Forecasting
Dr.Arun Kaushal
INTRODUCTION
Our life is full of uncertainties and so is the buisness.
Changes are even seen in the behaviour of consumer
depending on his tastes and preferences over time .
In short all calculations and speculations of a firm
regarding the details of his product depends on
demand.
And in this topic we will study about various methods
to calculate those predictions and objectives behind
them.
MEANING
A forecast is a guess or anticipation or a prediction about
any event which is likely to happen in the future.
For example : An individual may forecast his job
prospects, a consumer may forecast an increase in his
income and therefore purchases, similarly a firm may
forecast the sales of its product.
Demand Forecasting means predicting or estimating the
future demand for a firm’s product or products .
Important aid in effective and efficient planning It is
backbone of any business
The short term objectives are as follows :
1.Formulation of Production policy : helps to overcome the
problem of over production and under production.
2.Regular Availability of Labour : helps to properly arrange
skilled and unskilled labour.
3.Regular supply of Raw Material : helps in predicting
requirement of raw material in future .
4.Arrangement of funds : enables to estimate the financial
requirements .
5.Price policy formulation : enables the management to
evolve a suitable price strategy .
If the period of forecasting is more than one year then it
is termed as long term forecasting .
•The long term objectives are as follows :
1.Labour requirements : helps in arranging skilled
labour .
2.Arrangement of funds : enables to arrange long
term finances on reasonable conditions.
3.To decide about Expansion :enables to plan for a
new project as well as expansion and modernisation
of existing unit .
NEED AND SIGNIFICANCE
• It is necessary to forecast demand in buisness because :
1. Effective planning : provides scientific and reliable
basis for anticipating future operations
2. Reduction of uncertainty
: aims at reducing the
area of uncertainty that surrounds mangerial decision
making with respect to costs , production, sales , profit
etc .
3. Investment decision : investments are made keeping in
mind the the returns and returns depend on market
demand.
4. Resource allocation : efficient allocation of resources
when future estimates are available .
5. Pricing decisions : in order to pursue optimal pricing
strategies firm need to have complete information about
the future demand. Two concepts arises here :
(a) Overoptimistic :these estimates may lead to an excessively
high price and lost sales.
(b)Over pessimistic : these estimates of demand may lead to a
price which is set too low resulting in losses.
6. Competitive strategy : the level of demand for a product
will influence decisions , which the firm will take
regarding the non-price factors .
7. Managerial control : forecasting disclose the areas where
control is lacking . It is must in order to control costs of
production .
How
??
Step 5 estimating future
events
Step 4 Gather and analyze data
Step 3 Select a forecasting
technique
Step 2 Selection of products
SO ,WE KNOW WHAT IT’S ALL
ABOUT!!!
NOW LETS ANALYSE THE
METHODS OF
DEMAND FORECASTING.
QUALITATIVE
TECHNIQUES
They mainly employ human judgment to predict future
events .
They are also called macroeconomic methods.
This involves the prediction of economic aggregates such as ,
unemployment, GDP growth, short-term interest rates etc..
This involves :
1) Expert opinion methods
2) Survey methods :
a.Complete enumeration survey b.Sample survey
c.Sales force opinion
• Expert Opinion Method : This technique of forecasting
demand seeks the views of experts on the likely level of
demand in the future. They have a rich experience of the
behaviour of demand.
• If the forecasting is based on the opinion of several experts,
then it is known panel consensus.
• A specialized form of panel opinion is the Delphi Method.
This method seeks the opinion of a group of experts through
mail about the expected level of demand.
• The responses so received are analyzed by an
independent body
• Survey Methods :
In it we have four major survey methods : -
a) Consumers Complete Enumeration Survey :
• In this method data is collected from all the customers and
then added up to arrive as the total expected demand of the
product.
• The method is comprehensive and can give better forecasts of
demand.
• This method is time consuming and costly.
b) Consumers Sample Survey :
• Only a few consumers are selected and their views on
the probable demand are collected.
• Thus, it is a miniature form of Complete
Enumeration Survey.
• The sample is considered to be a true representation
of the entire population.
• This method is simple and cheaper.
• The results of survey can be obtained quickly and
results are good.
c) Sales Force Opinion Survey :
• In this method sales persons are expected to estimate
expected sales in their respective territories.
• The sales force, which has been selling the product to
wholesalers / retailers / consumers over a period of
time, is considered to know the product and the
demand pattern very well.
• These method does not require intricate mathemathical
calculations.
• This method is based on the first hand knowledge of
the salesman.
• It is useful to forecast the sales of new products.
“ARE YOU STILL THERE??”
HMMM GREAT !!!
THAT FINISHES THE
QUALITATIVE
METHODS.
NOW LETS LOOK AT THE
“QUANTITATIVE
METHODS”
QUANTATIVE TECHNIQUES
This method involves various statistical tools to data
for predicting future events.
These methods are also called microeconomic
methods.
Involves the prediction of activity of particular firms,
branded products, commodities, markets, and
industries.
They are much more reliable.
a) Trend Project ion Met hod :
• This method is used when a detailed estimate has to
be made.
• Time plays a n important role in this method .
• This method uses historical and cross –sectional
data for estimating demand
This technique assumes that whatever has been the
pattern of demand in the past, will continue to hold
good in the future as well.
• In this method data is arranged
chronologically which yields a ‘time series’.
• The time series represent the past pattern
of effective demand for a particular
product and is used to project the trend of
the time series.
