1. Demand
forecasting

2. Why Demand Forecasting?
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Demand results in sales
Which is the primary source of Revenue
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Predicting future demand for a product
To avoid under or over production
Minimize the “Uncertainties”
Rough estimate of the demand prospects
Demand forecasting helps in planning to acquire inputs
( men & material), organizing production, advertisement
and organizing sales channels.

3. Purpose of Forecasting Demand
•
Short –run Forecast :
– Seasonal patterns are important
– Forecasting helps in preparing suitable sales policy and
proper scheduling of output.
– Pricing policy and modification in advertising and sales
techniques
•
Long-run Forecast :
– Capital planning
– Planning of production, material, man-hours, machine
time
– Changes in variables are included

4. Steps Involved in Forecasting
Identification of Objective
Nature of Goods
Selection of method
Of Forecasting
Interpretation of Results
Estimation of one /
more than one aspect
Goods have
different demand pattern

5. Steps Involved in Forecasting

6. Time Horizon

7. Demand Forecast Determined

8. Methods of Demand Forecasting
Techniques
Statistical
Methods
Survey Methods
Consumer Survey
Direct Interview
Opinion Poll
Methods
Trend
Projection
Econometric
Methods

9. Survey Methods
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Where the purpose is to make short- run forecast of
demand.
Consumer surveys are conducted to collect information
about their intentions and future plans.
1) Survey of potential consumers on their intentions and
plan.
2) Opinion polling of experts

10. 1) Consumer Survey Method
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Direct Interview with the potential consumers.
Ask what quantity of the product would they buy at different
prices over a given period of time.
Consumer Survey
Method
Complete
Enumeration
Method
Sample Survey
End-Use Method

11. a) Complete Enumeration Method:
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All potential users of the product are contacted and asked
about their future plans of purchasing the product
The quantities indicated by the consumers are added
together to obtain demand of the product
• Dp = q1 + q2 + q3+…………..+ qn
n
= ∑ qi
i=1
Limitation:
1)
2)
3)
4)
5)
Only successful if consumers are concentrated in a certain
region or locality.
Consumers actual demand in future may not be known
Consumers may give hypothetical answers
Consumers response could be biased to their expectations
Consumers plan may change with the change in factors not
included in questionnaire

12. b) Sample Survey Method:
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Only few potential consumers /users are selected.
Its through face to face/ telephonic interview or mailed / web
questionnaire
On the information, the probable demand may be estimated.
Less costly, less time- consuming
Used to estimate short-term demand (yearly)
Dp = HR
HS
( H. AD )
Dp = probable demand forecast
H = Census number of households
Hs = Sample Household
Hr = No of HH reporting demand for the product
Ad = Avg expected consumption ( Total quantity reported to be
consumed / no of hh)

13. –
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Business firms, Government departments and
Households plan their expenditure one year in advance.
Therefore they can supply a fairly reliable estimate of
their future expectations.
Limitations:
– Similar to complete enumerations
– Quantification of variables (e,g Feelings, opinions,
expectations) is not possible

14. c) End- Use Method:
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Requires building up schedule for probable aggregate
future demands for inputs by consuming industries /
sectors
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Technological, structural & other changes which might
influence the demand are taken into account in the
process of estimation
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More relevant for B2B markets

15. c) End- Use Method:
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Stage 1
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Stage 2
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Stage 3
: Application of Norms
» Necessary to know targeted levels of output
of individual industries for the target year
» And likely development in other economic
activities which use the product & likely
output targets
: List all possible uses of the product
: Fix suitable technical norms for each
end use
» Per unit of production of complete product /
per unit of investment / per capita use
» Questionnaires used to collect relevant
information

16. Limitations
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Enumeration of all possible uses – due to lack of
published data
Despatch records of the manufactures, if available need
not enumerate all the final users.
Impossible to organise and collect data of wide network of
wholesale and retail agencies
Possibility of missing out end-uses or new applications
– Therefore estimations should provide some margin of
error
Establishing norms – is difficult
Inaccuracy in estimating sales of target industries
Advantages
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Probing into current use-pattern of consumption of
product – it provides opportunity to determine the demand
by types, categories & sizes etc
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It facilitates in diagnosis & pin-pointing as to where & why
did the actual consumption deviate from estimated
demand

17. 2) Opinion Poll Method
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Aims at collecting opinions of those who possess knowledge
of the market
Sales representatives, sales executives, marketing experts
and consultants
Opinion Poll
Expert -Opinion
Delphi method
Market studies/
experiment

18. a)
Expert – Opinion Method:
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Firms having good network of sales representatives
can ask them to assess demand
As they are in touch with consumers and
consumption pattern
Can provide a approximate figure of likely demand
Limitations:
• Estimates are reliable only to the extent of their
skill to analyse the market.
• The assessor may have subjective judgement
which may lead to over / under estimation
• Inadequate information may be available to the
assessor as they may have narrow view of the
market.

