Sales Forecasting
Sales Forecasting
Sales Forecasting
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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
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Sales Forecasting Methods
Qualitative Quantitative
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Executive opinion method
Most widely used
Method of combining and averaging views of several
executives regarding a specific decision or forecast.
Leads to a quicker (and often more reliable) result
without use of elaborate data manipulation and
statistical techniques.
Delphi Method
Process includes a coordinator getting forecasts
separately from experts, summarizing the forecasts
giving the summary report to experts who are asked
to make another prediction; the process is repeated
till some consensus is reached 6
Sales force composite method
Also known as “Grassroots Approach”
Individual salespersons forecast sales for their
territories
Individual forecasts are combined & modified by the
sales manager to form the company sales forecast.
Best used when a highly trained & specialized sales
force is used.
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Survey of Buyer’s intentions
Process includes asking customers about their
intentions to buy the company’s product and
services
Questionnaire may contain other relevant questions
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Time Series Analysis
Make forecasts based purely on historical patterns in
the data. It has four components
The Trend component-Gradual upward or
downward
movement over time.
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The Cyclical Component
Sales are often effected by swings in general
economic activity as consumers have more or less
disposable income available
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The Seasonal Component
It is a distinguished pattern to sales caused by
things such as the weather, holidays, local customs
and general consumer behaviour.
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The Erratic events-Random Variations in data
caused by change and unusual situations
Time series analysis are accurate for short term and
medium term forecasts and more so when demand
is stable or follows the past behavior.
Some of the popular techniques of time series
analysis are:
moving averages,
exponential smoothing
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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.
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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
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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.
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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
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Benefits of Sales Forecasting
Better control of Inventory
Staffing
Customer Information
Use for Sales People
Obtaining Financing
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Limitations of Sales Forecasting
Part hard fact, part guesswork
Forecast may be wrong
Times may change
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