• To do so there are two methods :
a.Graphical method
b.Least Square method
Graphical method :
• A trend line can be fitted through a series
graphically .
• Old values of sale for different areas are plotted on
graph and a free hand curve is drawn passing through
as many points as possible .
• Based on trend equation, we find ‘Line of Best Fit’
and then it is projected in a scatter diagram,dividing
points equally on both sides
Least Square Method :
•It is a mathematical procedure for fitting a line
to a set of observed data points in a manner that
the sum of the squared differences between the
calculated and observed value is minimised.
•The linear trend is the most widely used mode
of time series analysis.
It is represented:
Y= a + b x
•Y=Demand
•X= Time Period
•a & b are constants .
•For calculation of Y for any value of X
requires the values of a & b .These are
calculated using :
∑Y=na + b∑X
∑XY=a∑X+b∑X²
PROBLEM & SOLUTION
• The data relate to the sale of generator sets of a
company over the last five years
• Year : 2003
sets : 120
2004
130
2005
150
2006
140
2007
160
Estimate the demand for generator sets in the year 2012
if the present trend continues
Let the base year be 2002.
YEAR
X
Y
X2
XY
2003
1
120
1
120
2004
2
130
4
260
2005
3
150
9
450
2006
4
140
16
560
2007
5
160
25
800
TOTAL
15
700
55
2190
For a linear equation Y = a + bX The set of normal equation are :
ΣY = na + bΣX , ΣXY = aΣX + bΣX2
1.Substituting the Table Values in equation (ii) & (iii), We get
700 = 5a +15b
2190 = 15a + 55b
2.By multiplying equation iv by 3 and subtracting it from
equation v we get
10b =90
b =9
3.Substitute this value in equation iv we have
700 =5a +15 b
700 = 5a +15 (9)
5a =565
a = 113
Trend equation Y=113 + 9x
For 2012 ,x will be 10 (2012 - 2002)
Y(2012)
= 113+9 x 10 =203 sets
b) Baromet ric Met hod :
• Method uses business barometers or indicators of various
economic phenomena.
• term Barometer is used to indicate the economic
The
phenomena.
• assumption behind this
The
is that the past pattern
tend to repeat themselves in future and future can be
predicted with the help of certain happenings of the
• present.
Forecasting Techniques that use the lead and lag
relationship between Economic variable for predicting
the directional changes in the concerned variables are
known as Barometric Techniques.
• Some of the important indicators are : a.Employment
b.Wholesale prices
c.Industrial production
d.Gross national product
Example : The bhuj earthquake in January 2001, led to a
• massive destruction of Property and buildings in Gujrat. This
necessitated constructions of building. The construction was
followed by a spurt in demand for cement, fans, Tube lights
etc. Thus one can say, that the construction of buildings leads
to the demand for cement.
In this case the construction of building is the leading
• indicator or the barometer.
c) Economet ric met hods :
• Refers to the application of mathematical economic
theory and statistical procedures to economic data to
establish quantitative results.
• These models are very complex in practice as they
combine the knowledge of economics , mathematics
and statistics.
• Employs the following two :
1. Regression method
2. Simultaneous Equations
Regression Method :
•Linear regression analysis establishes a relationship
between a dependent variable and one or more
independent variables.
•In simple linear regression analysis there is only one
independent variable.
•If the data is a time series, the independent variable is
the time period.
•The dependent variable is whatever we wish to
forecast.
•
Regression Equation
This model is of the form:
Y = a + bX
Where,
Y = dependent variable
X = independent variable a = y-axis
intercept
b = slope of regression line
• Solution:
a = (∑X²) ( ∑Y) - (∑X )( ∑X Y)
N∑X²
- (∑X )²
b = N∑X Y
N∑X²
- (∑X )( ∑ Y)
- (∑X )²
Example :
• The data of a firm relating to sales and advertisement
is given below .If the manager decides to spend Rs 30
mill in the year 2005 what will be the prediction for
sales
YEAR
AD.EX.
SALES
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
5
8
10
12
10
15
18
20
21
25
45
50
55
58
58
72
70
85
78
85
YEAR
AD.EX mill
SALES(‘0000 X2
) units
XY
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
5
8
10
12
10
15
18
20
21
25
45
50
55
58
58
72
70
85
78
85
25
64
100
144
100
225
324
400
441
625
225
400
550
696
580
1080
1260
1700
1638
2125
N=10
∑X=144
∑Y=656
∑X2=2448
∑XY=10254
• Using formula the calculated values of a &
b are :
a = 34.54
b = 2.15
• Therefore , for Y =a + b
x Y=34.54
+2.15 x ,
x =30
Y =34.54+2.15 (30)= 99 Thousand
Simultaneous Equations :
• When the inter relationship between the economic variables
becomes complex, the use of single equation regression method
becomes difficult. In such cases forecasting of demand is done
using multiple simultaneous equations. This is the complex
statistical methods of forecasting.
These variables are of two types :
• endogenous,
• exogenous.
The number of equation in such a model is equals the number
of endogenous variables.
WARNING !!
The limitations are :
Forecasts are subject to degree of error and they can
never be made with 100% accuracy.
Also quantitative techniques are based on certain
assumptions so conclusions are not better.
Managers often neglect to examine whether the
forecasts are supported by reliable information.
QUERIES ??
(IF GENUINE PLEASE THEN ONLY)