Meaning of Forecasting
Forecasting is the process of estimating the relevant events of the future, based on the analysis of their past and present behaviour. The future cannot be probed unless one knows how the events occurred in the past and how are they occurring presently. Thus the past and present analysis of events provide information about their future occurrences. Since forecasting may need various statistical techniques, some people equate this analysis with statistical analysis.
Definition of Forecasting
According to Neter and Wasserman, “Business forecasting refers to the statistical analysis of the past and current movement in the given time series to obtain clues about the future pattern of those movements”.
According to Louis A. Allen, “Forecasting is a systematic attempt to probe the future by inference from known facts”.
According to the American Marketing Association, “Forecasting is an estimate of sales in dollars or physical units for a specified future period under a proposed marketing plan or program and under an assumed set of economic and other forces outside the unit for which the forecast is made. The forecast may be for a specified item of merchandise or an entire line”.
According to Fayol, “Forecasting is the essence of management. Its techniques are used in every type of organisation may it be government or private, production or service and social or religious”.
Forecasting is the process of predicting the future. Whether it is predicting future sales, demand, or production, forecasting is an important yet unavoidable task that is an integral part of almost all business activities. Demand forecasting is essential for a firm to produce the required quantities at the right time and arrange well in advance for various inputs. Forecasting helps a company to assess the probable demand for its products and plan its production accordingly.
Need of Forecasting
The need and importance of forecasting can be found with the help of the key role played for forecasting in the management process, especially in the planning process. Whatever planning is done by the management executives, their planning has to be based on forecasting.
Forecasting helps the management in the following ways:-
- Promoting Business
- Effective Planning
- Implementing Project
- Achieving Success
- Achieving Objectives
- Improving the Quality of General Management
- Helping Every Aspect
1) Promoting Business
While promoting a new business, the promoters must know how the various factors in the environment will affect promotional activities over some time. They must forecast what will happen in future, and what risks are involved if an action plan is drawn based on forecasting results. If the promoters are satisfied that the risks involved are worth taking, they may take up the plan, otherwise, it is a blind jump into the future. Thus forecasting provides the basis for the promotion of a business.
2) Effective Planning
Forecasting is an essential ingredient of planning. Without it, planning is not possible. Planning decides the future course of action which cannot take place in a vacuum but certain circumstances and conditions are predicted by the forecasting procedure. Based on events that happened in the past and which are being occurred in the present forecasting decides what will happen in future with the help of some techniques.
The planning structure is founded based on that future event. It provides the knowledge of various planning premises within which managers may analyse their strengths and weaknesses and may take appropriate actions in advance before they are put on the market. Planning decides the course of action based on forecasting. future events are projected, managers may make necessary changes in the plan and may sail smoothly.
3) Implementing Project
Many entrepreneurs implement a project based on their experience. Forecasting helps an entrepreneur gain experience and ensures his success. In this way, forecasting is an important factor which enables the entrepreneur to get success.
Forecasting provides the way for effective coordination though indirectly. In the forecasting process, information is required which is collected from internal as well as external sources. All units/departments are involved in this process. It provides interactive opportunities for better unity and coordination in the process of planning.
Forecasting provides relevant information to exercise controlling function. The information supplied by different units in the organisation is used in forecasting. It presents the actual performance while forecasting the future. The managers may come to know their weaknesses which may be overcome by taking corrective measures.
6) Achieving Success
The common phenomenon of ups and downs in the business involves uncertainties and risks, which affect the profits of the business. Risks depend upon future happenings and forecasting provides help to overcome the menace, the managers may take alternative action to avoid the risks and thus save their business from untoward happenings. Thus forecasting ensures future risks. Though it cannot check the future, it may provide clues about it and indicate when the alternative action may be suitable.
7) Achieving Objectives
An organisation is established to achieve certain objectives which may be achieved by performing certain activities. The type of activities depends very much on the expected outcome of these activities which in turn depends on future events and how these activities are being performed. Therefore, forecasting future events is relevant to achieving the objectives.
8) Improving the Quality of General Management
Forecasting is based on thinking and rethinking the problems to be faced by the management in future, based on past experiences. Thus it helps in the development of the mental faculties of the managers.
Managers choose to identify one alternative out of several alternatives available based on forecasting. They think of the strengths and weaknesses of each alternative and decide which one is the best in the current circumstances. They decide what action they would prefer if the circumstances change. Thus, forecasting develops the mental faculties of managers.
9) Helping Every Aspect
Thus forecasting helps every aspect of management. It is the basis of planning. It is the first phase in the process of management. The success of the business depends on forecasting.
Process of Forecasting
The forecasting period may be short-term or long-term. In either case, certain stages or steps have to be passed through while making the forecast.
These stages or steps are briefly discussed below:
- Thorough Preparation of the Foundation
- Estimation of Future
- Collection of Results
- Comparison of Results
- Refining the Forecast
1) Thorough Preparation of the Foundation
Detailed investigation and complete analysis of the company are necessary for forecasting. Forecasting is based on the organisational structure of the company and its past performance. The growth of a company or a business is assessed over some time and the factors responsible for such are identified. Besides this, the extent of the dependence of one factor on other factors that ensure the growth of a company has to be studied. The very objective of the thorough preparation of a foundation is that the forecasting is based on the foundation.
2) Estimation of Future
The prosperity of the future can be estimated with the help of experience and performance as well as the talents possessed by top management executives. The brightness of the future period can be estimated in consultation with the key personnel and it may be communicated to all the employees of the business unit. This type of communication will help the management to fix the responsibility of each employee fulfilling the promises of this forecast and accountability for any deviations from this forecast.
3) Collection of Results
All the information can be gathered. Relevant records were prepared and maintained to collect the results. Nothing can be omitted and irrelevant information can be avoided while collecting the results.
