to elicit innovative ideas on a given problem.

It involves the following procedure:

a. Group meeting is conducted.

b. Criticism of any idea, however stupid or impracticable it may be, is eliminated.

c. Free flow of idea is facilitated.

d. Maximization of idea is achieved.

e. Out of the ideas gathered, good idea is implemented.

Similarly, in sales forecasting context, sales people are made to form groups and encouraged to arrive at forecast on various situations. Finally, marketing management chooses the more valid one.

Technique # 2. Quantitative Forecasting:

i. Business Barometers:

Index numbers are used to measure the state of condition of business or economy between two or more periods. These index numbers reveal the trends, seasonal fluctuations, cyclical movements and irregular fluctuations. These number when used in conjunction with one another or in combination with one or more provide a direction of economy.

For example, rise in rate of investment may herald a booming economy and may indicate higher employment, opportunities and higher income. Higher per capita income may lead to higher savings and higher consumption.

ii. Time Series Analysis:

Under this method, future is taken as extension of the past events. For time series analysis, data should be available for a longer period. When the past trend is stable and steady, future can be accurately predicted under time series method.

iii. Extrapolation:

It means estimation of future behaviour from the known data. It is also based on time series method. This method relies on the behaviour of a series in the past and projects the same trend in future. This method does not isolate the various factors influencing the problem under study but takes into account the totality of their effects. It assumes that effect of these factors is stable and constant and it would continue in future as well.

iv. Regression Analysis:

This analysis is meant to estimate the impact of one independent variable on dependent variable in simple regression. For example, impact of advertisement is taken as independent and profit is taken as dependent variable. Simple regression measures the impact of advertisement on sales.

Multiple regression analysis measures the impact of two or more independent variables on one dependent variable. For example, cost of production and sales are taken as independent variable. The respective contribution of these factors to profit (dependent variable) is found out in multiple regression analysis.

v. Econometric Models:

This is one of the sophisticated tools of analysis used for forecasting the impact of various changes in the external environment on the business enterprise. For example, the impact of changes in tax laws or GDP on sales of a luxury product can be found out by applying this tool.

This approach combines the tools of economics and mathematics. These models take the form of a set of simultaneous equations. As variables influencing a business event are many, many such equations are formed. The construction of these equations is a complex task. Advanced software’s are used now a days to construct equations.

These models are useful to predict future trends and turning points with accuracy. It is expensive and time consuming. Besides various assumptions, underpinning specific micro economic theories are subject to debate.

For example, an econometric model is built on the assumption that the relationship between the economic variables and the level of economic activity for one year in the future are known. This type of forecast being complex, it can be handled only by econometrician.

vi. Input and Output Analysis:

When the relationship between input and output is known, output can be forecast for a given level of input. Similarly, the level of input can be forecast for a given level of output. Only where different sectors of an economy are inter-related, this forecast can be applied.

Such inter-relationship among the variables is known as coefficient in mathematical language. For example, the requirements for LPG can be predicted for various sectors of the economy using this model. This technique is used when an output is commonly used by different sectors. The forecast can be made by taking the basic usage levels in these sectors.

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