Methods of forecasting demand, Hope it will be useful.

1. By:
Anshul Agrawal
Balaji Bhukya
DEMAND FORECASTING

2. Demand Forecasting is a systematic and scientific estimation of
future demand for a product.
Simply, estimating the sales proceeds or demand for a product
in the future is called as demand forecasting.
The main challenge to forecast demand is to select an effective
technique.
There is no particular method that enables organizations to
anticipate risks and uncertainties in future.
Demand Forecasting

3. There are two approaches to demand forecasting.
1. The first approach involves forecasting demand by
collecting information regarding the buying behavior of
consumers from experts or through conducting surveys.
2. On the other hand, the second method is to forecast
demand by using the past data through statistical
techniques.

4. Methods of
forecasting
Survey
method
Consumer
survey
method
Opinion
poll
method
Statistical
method
Trend
projection
Barometric
method
Econometr
ic method

5. Survey Methods:
Under the survey method, the consumers or experts are
contacted directly and are asked about their intentions for a
product and their future purchase plans.
The survey method includes:
Consumer Survey Method
 Complete Enumeration Method
 Sample Survey
 End-use Method
Opinion Poll Methods
 Expert-Opinion Method
 Delphi Method
 Market Studies and Experiments

6. Consumer Survey Method:
It involves direct interview of the potential consumers.
This is done by interviewing all consumers or a selected
group of consumers out of the relevant population.
Here the burden of forecasting is shifted to the buyer.
Consumer Survey Method includes the further three
methods that can be used to interview the consumer:
 Complete Enumeration Method
 Sample Survey
 End-use Method

7. 1. Complete Enumeration Method:
Forecaster contact almost all the potential users of the product
and ask them about their future purchase plan.
The probable demand for a product can be obtained by adding
all the quantities indicated by the consumers.
Dp = Q1+Q2+Q3+Q4+……+Qn
Where, Q1, Q2, Q3 denote the demand of 1, 2, 3 and so on.

8. 2. Sample Survey:
The sample survey method is often used when the ’target
population under study is large’.
Only the sample of potential consumers is selected for the
interview. Here, the method of survey may be a direct interview
or mailed questionnaires to the selected sample-consumers. The
probable demand, indicating the response of the consumers can
be estimated by using the following formula:
Where,
Dp = probable demand forecast
H = Census number of households from the relevant market
Hs = number of households surveyed or sample households
HR = Number of households reporting demand for a product
AD = Average Expected consumption by the reporting households

9. 3. End-use Method:
The end-use method is mainly used to forecast the demand for
inputs. This method of demand forecasting has a considerable
theoretical and practical value.
Ex: forecasting of API demand

10. Opinion Poll Methods:
It is used to collect opinions of those who possess the
knowledge about the market, such as sales representatives,
professional marketing experts, sales executives and
marketing consultants.
The Opinion poll methods include the following survey
methods:
 Expert-Opinion Method
 Delphi Method
 Market Studies and Experiments

11. 1. Expert-Opinion Method:
Companies with an adequate network of ’sales reps takes
opinion of them to asses the demand’ for a product in a
particular region or locality that they represent.
 Sales representatives are in direct touch with the
customer, are supposed to know the future purchase
plans of their customers
 Sales representatives are likely to provide an
approximate, if not accurate, estimation of demand for
a target product in their respective regions or areas.
 It is simple and inexpensive method.

12. 2. Delphi Method:
The Delphi method is the extension of the expert opinion method
wherein the ”divergent expert opinions are consolidated to
estimate a future demand”.
 It requires a panel of experts, who are interrogated
through a sequence of questionnaires in which the
responses to one questionnaire are used to produce the
next questionnaire.
 Thus any information available to some experts and not to
others is passed on, enabling all the experts to have access
to all the information for forecasting.

