This document acknowledges those who helped the group complete their project on demand forecasting. It thanks God for giving them strength and their teacher for the opportunity. It then provides an overview of topics related to demand forecasting, including definitions of demand and demand forecasting. It discusses factors involved like types and levels of forecasting, importance, objectives and methods. Common methods include survey, statistical, regression and barometric. Challenges in forecasting and criteria for good forecasting are also outlined.

2. ACKNOWLEDGEMENT
First of all , We would like to thank ALLAH ALMIGHTY who
gave us the courage . Health and energy to accomplish our project
in due time and without WHOSE help this study which required
untiring efforts would have not been possible to complete within
the time limit.
Secondly we would like to express my special thanks of gratitude
to my teacher PROF: samiullah for giving us golden opportunity to
do this project on the topic of “demand forecasting” , which also
helped us in doing a lot of Research and we came to know about
so many new things.

3. TOPIC:
DEMANDESTIMATIONANDDEMANDFORCASTING
GROUP
MEMBE
RS
ADNAN
ZAFAR
FARHAN
ALI
ATIQE
UMAR
ANWAR
WAQAS
BAHIR
NADEEM
WARIS

4. What is demand
 Demand refers to how much
(quantity) of a product or service is
desired by buyers at various prices.
 The amount of a particular economic
good or service that a consumer or
group of consumers will want to
purchase at a given price....

5. DEMANDFORECASTING
Demand Forecasting is the demand for
products that are expected to be realized
for a certain period in the future.
According to Evan J. Douglas,
Demand forecasting may be defined as the
process of finding value for demand in
future time period

6. FACTORSINVOLVEDINDEMAND
FORECASTING
• TYPES OF FORECASTING
• Levels of forecasting.
• IMPORTANCE OF FORECASTING
• OBJECTIVE OF FORECASTING
• Methods of forecasting.
• Nature of commodity.
• Nature of competition.

7. TYPESOF FORECASTING
Short term forecasting:- This type of forecast is made of a time
frame from one day to three months. These types of forecasts are
utilized for day to day production planning, inventory planning,
workforce application planning, etc.
Medium term forecasting:- This type of forecast is made for a
time frame from three months to three years. These types of
forecasts are utilized production and layout planning, sales and
marketing planning, cash budget planning and capital budget
planning.
Long term forecasting:- This type of forecast is made for a time
frame of more than three years. These types of forecast are
utilized for long-term strategic planning in terms of capacity
planning, expansion planning, etc.

8. LEVELSOF FORECASTING
Micro level:-
It refers to demand forecasting by individual business firm for estimating the demand
for its product.
Industry level:-
It refers to the demand estimate for the product of the industry as whole. It relates to
market demand as whole.
Macro level:-
It refers to the aggregate demand for the industrial output by nation as whole. It is
based on the national income or aggregate expenditure of the country.

9. IMPORTANCEOF FORECASTING
• Production planning.
• Sales forecasting.
• Control of business.
• Correctness of management decisions.
• Growth and long-term investment programmes.
• Stability.
• Success in business.
• Estimation of financial requirements.
• Promotion of new business.

10. OBJECTIVESOFDEMANDFORECASTING
• Helping continuous production.
• Regular supply of commodities.
• Formulation of price policy.
• To formulate effective sales performance.
• Arrangement of finance.
• To determine productive capacity
• Labour requirements.

11. Methodsof
forecasting
Survey method
1 .Survey of buyers
intention.
2.Survey of experts
opinion.
3. Collective opinion
method
4. Simulated market
situation.
Statistical method
1.Trend projection
method
2.Method of moving
averages.
3.Regression method.
4.Barometric method.
5.economic indicators.

12. SURVEYMETHOD
• Forecast are done both for established products and new
products. Demand forecasting for the established products can be
done in routine manner with information drawn from existing
markets and past behavior of sales.
• Forecasts for new products are necessarily custom built jobs that
involve more ingenuity and expense. Since the product has not
been sold before it is difficult to get any clue for demand
forecasting.

13. SURVEYOF BUYERSINTENTIONSOR CONSUMER’S
SURVEY.
• Least sophisticated method and most direct method of estimating
sales in the near future.
• In this method customers are directly contacted in order to find out
their intention to buy commodities for future. This method is opinion
survey method.
• Intention’s are recorded through personal interview, mail or post
surveys and telephone interviews.
• There are two types of survey
1. Complete enumeration method: it covers all potential consumers in
the market and interviews conducted to find out probable demand.
2. Sample survey method: it covers only few customers selected from
total potential consumers interviewed and then the average demand
is calculated on the basis of the consumer’s interviewed.