4) Comparison of Results
The actual results are compared with estimated results to know deviations. If there are significant deviations between the estimation and actual results, the reasons for such deviations can be investigated. This will help the management to estimate the future (forecasting).
5) Refining the Forecast
The forecast can be refined in the light of deviations which seems to be more practical. If any factors or conditions have changed during the period of understudy, then those factors or conditions have to be taken into consideration for future estimation. In this way, the forecast can be improved and refined.
Techniques of Forecasting
The various techniques of forecasting demand may be grouped under the following categories:
- Qualitative Techniques/Opinion Polling Method
- Quantitative Techniques/Statistical or Analytical Methods
Qualitative Techniques/Opinion Polling Method
In this method, the opinions of the customers, sales force and experts could be gathered to determine the emerging trend in the market.
The opinion polling methods of demand forecasting are of three different kinds:
- Consumer Survey Methods
- Sales Force Opinion Method
- Delphi Technique
1) Consumer Survey Methods
The most direct method of forecasting demand in the short run is the survey method. Surveys are conducted to collect information about future purchase plans of the probable customers of the product.
Survey methods include the following:
- Complete Enumeration Survey
- Sample Survey and Test Marketing
- End-Use Method
i) Complete Enumeration Survey
Under the complete Enumeration Survey, the company has to go for a door-to-door survey for the forecast period by contacting all the households in the area.
ii) Sample Survey and Test Marketing
Under this method, some representative households are selected on a random basis as samples and their opinion is taken as the generalised opinion. This method is based on the basic assumption that the sample represents the population. A variant of the sample survey technique is test marketing. Product testing essentially involves placing the product with several users for a set period. Their reactions to the product are noted after some time and an estimate of likely demand is made from the result.
iii) End-Use Method
In this method, the sale of the product under consideration is projected based on a demand survey of the industries using this product and the intermediate product. In other words, demand for the last product is the end-use demand for the intermediate product used in the production of this final product.
2) Sales Force Opinion Method
This is also known as the Collective Opinion Method. In this method, instead of consumers, the opinion of the salesmen is taken. It is sometimes referred to as the “grassroots approach” as it is a bottom-up method that requires each salesperson in the company to make an individual forecast for his or her particular sales territory. These particular forecasts are discussed and agreed upon with the sales manager. The composite of all forecasts then constitutes the sales forecast for the company.
3) Delphi Technique
This method is also known as the expert opinion method of investigation. In this method instead of depending upon the opinions of buyers and salesmen, firms can obtain the views of the specialists of experts in their respective fields. Opinions of different experts are taken and their identity is kept secret. These opinions are then exchanged among the various experts and their reactions are sought and analysed. The process goes on until some sort of unanimity is arrived at among all the specialists. This method is best suited in cases where intractable changes are occurring.
Quantitative Techniques/Statistical or Analytical Methods
The statistical methods, which are frequently used, for making demand projections are given below:
- Trend Projection Method
- Barometric Method
- Regression Method
- Econometric Method
1) Trend Projection Method
An old firm can use its data of past years regarding its sales in the past 750 years. These types of data are known as time series of sales. A dry can predict sales of its product by the fitting trend to the time series of sales. A trend line can be fitted by the graphical method or by algebraic equations. The equations method is more appropriate.
The trend can be estimated by using any one of the methods given as follows :
- Graphical Method
- Least Square Method
- Time Series Data
- Moving Average Method
- Exponential Smoothing
i) Graphical Method
A trend line can be fitted through a series graphically. Old values of sales for various areas are plotted on a graph and a free-hand curve is drawn passing through as many points as possible. The direction of the free-hand curve indicates the trend. The main drawback of this method is that it may show the trend but not measure it.
ii) Least Square Method
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. It is a mathematical procedure for fitting a line to a set of observed data points in such a way 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 nicely fits the available data. This trend is then used to project-dependent variables in the future. This method is very popular because it is simple and cheap.
iii) Time Series Data
Time series data refers to data collected over a period recording historical changes in price, income, and other relevant variables influencing demand for a commodity. Time series analysis relates to the determination of change in a variable about time. Usually, trend projections are essential in this regard.
iv) Moving Average Method
Under this method, the moving average of the sales of the past years is computed. The computed moving average is taken as the forecast for the next year or period. This is based on the belief that future sales are the average of past sales. The moving average is the process of computing the average by leaving the oldest observation and including the next one.
v) Exponential Smoothing
Exponential smoothing is a popular technique for short-run forecasting. It uses a weighted average of past data as the base for a forecast. The process gives the heaviest weight to more recent information and a smaller weight to observations in the more distant past.
The reason for this is that the future is more dependent on the recent past than on the distant past. The method is known to be effective when there is randomness and no seasonal changes in the data.
2) Barometric Method
It is also known as leading indicators forecasting. The National Bureau of Economic Research of America has identified three types of indicators – Leading indicators, Coincidental indicators and Lagging indicators.
The analyst should establish a relationship between the sales of the product and the economic indicators to project the correct sales and to measure to what extent these indicators affect the sales. Establishing a relationship is not an easy task, especially in the case of a new product where there is no record.
3) Regression Method
This is a very common method of forecasting demand. Under this method, a relationship is established between quantities demanded (dependent variable) and independent variables such as the price of the good, prices of the related goods, income, etc.
Once the relationship is established, a regression equation is derived assuming the relationship to be linear. The equation will be of the form Y = A + BX. There could also be a curvy linear relationship between 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.
4) Econometric Method
The econometric model forecasting involves estimating several simultaneous equations, which are, generally, behavioural equations, mathematical identities and market-clearing equations. The econometric model technique is known also as the simultaneous equations method and complete system approach to forecasting. This method uses sophisticated mathematical and statistical tools.