Demand forecasting is the process of estimating future demand for a product or service. It involves quantitative and qualitative techniques. Quantitative techniques use past sales data and mathematical models to project trends, while qualitative techniques rely on expert opinions, consumer surveys, and market testing. Accurate demand forecasting allows firms to optimize production and inventory levels but can be limited by changing consumer preferences, lack of past data, and high costs of extensive analysis.

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2. Meaning of Demand Forecasting
“An estimate of sales in dollars or physical
units for a specified future period under a
proposed marketing plan.”
American Marketing Association
Demand forecasting is the scientific and
analytical estimation of demand for a product
(service) for a particular period of time.
It is the process of determining how much of
what products is needed when and where.

3. Categorization of Demand Forecasting
By Level of Forecasting
Firm (Micro) level: forecasting of demand for its
product by an individual firm.
decisions related to production and marketing.
Industry level: for a product in an industry as
a whole.
insight in growth pattern of the industry
in identifying the life cycle stage of the product
relative contribution of the industry in national
income.

4. Categorization of Demand Forecasting
Economy (Macro) level: forecasting of
aggregate demand (or output) in the
economy as a whole.
helps in various policy formulations
at government level.

5. Categorization of Demand Forecasting
By nature of goods
Capital Goods: Derived demand
demand for capital goods depends upon
demand of consumer goods which they
can produce.
Consumer Goods: Direct demand
durable consumer goods: new demand
or replacement demand
Non durable consumer goods: FMCG
.

6. Categorization of Demand
Forecasting
By Time Period
Short Term (0 to 3 months): for inventory
management and scheduling.
Medium Term (3 months to 2 years): for
production planning, purchasing, and
distribution.
Long Term (2 years and more) for
capacity planning, long term capital
requirement, and investment decisions

7. Choice of a forecasting technique
depends on:
Imminent objectives of forecast,
whether it is for a new product, or to gauge
impact of a new advertisement, etc.
Cost involved, cost of forecasting should
not be more than its benefits, here
opportunity cost of resources will also be
important.
Time perspective, whether the forecast is
meant for the short run or the long run

8. Choice of a forecasting technique
Complexity of the technique, vis-à-vis
availability of expertise; this would
determine whether the firm would look
for experts “in house” or outsource it
Nature and quality of available data,
i.e. does the time series show a clear
trend or is it highly unstable.

9. Techniques of Demand Forecasting
Subjective (Qualitative) methods: rely
on human judgment and opinion.
Buyers’ Opinion
Sales Force Composite
Market Simulation
Test Marketing
Experts’ Opinion
Group Discussion
Delphi Method

10. Techniques of Demand Forecasting
Quantitative methods: use
mathematical or simulation models
based on historical demand or
relationships between variables.
Trend Projection
Smoothing Techniques
Barometric techniques
Econometric techniques

11. Subjective Methods of Demand Forecasting
Consumers’ Opinion Survey
Buyers are asked about future buying
intentions of products, brand preferences
and quantities of purchase, response to an
increase in the price, or an implied
comparison with competitor’s products.
Census Method: Involves contacting
each and every buyer
Sample Method: Involves only
representative sample of buyers

12. Subjective Methods of Demand Forecasting
Merits
Simple to administer and comprehend.
Suitable when no past data available.
Suitable for short term decisions regarding
product and promotion.
Demerits
Expensive both in terms of resources and time.
Buyers may give incorrect responses.
Investigators’ bias regarding choice of sample
and questions cannot be fully eliminated.

13. Subjective Methods of Demand
Forecasting
Sales Force Composite / Openion
Survey
Salespersons are in direct contact with the
customers. Salespersons are asked about
estimated sales targets in their respective
sales territories in a given period of time.
Contd…

14. Subjective Methods of Demand Forecasting
Merits
Cost effective as no additional cost is incurred
on collection of data.
Estimated figures are more reliable, as they are
based on the notions of salespersons in direct
contact with their customers.
Demerits
Results may be conditioned by the bias of optimism
(or pessimism) of salespersons.
Salespersons may be unaware of the economic
environment of the business and may make wrong
estimates.

15. Subjective Methods of Demand
Forecasting
Experts’ Opinion Method
i) Group Discussion: (developed by Osborn in
1953) Decisions may be taken with the help of
brainstorming sessions or by structured
discussions.
ii) Delphi Technique: developed by the Rand
Corporation at the beginning of the Cold War,
to forecast impact of technology on warfare.
Way of getting repeated opinion of experts
without their face to face interaction.
Consolidated opinions of experts is sent for
revised views till conclusions converge on a
point.
Contd…

16. Subjective Methods of Demand Forecasting
Merits
Decisions are enriched with the experience
of competent experts.
Firm need not spend time, resources in
collection of data by survey.
Very useful when product is absolutely new
to all the markets.
Demerits
Experts’ may involve some amount of bias.
With external experts, risk of loss of
confidential information to rival firms.

