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Part 3 : Acquisition & Production Support
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3 Demand Forecasting
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Seung Hyun Lee (Ph
...
, CPL)
IEMS Research Center,

E-mail : lkangsan@iems
...
kr

Demand Forecasting
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․ An estimate of future demand
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- 2 -

Demand Forecasting
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․ To anticipate and manage change
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․ To anticipate inventory and capacity demands and manage lead times
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․ To improve competitiveness and productivity through decreased
costs and improved delivery and responsiveness to customer
needs
...

[Other Resource]

Demand Forecasting System
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1
...

․ This includes defining the source of the historical data to be provided and
the periods over which the data will be collected
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Assign responsibility for the forecast to a person which performance will
be measured on the accuracy of actual sales to the forecast
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Setup forecast system parameters :
․ Forecast horizon
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․ Forecast period and frequency
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- 4 -

Demand Forecasting
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￭ Constructing Demand Forecasting System
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Select appropriate forecasting models and techniques
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Collect data for input to forecasting models and test models for forecast
accuracy
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Run the forecasting model and generating forecasts
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Record actual demand information against forecast
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Report

forecast

accuracy

and

determine

the

root

cause

for

variance

between forecast and actual data
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- 5 -

Demand Forecasting
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￭ Qualitative Techniques
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․ This information is intuitive and based on subjective judgment
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- 6 -

Demand Forecasting
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․

Time series analysis is based on the idea that data relating to past demand can
be used to predict future demand
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[Other Resource]

￭ Causal Forecasting
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Causal forecasting methods develop forecasts after
establishing and measuring an association between the dependent variable and
one or more independent variables
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[Other Resource]

Various Forecasting Methods
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․

Market Research
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․

Panel Consensus
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Panel
forecasts are developed through open meetings with free exchange of idea from
all levels of management and individuals
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[Other Resource]

Various Forecasting Methods
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․

Historical Analogy
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There are many ways to classify such analogies - for example,
complementary products, substitute or competitive products, and products as a
function of income
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The Delphi method conceals the identity of the individuals
participating in the forecasting
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Procedurally, a
moderate creates a questionnaire and distributes it to participants
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- 10 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Regression
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Simple regression involves one
independent variable and one dependent variable
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- 11 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Regression
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x i is the independent variable, and


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e i is the residual ; the error in the fit of the model
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[Other Resource]

Various Forecasting Methods
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․ An arithmetic average of a certain number n of the most recent observations
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The value
of n (the number of periods to use for the average) reflects responsiveness
versus stability in the same way that the choice of smoothing constant does in
exponential smoothing
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Demand

over

the

past

three

months

has

been

120,

135,

and

114 units
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Forecast for month 4 =

120 + 135 + 114
3

=

369
3

= 123

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Quantitative Forecasting Methods
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￭ Quantitative Methods : Moving Average
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[Other Resource]

Quantitative Techniques
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․

Whereas the simple moving average gives equal weight to each component of
moving average database, a weighted moving average allows any weights to be
placed

on each element, providing, of course, that the sum of all weights

equals 1
...
+w nA t - n

where w i = Weight to be given to the actual occurrence for the period t-n

n = Total number of periods in the forecast
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i= 1
- 15 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Exponential Smoothing
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The heaviest
weight is assigned to the most recent data
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Ft = α A

t-1

+

( 1 - α) F

where

Ft

t-1

= New forecast
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F

t-1

= Previous forecast
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(0 ≤ α ≤ 1)
- 16 -

Quantitative Forecasting Methods
...

￭ Quantitative Methods : Exponential Smoothing
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[Other Resource]

Quantitative Techniques
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- 18 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Trend Effects in Exponential Smoothing
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․ To correct the trend, smoothing constant delta ( δ ) can be used
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FIT t = F t + T t
F t = FIT

t - 1 + α( A t - 1 - FIT t - 1 )

T t = T t - 1 + δ ( F t - FIT t - 1 )
where T t = The exponential smoothed trend for period t
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- 19 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Trend Effects in Exponential Smoothing
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2, and a delta of 0
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If actual demand turned out to be 115 rather
than the forecast 100, calculated the forecast for the next period
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2(115 -110) = 111
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3(111-110) = 10
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0 + 10
...
3

- 20 -

Quantitative Forecasting Methods
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￭ Quantitative Methods : Box and Jenkins Methods
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- 21 -

Quantitative Forecasting Methods
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￭ Decomposition
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․

Decomposition of a time series means identifying and separating the time series
data into these components
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1
...

Forecasting including trend and seasonal = Trend + Seasonal
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Multiplicative Seasonal Variation
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- 22 -

Seasonality
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￭ Seasonal Index
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․ The form for the seasonality index :
Seasonal Index =

Period average demand
Average demand for all periods

- 23 -

Seasonality
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￭ Seasonal Index
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․ Calculating seasonal index
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Seasonal Index for Quarter 1 = 128/100 = 1
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Seasonal Index for Quarter 2 = 102/100 = 1
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Seasonal Index for Quarter 3 = 75/100 = 0
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Seasonal Index for Quarter 4 = 95/100 = 0
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[Other Resource]

Causal Relationship of Forecasting
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․ There are several types of forecasts that are based on external indicators, factors
that determine the demand of performance of a related items
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Housing starts
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Number of babies
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Hits on a Web site
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Healthier lifestyle
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․ Fitness products
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[Other Resource]

Tracking The Forecast
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․

To determine accuracy, we must measure actual demand and compare it to
what we forecast
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Tracking forecast is the process of
comparing actual demand with the forecast
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[Other Resource]

Tracking The Forecast
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․ Bias, Cumulative Sum of Error
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Bias =

∑( A t - F t )
n

․ Mean Absolute Deviation (MAD), Standard Deviation
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MAD =

∑ ∣A t - F t∣
n

or

MAD t = MAD t - 1 + α∣A t - F t∣

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Forecasting Management
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￭ Example
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Bias = Cumulative Sum of Error / Number of periods = 200/10 = 20
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Standard Deviation (SD) = 1
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[Other Resource]

Tracking The Forecast
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․ The ratio of the cumulative algebraic sum of the deviation between the forecasts
and the actual values to the mean absolute deviation
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Tracking Signal =

Cumulative Sum of Error
MAD

․ Tracking Signal vs
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1
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Quantitative factors
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Qualitative factors
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Both quantitative and qualitative factors
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Neither qualitative nor quantitative factors
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Which of the following statements is TRUE about the integration of planning systems
and the level of forecast accuracy ?
A
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B
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C
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D
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- 30 -

Performance Check
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Which of the following is MOST directly affected by forecast inaccuracy ?
A
...


B
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C
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D
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4
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Expert opinion
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Historical data
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Exponential smoothing
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Moving average
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Seasonality is demand that shows which of the following patterns ?
A
...

B
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C
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D
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- 31 -

Performance Check
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Which of the following depend on external conditions affecting on demand ?
A
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B
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C
...


D
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7
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․ Alpha factor - 0
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․ Old Forecast - 562
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1
A
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B
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C
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D
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- 32 -

Performance Check
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Which of the following is the BEST statement about the general principles of
forecasting ?
A
...

B
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C
...

D
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9
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To compare the actual sales with the forecast
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To improve our forecasting methods
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To utilize actual sales data
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To satisfy marketing's need to know
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10
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If we wish to forecast demand, past sales must be used for the forecast
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Forecasts made in dollars for total sales should be used by manufacturing
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Forecasts should be made for individual items in a group
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The circumstances relating to demand data should be recorded
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Solutions

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