The document discusses the importance of forecasting in organizational planning, emphasizing its role in investment and resource allocation decisions. It distinguishes between forecasting, which relies on statistical techniques and historical data, and prediction, based on subjective judgment. Additionally, it covers types of forecasting, their methods, factors influencing sales, and highlights the benefits and limitations of sales forecasting.

2. INTRODUCTION
 Forecasting plays a crucial role in the
development of plans for the future
 It is an essential tool for the organization to
know what level of activities one is planning
before investment in inputs i.e. man,
machines and materials be made

3. INTRODUCTION
Before making an investment decision, many questions
will arise like:
 What should be the size or amount of capital
required?
 How large should be the size of the work force?
 What should be the size of the order and safety
stock?
 What should be the capacity of the plant?
The answer to above question depends upon the
forecast for the future level of operations.

4. CONTD..
 Forecasting as defined by American
Marketing Association is: “An estimate of
sales in physical units (or monetary
value) for a specified future period under
proposed marketing plan or program and
under the assumed set of economic and
other forces outside the organization for
which the forecast is made”.

5. FORECASTING Vs PREDICTION
Prediction:
 Prediction is an estimate of future event
through subjective considerations other than
just the past data.
 For prediction, a good subjective estimation
is based on managers skill, experience and
judgment.

6. CONTD..
Forecasting:
 Forecasting is based on the historical data
and it requires statistical and management
science techniques.
 It is an estimate of future event achieved by
systematically combining and casting
forward in a predetermined way data about
the past.

7. NEED FOR SALES FORECATING
 Majority of the activities of the industries depend upon the
future sales.
 Projected sales for the future assists in decision-making
with respect to investment in plant and machinery, market
planning programs.
 To schedule the production activity to ensure optimum
utilization of plant’s capacity.
 To prepare material planning to take up the replenishment
action to make the materials available at right quantity
and right time.
 To provide an information about the relationship between
sales for different products as a function of time.
 Forecasting is going to provide a future trend which is
very much essential for products design and
development.

8. LONG TERM AND SHORT TERM FORECASTING
 Forecasts which cover the period of less than 1
year are called as short term forecasting
 Short term forecasts are made for the purpose
of materials control, loading and scheduling and
budgeting
 Forecast which cover the period of more than 1
year (5 years or 10 years) are termed as long
term forecasting
 Long term forecast are made for the purposes
of product diversification, sales and advertising
budgets, capacity planning and investment
planning.

9. FACTORS AFFECTING SALES FORECASTING
External Factors
 Relative state of the economy
 Direct and indirect competition
 Styles or fashions
 Consumer earnings
 Population changes
 Weather

10. FACTORS AFFECTING SALES FORECASTING
Internal Factors
 Labour problems
 Inventory shortages
 Working capital shortage
 Price changes
 Change in distribution method
 Production capability shortage
 New product lines

11. CLASSIFICATION OF FORECASTING METHODS
 Judgmental (subjective method)
 Timer series (based on past data arranged in
a chronological order)
 Econometric (cause and effect relationship)

12. JUDGMENTAL TECHNIQUES
 Opinion survey method
 Executive opinion method
 Customer and distributor surveys
 Marketing trials
 Market research
 Delphi technique

13. TIME SERIES ANALYSIS
 Based on the past data arranged in
chronological order as a dependent variable and
time as an independent variable
 For e.g. sales of TV sets for last four years are:
 Time series method does not study the factors
that influence the demand, in this method all the
factors that shape the demand are grouped into
one factor-time and demand is expressed as a
series of data with respect to time.
YEAR 1993-94 1994-95 1995-96 1996-97
NO. OF TV SETS 20 30 40 58

14. FOUR COMPONENTS OF TIME SERIES ANALYSIS
 1. Trend(T)  2. Cyclical
fluctuation(C)
 3. Seasonal
variation (S)
 1. Irregular
variations(R)

15.  Most commonly used expression for a time
series forecast is:
Y=TCSR
Where, Y= Forecasted value
T= Secular trend
C= Cyclic variations
S= Seasonal variations
R= Irregular fluctuations
FOUR COMPONENTS OF TIME SERIES ANALYSIS

16. MOVING AVERAGES
 The sales results of multiple prior periods are
averaged to predict a future period
 Called ‘moving’ because it is
continually recomputed as
new data becomes available,
it progresses by dropping the
earliest value and adding the
latest value.

17. EXPONENTIAL SMOOTHING
 Similar to moving average method
 Used for short run forecasts
 Instead of weighing all observations equally in
generating the forecast, exponential smoothing
weighs the most recent observations heaviest
Next year’s sale=a(this year’s sale) + (1-a)(this
year’s forecast)
a is smoothing constant taken in scale 0-1

18. MARKET TEST METHOD
 Used for developing one time forecasts
particularly relating to new products
 A market test provides data about
consumers' actual purchases and
responsiveness to the various elements of
the marketing mix.
 On the basis of the response received to a
sample market test, product sales forecast is
prepared.

19. REGRESSION ANALYSIS
 Identifies a statistical relationship between
sales(dependent variable) and one or more
influencing factors, which are termed the
independent variables.
 When just one independent variable is
considered (eg. population growth), it is called a
linear regression, and the results can be shown
as a line graph predicting future values of sales
based on changes in the independent variable.
 When more than one independent variable is
considered, it is called a multiple regression

20. BENEFITS OF SALES FORECASTING
 Better control of Inventory
 Staffing
 Customer Information
 Use for Sales People
 Obtaining Financing

21. LIMITATIONS OF SALES FORECASTING
 Part hard fact, part guesswork
 Forecast may be wrong
 Times may change