17. Subjective Methods of Demand Forecasting
Market Simulation
 Firms create “artificial market”, consumers are
instructed to shop with some money. “Laboratory
experiment” ascertains consumers’ reactions to
changes in price, packaging, and even location of
the product in the shop.
Grabor-Granger test:
Half of members are shown new product to see whether
they would actually buy it at various prices on a random
price list and then are shown the existing product. Other half
is shown the existing product first and then the new product
to ascertain if a product would be bought at different prices.
Contd…..

18. Subjective Methods of Demand Forecasting
Merits
Market experiments provide information on
consumer behaviour regarding a change in
any of the determinants of demand.
Experiments are very useful in case of an
absolutely new product.
Demerits
People behave differently when they are
being observed.
In Grabor-Granger tests consumers may not
quote the price they may pay.

19. Subjective Methods of Demand Forecasting
Test Marketing
Involves real markets in which consumers
actually buy a product without the
consciousness of being observed.
product is actually sold in certain segments
of the market, regarded as the “test market”.
Choice and number of test market(s) and
duration of test are very crucial to the
success of the results.
Contd….

20. Subjective Methods of Demand Forecasting
Merits
Most reliable among qualitative methods.
Very suitable for new products.
Considered less risky than launching the
product across a wide region.
Demerits
Very costly as it requires actual production of the
product, and in event of failure of the product the
entire cost of test is sunk.
Time consuming to observe the actual buying
pattern of consumers..

21. Quantitative Methods of Demand Forecasting
Trend Projection
Statistical tool to predict future values of a variable
on the basis of time series data.
 Time series data are composed of:
Secular trend (T): change occurring consistently over a
long time and is relatively smooth in its path.
Seasonal trend (S): seasonal variations of the data
within a year
Cyclical trend (C): cyclical movement in the demand for
a product that may have a tendency to recur in a few
years
Random events (R): have no trend of occurrence hence
they create random variation in the series.

22. Quantitative Methods:
Methods of Trend Projection
 Graphical method
Past values of the variable on vertical axis
and time on horizontal axis and line is
plotted.
Movement of the series is assessed and
future values of the variable are forecasted
simple but provides a general indication
and fails to predict future value of demand
Contd…

23. Quantitative Methods:
Methods of Trend Projection
Least squares method
 based on the minimization of squared
deviations between the best fitting line and
the original observations given.
Estimates coefficients of a linear function.
Y=a+bX where a =intercept
and b =slope
The normal equations:
ΣY=na + bΣX
ΣXY= aΣX+ bΣX2
 Once the coefficients of the trend equation are
estimated, we can easily project the trend for
future periods.
Contd…

24. Quantitative Methods :
Barometric Techniques
Barometric Technique alerts businesses to
changes in the overall economic conditions.
Helps in predicting future trends on the basis
of index of relevant economic indicators
especially when the past data do not show a
clear tendency of movement in a particular
direction.
Contd….

25. Quantitative Methods
Simple (or Bivariate) Regression
Analysis:
deals with a single independent
variable that determines the value of
a dependent variable.
Demand Function: D = a+bP, where
b is negative.
Contd…..

26. Quantitative Methods
Problems Associated with Regression
Analysis
Multicollinearity: when two or more
explanatory variables in the regression model
are found to be highly correlated the estimated
coefficients may not be accurately determined.
Heteroscedasticity: Classical regression
models assume that the variance of error terms
is constant for all values of the independent
variables
Contd…

27. Specification errors: Omission of one or
more of the independent variables, or when
the functional form itself is wrongly
constructed or estimate a demand function
in linear form, though the function should
have been nonlinear.
Identification problem: where the
equations have common variables, like a
demand supply model.
Problems Associated with Regression
Analysis

28. Limitations of Demand Forecasting
Change in Fashion: Is an inevitable
consequence of advancement of civilization.
Results of demand forecasting have short
lasting impacts especially in a dynamic
business environment.
Consumers’ Psychology: Results of
forecasting depend largely on consumers’
psychology, understanding which itself is
difficult.

29. Lack of Past Data: Requires past sales data,
which may not be correctly available. Typical
problem in case for a new product.Limitations of Demand ForecastingLimitations of Demand Forecasting
Limitations of Demand Forecasting

30. Uneconomical: Requires collection of data in
huge volumes and their analysis, which may be
too expensive for small firms to afford.
Estimation process may take a lot of time, which
may not be affordable.
Lack of Experienced Experts: Accurate
forecasting necessitates experienced experts,
who may not be easily available. Forecasting by
less experienced individuals may lead to
erroneous estimates.
Limitations of Demand Forecasting