14. SURVEY OR EXPERT OPINION.
• There are people who are experts in the field of selling goods like
wholesalers, and retailers.
• They will be in position to tell what consumers would buy. Many
companies get their basic forecast directly from their salesman who
have most intimate feel of the market.
• The wholesalers and retailers by their experience are in the
position to feel about the probable sales in the coming year.

15. Collective opinion method
Also called “sales force polling”, salesmen are required to estimate
expected sales in their respective territories and sections.
Simple – no statistical techniques.
Based on first hand knowledge.
Quite useful in forecasting sales of new products.

16. SIMULATED MARKET SITUATION
• Under this method an artificial market situation is created and
participants are selected.
• These are called consumers clinics
• Those participants are given some money and asked to spend the
same in artificial departmental stores. Different prices are set up
for different groups of buyers. The responses to price changes are
observed and accordingly necessary decisions about price and
promotional efforts are undertaken.

17. STATISTICALMETHODS
• Demand forecasting uses statistical methods to predict future
demand. This method is useful for long run forecasting for the
existing products.
• There are several ways of using statistical or mathematical data.
They are:
• 1. Trend projection method or time series
• 2. Method of moving averages
• 3. Regression method
• 4. Barometric methods.
• 5. Other methods

18. 1. TRENDPROJECTIONMETHOD
• This method is based on analysis of past sales. A firm which has
existence for quite long time will have accumulated considerable data
regarding sales for a number of years. Such data is arranged
chronologically with intervals of time. This is called time series.
• It has 4 types of components namely:
• 1. Secular trends
• 2. Seasonal variation
• 3. Cyclical variation
• 4. Random variations.

19. • The trend in Time series can be estimated by using any one of the
following of methods
• 1. Least square method
• 2. Free Hand method
• 3. Moving averages method
• 4. Method of semi averages.

20. TRENDPROJECTION
• A time series analysis of sales data over a period of
time is considered to serve as a good guide for sales
or demand forecasting.
• For long term demand forecasting trend is computed from
the time base demand function data.
• Trends refer the long term persistent movement of data in
one direction upward or downward. There are 2
important methods for trend projection.
1. Least square method
2. Method of moving averages.

21. LEASTSQUAREMETHOD
• The trend line if fitted by developing an equation giving the nature and
magnitude of the trend. The common technique used in constructing the line of
best fits is by the method of least squares.
• The trend is assumed to be linear. The equation for straight line trend is y=a+bx
• Where “a” is the intersect and “b” shows the impact of independent variable. Sales
are dependent on variable “y” since sales vary with time periods which will be the
independent variable “x” thus “y” intercept and the slope of line are formed by
making appropriate substitutions in the following normal equations
• ΣY = Na+bσx --------------(1)
• ΣXY = aσx + bσx2----------------- (2)

22. • YEAR SALES X X2 XY
• 1996 45 1 1 45
• 1997 52 2 4 104
• 1998 48 3 9 144
• 1999 55 4 16 220
• 2000 60 5 25 300
• N=5 ΣY=260 ΣX=15 ΣX2=55 ΣXY=813

23. • SUBSITITUTING THE ABOVE VALUES IN THE TWO
NORMAL EQUATIONS WE GET THE FOLLOWING:-
• 260=5a+15b----------------
• 813=15a+55b-----------------
• Solving both equation we get b=3.3
• 260=5a +15
• 260=5a+49.5
• A=42.1
• Therefore the equation for the line of best fit is
equal to:
• Y=42.1+3.3X.

24. • Using this equation trend values for previous years and
estimates of sales for 2001. The trend values and estimates
are as follows:-
• Y 1996 = 42.1 +3.3(1)= 45.4
• Y 1997 = 42.1+3.3(2)= 48.7
• Y 1998 = 42.1+3.3(3)= 52.2
• Y 1999 = 42.1+3.3(4)=55.3
• Y 2000 = 42.1+3.3(5)=58.6
• Y 2001 = 42.1+3.3(6)=61.9. Based on the trend projection
equation illustrated above, the forecast sales for the year 2001
is Rs 61.9 Lakhs.

25. METHODOF MOVINGAVERAGES.
• The trend projection method is very popular in business circles on
account of simplicity and lesser cost. The basic idea in this
method is that past data serves a guide for future sales.
• This method is inadequate for prediction whenever there are
turning points in the trend itself. While irregular factors such as
storms and strikes can be averaged out and contained into the
equation it is desirable to know how valuable such an exercise
could be.

