Sales Forecasting
Sales forecasting is the process of a company predicting what its future sales will be. This forecast is done for a particular period of time in the near future, usually the next fiscal year. Accurate sales forecasting enables a company to make informed business decisions. Sales forecasting is easier for established companies that have been operating for a few years than for newer companies. Established companies have years of sales records and can base their forecasts on that past sales data. Newly founded companies have to base their forecasts on less verified information, such as market research and competition analysis to forecast their future business.
Why is Sales Forecasting important?
Sales Forecasting gives insight on whether a company should expand, information about cash flow, and the ability to effectively manage its resources. Without forecasting, a company would be unsure of what inventory level to maintain, unsure on how it should allocate resources across the company, and it would have a hard time predicting future success. Forecasting sales is a crucial business practice, because in addition to helping a company allocate its internal resources effectively, having this data is important for acquiring investment capital. Often, investors want to know what a company’s future expected sales are before making an investment.
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)
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