19. b)
Delphi Method:
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To consolidate the expert opinions and arrive at
estimate of future demand.
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Experts are provided information on the estimates of
other experts, and they revise their own estimates
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The consensus of experts about the forecast
constitutes the final forecast
This technique can be used for cross – checking
information on forecasts.

20. c)
Market studies and experiments
To carry out studies on consumer behaviour under actual,
controlled market conditions.
Market studies:
– Firms select areas of market having similar features
( populations, income levels, cultural/ social
backgrounds, choices….)
– Carry out experiments by changing variables of
demand functions
– Consequent changes in demand are recorded
–
Assessment of demand of the product is made.
Experiments:
– Consumers are given money to buy goods with varying
prices, packages, displays…
– It reveals consumers responsiveness to the changes

21. Limitations:
– Expensive – unaffordable for small firms
– Experiments are carried out on a small scale leads to
generalization
– Studies are based on short term and controlled
conditions may not exist in uncontrolled market.
– Changes in socio-economic , climatic conditions may
alter the results.

22. Statistical Methods
• Advantages
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Subjectivity is minimum
Method of estimation is scientific
Estimates are relatively more reliable
Involves smaller cost
Methods
1) Trend Projection Method
2) Econometric Method

23. a)
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Trend Projection
It is a study of movement of variables through time.
Requires long and reliable time-series data
Its based on the assumption that factors responsible for
the past trends will continue to be the same in future.
a) Graphical Method:
– Annual sales data is plotted on a graph
– Line is drawn through the plotted points
– Free line is drawn that the total distance between the
line and points is minimum.
– Second line drawn taking the mid values of variations.
– The trend line is then extended to forecast the
demand for next year.
• The projections may not be realisable as the
extension of trend line involves subjectivity and
personal bias.

24. 1)
Graphical Method
P
Sales
Year

25. 2) Fitting Trend equation:
b) Fitting Trend equation: Least square method:
Trend line is fitted to the time-series data
Linear best fit curve
Minimises the deviation of the actual line
S = a + bT
S = Annual sales
T = time (years)
a & b are constant
∑ S = na + b ∑ T
∑ ST = a ∑ T + b ∑ T
2

26. b) Econometric Method
• It combines statistical tools with economic theories to
estimate economic variables.
• Forecast are more reliable
• This model try to identify all those economic and
demographic variables that influence the future value of
the variable under forecast.
Two types of method:
a) Regression method
b) Simultaneous method

27. b) Econometric Method
a) Regression method
• Establishes casual relationship between
– Dependent variable (demand)
– Independent variables (parameters that impact
demand)
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Most popular method
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As it combines
– Economic theory
• To specific determinants of demand & their
relationship with demand
– Statistical techniques
• To estimate the values of parameter in the
equation. Or estimate the impact in the demand
for a unit change in the determinant

28. b) Econometric Method
a) Regression method
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Simple / Bivariate regression
– If demand of a commodity depends on a single independent
variable
• E.g. – demand for salt / sugar depends largely on
population
– The relationship can be established using ‘least square
method’
• As used in time series
• Only difference is time is replaced by the ‘independent
variable’ on which the demand depends the most

29. b) Econometric Method
a) Regression method
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Multi-variate regression
– If demand of a commodity depends on a more than one
independent variables
• E.g. – demand for sweets, fruits, & vegetables depends
on price of the product, price of its substitutes,
household income, population etc.
– Procedure
• Specify variables that have an impact on demand. This
will be different for different categories
• Next specify the form of equation – linear, logarithmic,
power etc
• Collect the necessary data
• Estimate the value of co-efficient of the independent
variables through statistical techniques. Essentially
done with the help of computer

30. b) Econometric Method
a) Regression method
– It uses one single equation
– It assumes one-way causation i.e. only independent variable
causes
variation in dependent variable and not vice versa
• However, realistically demand for a product also has an
impact on price of the product
– This issue can be addressed through simultaneous equation
model

31. b) Econometric Method
b) Simultaneous method
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Is a complete & systematic approach to forecasting
It involves solving several simultaneous equations for estimating
demand.
It takes two- way causation i.e: simultaneous interaction between
dependent and independent variable. As well as inter-dependence
of independent variables
– For instance
• Demand for white goods depends on product price, price of
substitute, household income, consumer preference,
availability of credit & interest rate
• Interest rate depends on Availability of credit
• Which in turn may depend on many other economic
parameters & government policies at that point.
• And so on
– Thus estimation of demand will require solving all such
functions simultaneously

32. Salient features of good forecasting
method
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Simplicity
Accuracy
Economy
Availability
Applicability
Though mere possession of right tools is does not
necessarily mean accurate forecast. Equally important
is analysts judgement.