26. • The calculation depends upon whether the period should be
odd or even.
• In the case of odd periods like (5, 7, 9) the average
observations is calculated for a given period and the value
calculated value is written in front of central valuable of the
period, say 5 years. The average of values of five years is
calculated and recorded against the third year. In the case of
five yearly moving averages the first two years and last two
years of data will not have any average value.
• If the period is even say four years then average of four yearly
observations is written between second year and third year
values. After this centering is done by finding average of
paired values. Let us take up the following illustration:-

27. • The following are the annual sales of dresses during the
period of 1993-2003. We have to find out trend of the sales
using a) 3 yearly moving averages, b)4 yearly moving
averages.
• 3 yearly moving averages will be
• A+b+c/3, b+c+d/3,c+d+e/3 ,d+e+f/3-------
• The value of 1993+1994+1995/3
• 12+15+14/3 = 41/3=13.7.

28. • YEAR SALES 3 YEARLY 3 YEARLY
MOVING
• MOVING TOTAL AVERAGE trend
values
• 1993 12 (-) -
• 1994 15 41 41/3=13.7
• 1995 14 45 45/3=15
• 1996 16 48 48/3=16
• 1997 18 51 51/3=17
• 1998 17 54 54/3=18
• 1999 19 56 56/3=18.7
• 2000 20 61 61/3=20.2
• 2001 22 67 67/3=22.3
• 2002 25 71 71/3=23.7

29. ADVANTAGES AND DISADVANTAGES
• This method is simple and can be applied easily.
• It is based on mathematical calculations and finally this is
more accurate.
• The disadvantage of this method of moving average is that it
gives equal weight age to the data related to different periods
in the past. It cannot be applied it if some observations are
missing.

30. REGRESSIONMETHOD
 It may be associated with competitors,
advertising ones own advertising change in
population, income and size of family and
environmental factors.

31. TRENDPROJECTIONBY REGRESSIONMETHOD
 This is a mathematical tool, with this adapting “method of
least squares” a trend line can be fixed to know the
relationship between time and demand/sales. Based on this
trend line sales /demand can be projected for future years.
• This is an inexpensive method of forecasting. The data will
be available within the organization and based on this data
demand or sales, can be projected for future years.

32. YEAR:- 1998 1999 2000 2001 2002
SALES:- 240 280 240 300 340
YEAR SALES TIME TD PRODUCT
DEVIATION SQUARED TIME DEVIATION
1998 24O -2 4 -480
1999 280 -1 1 -280
2000 240 0 0 0
2001 300 +1 1 300
2002 340 +2 4 +680
X=5 Σy=1400 Σx=0 Σx2=10 Σxy=220

33. • The equation is y=a+bx.
• In this equation “a” and “b”.
• a=Σy/n=1400/5=280.
• b=Σxy/Σx2=220/10=22.
• Now applying values to regression equation the equation will be
y=280+22x
• From this we can ascertain sales projection from 2003, 2004,
2005.
• For the year 2003=280+22(3)=Rs. 346 crores.
• For the year 2004=280+22(4)=Rs. 368 crores.
• For the year 2005=280+22(5)=Rs. 390 crores.

34. BAROMETRICMETHOD
 At times, a business concern may assign the task of
demand forecasting to some expert
 It would attempt to forecast on the basis of signals
received from the polices adopt or the events that had
taken place within the country or in the other country

35. Disadvantages
 Does not predict the magnitude of changes
very well
 The method can be used for used term
forecast only
Advantages
 Simple method
 Predict directional change quite
accurately

36. FORECASTINGDEMANDFORNEW
PRODUCTS
 Evolutionary approach:-
project the demand for new product as an outgrowth and evolution of
existing old product.
 Substitute approach:-
According to this approach the new product is to be considered as
substitute for the old product
 Growth curve approach:-
The rate of growth and ultimate level of demand for new products can
be estimated on the basis of pattern of growth for old products.

37. Opinion polling approach:-
Estimate the demand by direct inquiry of the ultimate purchasers
then blow up the sample to full scale.
Sending an engineer with drawing and specifications for new
industrial products to a sample company is an example of opinion
polling which is widely used to explore the demand for new products.
Sales experience approach:-
the new product is offered for sale in a sample market and then the
demand for new product is estimated in fully developed market.
Vicarious approach:-
Specialized dealers are contacted because they have intimate feel of
the customers.

38. DIFFICULTIESIN FORECASTING
• Changes in size and characteristics of population
• Changes in national and international politics
• Existing stock of goods
• Constraints of the firm
• Weather changes and natural disasters.

39. CRITERIAFORGOODFORECASTING.
According Joel dean lays down the following criteria of good
forecasting method:-
Accuracy
Forecast must be accurate as far as possible. Its accuracy must be
judged by examining the past forecast with present situation.
Simplicity
A simpler method is always more comprehensive than a complicated
one.

40. Economy
It should be economy .we should have to choose those method
which will be less costly and less time consuming
Quickness
It should yield quick results. A time consuming method may delay
the decision making process.
Flexibility
Not only the forecast is to be maintained up to date there should
be possibility of changes to be incorporated in the relationships
entailed in forecast procedure, time to time.