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
