Demand forecasting involves estimating future demand for a product or service. It can use both qualitative methods like expert opinions and quantitative methods like analyzing historical sales data. There are various forecasting techniques for different time horizons, from short-term methods like surveys to long-term statistical methods like time series analysis and regression. Common statistical forecasting methods include trend projection using techniques like moving averages, as well as causal models like regression and simultaneous equations.
3. Demand Forecasting
Demand forecasting
is the activity of
estimating the
quantity of a product
or service that
consumers will
purchase. It involves
techniques, such as guesses, and quantitative methods,
such as the use of historical sales data.
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4. All good forecasts are built on one of
the three information bases:
What people say?
What people do?
What people have done?
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5. Forecasting
Q. Predict the next number in the pattern:
a) 3.7, 3.7, 3.7, 3.7, 3.7,
b) 2.5, 4.5, 6.5, 8.5, 10.5,
3.7
12.5
c) 5.0, 7.5, 6.0, 4.5, 7.0, 9.5, 8.0, 6.5,
9.0
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7. 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
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9. Methods of Demand Forecasting
Two approaches –
1) Expert’s opinion or by
conducting interviews with
consumers. suitable for
short-term forecasting.
2) Use past experience using
statistical technique. Suitable for long-term forecasting
There is no easy method for a manager to predict the future.
Economists and statisticians have developed several methods.
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11. Expert Opinion Method
Also known as Delphi Method.
Experts are requested to give their ‘opinion’ or ‘feel’
about the product.
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12. Sales Force Opinion Survey Method
Also known as collective
opinion method.
Instead of consumers,
the opinion of the
salesmen is considered.
It is easy and cheap.
Useful in forecasting sales
of new product.
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13. Consumers Survey Method
The burden of forecasting
is shifted to the buyer.
Direct method of estimating
the demand in short run.
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14. Complete Enumeration Survey
Door-to-door survey for forecast period.
Limitation is that it requires lots of resources,
manpower and time.
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15. Sample Survey
Some representative
households are selected
on random basis as
sample and their opinion
is taken.
This sample truly
represents the
population.
This method is less
costly.
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16. End Use Survey Method
The demand of the final product is the end
user demand of the intermediate product
used in the production of this final product .
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17. Statistical Method
Viewing the problem with an
external point of view.
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19. Barometric Techniques
It is a instrument
measuring changes.
“the future can be
predicted from certain
happenings in present”
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.
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23. Trend
Projection
Method
Graphical
Method
Semi-Average
method
Moving
Average
Least Square
Method
Straight Line
Trend
Parabolic
Trend
Exponential
Trend
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24. Graphical Method
Demand in next period is the same as demand
in most recent period
May sales = 48 →
Usually not good
June forecast = 48
6
5
4
3
2
1
0
Category 1 Category 2 Category 3 Category 4
Series 1 Series 2 Series 3
25. Straight Line Method
It is a mathematical method of determining trend.
The straight line obtained by this method is called
line of best fit.
It is difficult to select the type of trend to be fitted.
It is a time consuming method.
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26. Simple Moving Average
Assumes an average is a good
estimator of future behavior.
–Used if little or no trend
–Used for smoothing
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27. Q. Suppose you’re manager in Amazon’s electronics department. You want to
forecast iPods sales for months 4-6 using a 3-period moving average.
Month Sales (000) Moving Average
1 4 NA
2 6 NA
3 5 NA
4 3 (4+6+5)/3=5
5 7 4.667
6 5
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28. Semi-Average Method
The given data is divided into 2 groups preferably with same no. of yr.
It is simple to understand then the other models such as moving,
method of least square.
It is an objective method. Everyone will get the same answer by this
Method.
It always assumes the straight line relationship the plotted points
regardless of the fact.
Since it is based on the arithmetic mean, limitations of arithmetic
mean shall automatically apply.
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29. Exponential Smoothing
It is the most popular forecasting method.
It is very simple in application and in addition,
the past data required is limited to just the
last period’s actual demand and its forecast.
Ft+1 = Ft + a(At - Ft)
Ft+1 = Forecast value for time t+1
At = Actual value at time t
a = Smoothing constant
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