2. "Everything you have in your life, you have
attracted to yourself because of the way
you think, because of the person that you
are. You can change your life because you
can change the way you think.”
-Brian Tracy
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3. What is Sales forecasting..?
Def: The prediction, projection or estimation of
expected sales over a specified future time period.
Sales forecasting for an established business is easier than
sales forecasting for a new business
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4. Why…???
To raise necessary cash for investment and operation.
To establish capacity and output level.
To acquire and stock and amount of supplies.
To hire the required number of people.
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5. Level of Sales Forecasting
Product-byproduct
Sales
forecasting
Seasonal
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Geographical
6. Types Of Sales forecasting
There are two major types of forecasting, which can be broadly
described as macro and micro:
Macro forecasting is concerned with forecasting markets in total.
Micro forecasting is concerned with detailed unit sales
forecasts.
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7. Which type of forecasting to use
depends on several factors:
The degree of accuracy required..
The availability of data and information..
The time horizon that the sales forecast is
intended to cover..
The position of the products in its life cycle.
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8. Steps in the Forecasting Process
“The forecast”
Step 6 Monitor the forecast
Step 5 Prepare the forecast
Step 4 Gather and analyze data
Step 3 Select a forecasting technique
Step 2 Establish a time horizon
Step 1 Determine purpose of forecast
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10. Sales Forecasting Techniques
QAULITATIVE TECHNIQUES
Consumer/User survey method
Jury of executive opinion
Sales force composite
Delphi method
Product testing and test marketing
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11. Consumer/User survey Method
(Market Research)
Involves asking consumer about there likely purchase for
the forecasted period
Well defined buyers
Limited in number
Advantage: Simple and Easy
Disadvantage: buyers might change their opinions
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12. Jury of Executive opinion
Specialist & experts are consulted who have knowledge of the
industry being examined
Committee members came together and discuss forecasts and
agree one of the estimates or come up with a new estimate for
whole company.
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13. Cont.
Advantage : Developing a general, rather than product by
product forecast
Disadvantage: Difficulty in allocating the forecast among
individual product
Cause the statistics are not collected from the market
Allocation can be Arbitrary
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14. Sales force composite
Each sales-person makes a product-by-product forecast for their
particular sales territory.
Advantage: simple
Disadvantage:
1- Over estimate
More than sales potential
Over production (extra cost)
Additional cost for keeping stock.
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15. CONT..
Disadvantage:
2- Under estimate:
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Less than sales potential
Demand do not match
Shift to competitors and decrease in sales and
decrease in profitability
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16. Delphi Method
• Very similar to jury of executives method but this time members
are both inside and outside the company
A questionnaire is given to each member of the team which asks
question usually of behavior nature
Main objective is to translate opinion into some from of forecast
•
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This will continue until all members agree on same forecast. (it is suitable for
long-term forecasts).
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18. Product testing and test marketing
This research method is heavily preferred
when company offers a new product to the
market (innovation).
Advantage: provide real feedbacks about customers
reactions and make estimates upon that.
Disadvantage: Rivals might get aware of it.
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20. TIME SERIES ANALYSIS
The time series analysis method predicts the future sales by
analyzing the historical relationship between sales and time.
While breaking time series into components, the three most
common patterns observed are
1. Trend form
2. Level form &
3. Seasonal form
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21. CONT..
• Seasonality: A seasonal pattern(e.g., quarter of the year, month of the
year, week of the month, day of the week) exists when demand is
influenced by seasonal factors.
• Trend: During the growth and decline stages of the product life cycle, a
consistent trend pattern in terms of demand growth or demand decline
can be observed.
• Level : It is difficult to capture short term patterns that are not
repetitive in nature. In short run, sometimes there is a swing, which
could be in either direction, upward or downward, and it usually has
momentum that lasts for a few periods
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22. CASUAL TECHNIQUE
Causal forecasting model show the cause for demand and its
relation to other variables
Examples: Soft drink can be related to the average
summer temperature.
Rainfall can give us an estimate of crop and
in turn an estimate of the demand for consumer durables
in the rural areas.
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23. FORECASTING ERROR
Flaw in data.
Unpredictable economic or socio-political environment.
Non-realistic & accurate assumption
Technical and technological changes
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