demand forecasting & techniques

1. Presenting by -
P.JOEL PRAKASH

2. What is demand Forecasting ?
 “PREDICTIONS ARE USUALLY DIFFICULT,
ESPECIALLY ABOUT THE FUTURE”
 Prediction or estimation of a future situation, under
given conditions.
 Classified into categories: (i) Passive forecasts
(ii)Active forecasts
 Important aid in effective and efficient planning
 It is backbone of any business

3. Importance of demand
forecasting
 Crucial to manufacturer ,wholesaler, retailer
 Business decisions
 Planning for future finished goods
 accurate demand forecasts lead to efficient operations
and high levels of customer service
 Improve quality & effectiveness of product

4. Factors determining demand
forecasting
 Time factor
 Level of forecasting
 General or Specific forecasting
 Problems & methods of forecasting
 Classification of goods
 Knowledge of different market conditions

5. Levels of Demand Forecasting
1) Micro Level- Demand forecasting by individuals
business firm for forecasting the demand for its
product.
2) Industrial Level- Demand estimate for the product of
the industry
3) Macro Level- Aggregate demand forecasting for
industrial output at the national level- it is based on
the national income/ aggregate expenditure of the
company.

6. Types of Forecasts by Time Horizon
Short–range Forecast
• Usually < 3 months
Medium-range
Forecast
• 3 months to 2 year
Long-range Forecast
• 2 years
Quantitative
methods
Qualitative
methods

7. Approach of forecasting
Qualitative
Quantitative
FORECASTING

8. Qualitative Forecasting approach
 Obtaining information on likes and dislikes of the
consumers
 It is short term forecasting
 Demand forecasts for new products

9. Qualitative Forecasting approach
I. Consensus approach
 Expert Opinion method
Forecasting the demand on
base of opinion of several
experts who are more relevant
to that area of interest
 Delphi method
It is a systematic, interactive
forecasting method which
relies on a panel of experts

10. Complete Enumeration survey method
Complete survey
on all the
consumers for
commodity
Ex: 1.Indians addicted to
smartphones, says survey
2. About 70 percent students
today own smart phones in
cities, according to a survey
by software services firm
TCS
By these survey many young
entrepreneurs came forward
and setting up there own
business
Survey approach

11. Sample Survey Method:
Only few consumers
are selected and
there views are
collected
Ex: samples of
Maggie from
different shops of
city are collected for
testing

12. End-User Survey Method:
Focus on forecasting
the demand on
intermediary goods
Ex:
Cement use for
construction of
houses, buildings,
hotels, etc

13. Sales Force Opinion Survey Method
Employees of
Company who are
the part of sales &
marketing teams are
asked to predict the
demand

14. Quantitative Forecasting
 Forecast of future demand is based on past data &
extrapolating it to make the forecast of future levels.
 It is long-term forecasting
 Demand forecast for existing products can be made by
these method accurately

15. Levels of Approach in Quantitative
forecasting
 Trend Projection approach
 Secular-Trend method: Change occurring consistent over
period of time Ex: Sales of PC’S increases over a year
 Seasonal-Trend Method: Seasonal variation of the data
within a year Ex: raincoats are dependent of weather
 Cyclical-Trend Method: Demand for the product that may
have a tendency to recur in a few years. Ex: Changes in BSE

16. Barometric approach
This type of approach is constructs an index of
relevant economic indicators and forecast
future trends on the basis of these indicators.
These indicators are
leading indicators tells us where we are
heading
coincident indicators tells us where we are
lagging indicators tells us where we lagging
behind
Commonly Used indicators:-
(1) Gross National Income.
(2) Employment
(3) Agriculture Income
(4) Bank Deposits etc.
(5) Industrial Production
(6) Construction contracts
awarded for building materials.
(7) Personal Income.
Andrew Carnegie the famous industrialist used to
estimate the future of steel by counting the no of
chimneys emitting smoke in Pittsburg
Ex:In 2001, Gujarat earthquake all constructions
are collapsed while rebuilding the cement
became the leading indicators

17. Economic approach
It is on basics of
systematic analysis of
economic relationships
by combing economic
theory with
mathematical &
statistical tools
Regression
method: To develop
the functional
relationship & analyze
the values of dependent
variables with those of
one or more in
dependents variables
Plain
biscuits
Savory
Biscuits
Filled
Biscuits
Sales of biscuit by category

18. Simultaneous Method:
Incorporates
mutual
dependences
among variables.
Ex: demand
forecasts on
electricity based
on many factors

19. Forecasting Limitations
 Change in fashion
 Consumer’s Psychology
 Uneconomical
 Lack of Experts
 Lack of past data