Forecasting Methods
There is nothing new about the business forecasting as, for many years, the businessmen have tried to adjust themselves in such a manner as to make the best out of the future conditions. The rule-of-thumb technique has been widely practiced in the business. It consists of deciding about the future in terms of the past experience and familiarity with the problem at hand even nowadays. This technique is very widely used in business however; it can lead to absurd conclusions if employed by the inexperienced.
A forecast is usually a combination of various technique.
Business barometers: - Of great assistance in practical forecasting is a series that can be used index or indicator is also widely, though loosely, used in business statistics; sometimes the word is used to mean simply an indicator of the present economic situations and sometimes it is used to designate an indicator of future conditions.
The following are some of the main series which aid businessmen in forecasting:
(i) Gross national product
(ii) Employment
(iii) Wholesale prices
(iv) Consumer prices
(v) Industrial production
(vi) Volume of the bank deposits and currency outstanding
(vii) Consumer credit
(viii) Disposable personal income
(ix) Departmental store sales
(x) Stock process
(xi) Bond yields.
Extrapolation:- The Extrapolation is the simplest yet often a useful technique of forecasting. In many forecasting conditions the most reasonable expectation is that the variable will follow its already established path. The Extrapolation relies on the relative constancy in the pattern of past movements in some time series. Strictly speaking, nothing require to be known about causation-why the series moves as it does. But in practice the justification involves the nature of the growth process being described. The Extrapolation is used frequently for the sales forecasts and for other estimates when better forecasting methods may not be justified.
Most of the most useful ones are:
Arithmetic trend:- The straight-line arithmetic trend assumes that the growth will be b a constant absolute amount every year.
Semi-log trend:- The semi-logarithmic trend assumes a constant percentage increase every year. Since the annual increment is constant in logarithms. This line translates a straight line when drawn on paper within a logarithmic vertical scale.
Modified exponential trend:- This curve assumes that each increment of growth will be a constant percent than 100 of the earlier one. The line terms is normally used for approach, by never quite reach a distant asymptote, that may be thought of as an upper limit.
Regression analysis:- The regression approach offers many valuable contributions to the solution of the forecasting problem. This is the means by which we select form among the many possible or theoretically suggestive relationships between two variables to the exact quantified knowledge. If possible an estimate of the another. For e.g. If we know that the advertising expenditure and sales are correlated then for a given advertising expenditure. We can find out the probable increase in sales or vice versa.
Econometric models:- The Econometric techniques which is originated in eighteenth century, have recently gained in popularity for forecasting. Much of the revival of econometrics is attributed to the growth of computer technology. The word econometrics refers to the application of mathematical economic theory and statistical procedures to economic data in the order to verify economic theorems and to establish quantitative results in the economics. And all in the econometric models take the form of a set of simultaneous equations. The constants values in such equations are supplied by a study of statistical time series and a large number of equations may be necessary to produce an adequate model. The work of the computations is greatly facilitated by electronic data processing equipment such as computer etc.
Forecasting by the use of time series analysis:- The time series analysis helps to identify and explain:
Any regular or systematic variation in the series of data which is due to seasonality-the seasonal.
Opinion polling:- The Opinion poll is the survey of opinion of experts knowledgeable people in the field whose views carry lot of weight, for e.g. , a survey of opinion of wholesalers, sales representatives, retailers etc. shall be of great help in formulating the demand projections. The survey research center of the University of Michigan conducts an annual pool regarding the future plans of consumers. The answers to too many questions are translated into short-run demand for automobiles, color television sets and other consumer products.
Causal models: - The Causal model is the most sophisticated king of the forecasting tool. It expresses mathematics call to the relevant causal relationships. And may consist pipeline considerations (inventories) and market survey information. They may also directly incorporate the result for a time series analysis.
Illustration: from the following values prepare forecasts by the techniques of exponential smoothing taking initial estimate as 100, the values of α = 0.04 and an initial trend value zero:
Time period (ƒ)
|
1999
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
Sales ($ crores)
|
104
|
108
|
118
|
115
|
120
|
122
|
123
|
125
|
128
|
130
|
Solution:
t
|
X1
|
Smoothed value St
|
Change in St ?St
|
Trend estimate tt
|
Forecast St
|
Forecasting error (e)
|
1999
|
104
|
100.0
|
-
|
-
|
-
|
-
|
2000
|
108
|
103.2
|
3.20
|
1.28
|
105.12
|
-12.88
|
2001
|
118
|
109.12
|
5.92
|
3.14
|
113.83
|
-1.17
|
2002
|
115
|
111.47
|
2.35
|
2.82
|
115.70
|
-4.30
|
2003
|
120
|
114.83
|
3.41
|
3.06
|
119.47
|
-2.53
|
2004
|
122
|
117.73
|
2.85
|
2.98
|
122.20
|
-0.80
|
2005
|
123
|
119.84
|
2.11
|
2.63
|
123.79
|
-1.21
|
2006
|
125
|
121.90
|
2.06
|
2.40
|
125.50
|
-2.50
|
2007
|
128
|
124.34
|
2.44
|
2.42
|
127.97
|
-2.03
|
2008
|
130
|
126.60
|
2.26
|
2.36
|
130.14
|
-
|
Exponential smoothing:- This method is an outgrowth of the recent attempts to maintain the smoothing function of moving averages without their corresponding drawbacks & limitations. The Exponential smoothing is a special kind of weighted average and is found extremely useful in short-term forecasting of inventories and sales.
Smoothing process: - The steps in the smoothing process are:
The exponentially smoothed value at time period t is denoted by Si the smoothing process begins by assigning S1 = X1 at the first time period. For the second time period.
S2 = a X2 + β S1
And for any succeeding time period t the smoothed value Si is found by computing.
St = a Xt + β St - 1
Survey method; - The survey technique is very widely used as a tool of forecasting for the existing any new products. The Field surveys are conducted and the necessary information, both quantitative and qualitative obtained. The Forecasts are made out about likely demand expenditure on consumer durables. Etc. The attitude of consumers about consumption of different items provides very useful information.