13. 3. Market Studies and Experiments:
Future demand for a product is determined by conducting
market studies and experiments on the consumer behavior
under controlled market conditions.
 Experiments are carried out in selected areas which
represents market by changing the prices, advertisement
expenditure and all other controllable factors, other
things remaining the same.
 Once these changes are introduced in the market, the
consequent changes in the demand for a product are
recorded. On the basis of these recorded estimates, the
elasticity coefficients are calculated

14. Methods of
forecasting
Survey
method
Consumer
survey
method
Opinion
poll
method
Statistical
method
Trend
projection
Barometric
method
Econometr
ic method

15. Statistical Methods:
The statistical methods are often used when the forecasting of
demand is to be done for a longer period.
The statistical methods utilize the time-series (historical) and
cross-sectional data to estimate the long-term demand for a
product.
It includes,
 Trend Projection Methods
 Barometric Methods
 Econometric Methods

16. Trend Projection Method:
A firm existing for a long time will have its own data regarding
sales for past years of existing products can be used to forecast
future demand.
 Time series 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 inexpensive and partly
because time series data often exhibit a persistent growth
trend.

17. Year Sales (Rs. Crore)
1995 40
1996 50
1997 44
1998 60
1999 54
2000 62
1. Graphical Method:
Simple technique to determine the trend.
All values of output or sale for different years are plotted on a graph
and a smooth free hand curve is drawn passing through as many
points as possible. The direction of curve upward/downward shows
the trend.
Illustration of this method Table 2.Table 2: Sales of Firm

18. 2. Least Square Method:
Trend line can be fitted to the time series data with the help of
statistical techniques such as least square regression.
When the trend in sales over time is given by straight line, the
equation of this line is of the form:
y = a + bx
Where,
a - is the intercept
b - shows the impact of the independent variable.
Two variables:
X - the independent variable
Y - dependent variable
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.

19. 3. Box-Jenkins Method:
Box - Jenkins Analysis refers to a systematic method of
identifying, fitting, checking, and using integrated
autoregressive, moving average (ARIMA) time series models.
The method is appropriate for time series of medium to long
length (at least 50 observations).

20. 4. Simple moving average:
It is suitable under situations where there is neither a growth nor a
decline trend shown by the actual past data for forecasting.

22. Barometric Technique:
A barometer is an instrument of measuring change like predicting
future based on present happenings.
This is accomplished by the use of economic and statistical indicators
which serve as barometers of economic change.
1. The Leading Series:
The leading series comprise those factors which move up or down
before the recession or recovery starts. They tend to reflect in future
market changes.
Ex: Baby powder and soaps sales prediction for next five years based
on present birth rate.

23. 2. Coincident or Concurrent Series:
The coincident or concurrent series are those which move up or
down simultaneously with the level of the economy.
They are used in confirming or refuting the validity of the leading
indicator used a few months afterwards.
Common examples of coinciding indicators are G.N.P itself,
industrial production, trading and the retail sector.
3. The Lagging Series:
The lagging series are those which take place after some time lag
with respect to the business cycle.
Examples of lagging series are, labour cost per unit of the
manufacturing output, loans outstanding, leading rate of short
term loans, etc.

24. The Econometric Methods:
Make use of statistical tools and economic theories in combination
to estimate the economic variables and to forecast the intended
variables.
An econometric model consists of two types of methods namely,
regression model and simultaneous equations model.

25. Linear Regression Analysis:
It is applied in situations where two variables are linearly
correlated to each other.
In time series analysis, the independent variable is time
while the dependent variable is the actual demand in the
past.
A graph showing the points for the corresponding values
of two variables is called scatter diagram. These points
should display an approximately linear trend.

26. Example of linear regression
Y= 1060X + 440 is the regression equation
Interpretation:
As the age of the car increase by 1 year the maintenance
cost is expected to increase by Rs1060.
y = 1060x + 440
R² = 0.997
0
2000
4000
6000
8000
10000
12000
0 2 4 6 8 10 12
Maintenance Cost(Y)
Maintenance
Cost(Y)