demand forecasting

1. Demand Forecasting

2. Chapter Outline
 Meaning of Demand Forecasting
 Techniques of Demand Forecasting
 Subjective Methods of Demand Forecasting
 Quantitative Methods of Demand Forecasting
 Limitations of Demand Forecasting

3. Demand forecasting
 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.

4. Categories of forecasting
 Macro level
 GDP
 Components of GDP
 Share of manufacturing in total GDP in 2011
 Industry level
 Industry sales- car sales in 2011
 Firm level
 Sales of Tata Indica in 2011

5. Choice of forecasting technique
 Objective of forecast
 New product, impact of advertisement
 Cost effective
 Opportunity cost of resources employed
 Time perspective
 Urgency of forecast- breaking of epidemic
 Long run/short run
 Availability of data
 Quality and quantity

6. Techniques of Demand Forecasting
 Qualitative (subjective) technique
 Rely on human judgment and opinion
 Experts’ Opinion
 Group Discussion
 Delphi Method
 Sales force composite
 Opinion polls
 Market research
 Market simulation
 Test marketing
 Surveys of spending plans
 Barometric technique

7.  Quantitative technique
 Use mathematical or simulation models
 Based on historical demand data or
 Relationship between demand and other
variables
 Naïve techniques
 Trend Projections
 Smoothing Techniques
 Econometric Techniques
Techniques of Demand Forecasting

8. Qualitative Technique
 Experts opinion
 Group Discussion
 Within a corporation (jury of executive opinion)
 Structured discussion on topics/ forums
 Eg., stock market, beauty products

9.  Experts opinion
 Delphi Method (Rand Corporation in 1950)
 Forecast the impact of technology on warfare
 Experts do not meet face to face
 Sequential series of written Q & A
 Consolidated opinions of experts is sent for
revised views till conclusions converge on a
point.
Qualitative Technique

10.  Expert’s opinion- Delphi Method
 Merits
 Decisions are enriched with the experience of
competent experts.
 Very useful when product is absolutely new to all
the markets.
 Demerits
 Experts’ may involve some amount of bias.
 Sometimes difficulty in assessing the degree of
expertise
 With external experts, risk of loss of confidential
information to rival firms.
Qualitative Technique

11.  Sales force composite
 Salespersons are asked about estimated sales
targets in their respective sales territories in a
given period of time.
 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.
Qualitative Technique

12.  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.
 This method is ideal for short term and not for
long term forecasting
Qualitative Technique

13.  Opinion poll (Buyers’ opinion, consumers
opinion survey)
 consumers future buying intentions of
 Products
 Brand preferences
 Quantities purchased
 Response to price increase
 Implied comparison with competitor’s products
 Census Method: Involves contacting each and every
buyer
 Sample Method: Involves only representative sample
of buyers
Qualitative Technique

14.  Opinion Poll
 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
 Investigators’ bias regarding choice of sample
and questions
Qualitative Technique

15.  Market research
 Market simulation
 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 for pricing strategy
Qualitative Technique

16.  Market Research- Market simulation
 Merit
 Provides information on changing consumer
behaviour and impact of determinants of
demand
 Very useful in case of new products
 Demerits
 People behave differently when they are being
observed.
 In Grabor-Granger tests consumers may not
quote the price they may pay
Qualitative Technique

17.  Market Research
 Test marketing
 product is actually sold in certain segments of the
markets
 Location, no. of test markets, duration of test are
very crucial to the success of the results.
 Merits
 Most reliable among qualitative methods.
 Very suitable for new products.
 Less risky than launching the product directly
Qualitative Technique

18.  Market Research- Test marketing
 Demerits
 Costly
 Requires actual production
 Failure means entire cost of test is sunk.
 Time consuming
 Extrapolation may not give accurate results
 Markets are geographically widely distributed
Qualitative Technique

19. Qualitative Techniques
 Surveys of spending plans
 More macro type of study
 Income spending habits of consumers
 NSSO survey is India on consumer expenditure
 Proportion of income spent on various items

20.  Barometric Technique
 Alert economic conditions.
 Helps in predicting future trends on the basis
of index of relevant economic indicators
 Particularly helpful when past data do not show
any trends
 Eg., forecasting the impact of recession of
2008-09
Qualitative Techniques

21. Qualitative Techniques
 Indicators may be
 Leading indicators
 Indicators that move ahead of economic events
 Export-import values, Building permits
 Coincident indicators
 Move up or down simultaneously with economic
activity
 Industrial production
 Lagging indicators
 Move with economic series after a period of time
 Average duration of employment, commercial and
industrial loan outstanding

22. Quantitative Techniques
 Naïve forecasting techniques
 Compound Growth Rate
 Trend Projections
 Smoothing Techniques
 Econometric technique

23. Quantitative Techniques
 Constant compound growth rate
 Appropriate when variable is expected to
increase at a constant percentage
 CGR = (E/B) (1/n)
-1 => E/B = (1+i)n
 E : ending value, B : beginning value, n: no. of
years, i: growth rate
 Demerit
 Does not take the fluctuations into
consideration

24. Quantitative Techniques
 Trend Projections
 Statistical tool to predict future values of a variable
on the basis of time series data
 Secular Trend (T)
 Direction of movement of data over long period of time
 Cyclical trend (C)
 Business cycles
 Seasonal trend (S)
 Seasonal variations within a year
 Random events (R)
 Have no trend of occurrence

25.  Additive Form: Y = T + S + C + R
 Multiplicative Form: Y = T x S x C x R
Log Y= log T + log S + log C + log R
 Methods of trend projection
 Graphical
 Linear regression models
 ARIMA or Box Jenkins Method
Quantitative Techniques

26.  Smoothing Techniques
 Moving Average
 Based on averages of recent past data
 Et+1 = ( Xt +Xt-1+…+Xt-N-1) / N
 E: forecast, X: actual observation
 Eg., 3 month moving average, 5 month moving
average
 Weighted moving average
 Attaching weights to the past data
 Et+1 = ( w1Xt +w2Xt-1+…+wnXt-N-1) / N
Quantitative Techniques

27.  Exponential smoothing
 Greater weight is assigned to most recent data
 Et+1 = wXt + (1-w)Et
 0< W <1
 Larger the W, greater the importance of the
observation
 If series is volatile – less smoothing effect
Quantitative Techniques

28.  Econometric Techniques
 Causal or explanatory forecasting techniques
 Regression analysis
 Single equation technique
 Multiple equation technique
 Simultaneous equation technique
Quantitative Techniques

29. Limitation of Demand forecasting
 Changing fashion changes preferences of
consumers
 Consumers psychology
 Understanding of this is very difficult
 Uneconomical for small firms
 Time required to do the analysis
 Data collection is costly
 Lack of experienced experts
 Lack of past data

30. Limitations of Demand Forecasting
 Change in Fashion:
 Consumers’ Psychology: Results of forecasting depend
largely on consumers’ psychology, understanding which
itself is difficult.
 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.

31.  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.
 Lack of Past Data: Requires past sales
data, which may not be correctly
available. Typical problem in case for a
new product.