Forecasting Methods and Techniques for Demand Planning

 
Chapter 4
 
Naive Approach
Naive Approach
 
Assumes demand in next period is the
Assumes demand in next period is the
same as demand in most recent period
same as demand in most recent period
e.g., If May sales were 48, then June sales
e.g., If May sales were 48, then June sales
will be 48
will be 48
Sometimes cost effective and efficient
Sometimes cost effective and efficient
 
Used if little or no trend
Used often for smoothing
Provides overall impression of data
over time
Moving Average Method
Moving Average Method
 
 
 
 
 
(12 + 13 + 16)/3 = 13 
(12 + 13 + 16)/3 = 13 
2
2
/
/
3
3
 
 
 
 
(13 + 16 + 19)/3 = 16
(13 + 16 + 19)/3 = 16
 
 
 
 
(16 + 19 + 23)/3 = 19 
(16 + 19 + 23)/3 = 19 
1
1
/
/
3
3
Moving Average Example
Moving Average Example
Graph of Moving Average
Graph of Moving Average
 
Used when trend is present
Older data usually less important
Weights based on experience and intuition
Weighted Moving Average
Weighted Moving Average
 
 
 
 
 
[(3 x 16) + (2 x 13) + (12)]/6 = 14
[(3 x 16) + (2 x 13) + (12)]/6 = 14
1
1
/
/
3
3
 
 
 
 
[(3 x 19) + (2 x 16) + (13)]/6 = 17
[(3 x 19) + (2 x 16) + (13)]/6 = 17
 
 
 
 
[(3 x 23) + (2 x 19) + (16)]/6 = 20
[(3 x 23) + (2 x 19) + (16)]/6 = 20
1
1
/
/
2
2
Weighted Moving Average
Weighted Moving Average
 
Increasing n smooths the forecast but makes it less sensitive
to changes
Do not forecast trends well
Require extensive historical data
Potential Problems With
Potential Problems With
 Moving Average
 Moving Average
Moving Average And
Moving Average And
Weighted Moving Average
Weighted Moving Average
 
Figure 4.2
Figure 4.2
Exercise  4.1
Exercise  4.1
 
The following gives the number of pints of
Type A blood used at Woodlawn Hospital in
the past six weeks.
 
 
 
 
 
a)
Forecast the demand for the week of
October 12 using a three-week moving average.
 
b) Use a three week weighted moving average, with weights of .1, .3,
and .6, using .6 for the most recent week. Forecast demand for the
week of October 12.
 
Exercise  4.1
Exercise  4.1
 
a)
Forecast the demand for the week of October 12 using a three-week
moving average.
Exercise  4.1
Exercise  4.1
 
b) Use a three week weighted moving average, with weights of .1, .3,
and .6, using .6 for the most recent week. Forecast demand for the
week of October 12.
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Explore different forecasting methods such as Naive Approach, Moving Average, Weighted Moving Average, and their applications in demand forecasting. Understand the concepts, advantages, and limitations of each method through examples and visual representations.


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  1. Chapter 4

  2. Naive Approach Assumes demand in next period is the same as demand in most recent period e.g., If May sales were 48, then June sales will be 48 Sometimes cost effective and efficient

  3. Moving Average Method Used if little or no trend Used often for smoothing Provides overall impression of data over time demand in previous n periods n Moving average =

  4. Moving Average Example Actual Shed Sales 3-Month Moving Average Month January February March April May June July 10 12 13 16 19 23 26 10 12 13 (10 + 12 + 13)/3 = 11 2/3 (12 + 13 + 16)/3 = 13 2/3 (13 + 16 + 19)/3 = 16 (16 + 19 + 23)/3 = 19 1/3

  5. Graph of Moving Average Moving Average Forecast 30 28 26 24 22 20 18 16 14 12 10 Actual Sales Shed Sales | | | | | | | | | | | | J F M A M J J A S O N D

  6. Weighted Moving Average Used when trend is present Older data usually less important Weights based on experience and intuition (weight for period n) x (demand in period n) Weighted moving average = weights

  7. Weights Applied Period Weighted Moving Average 2 Two months ago 1 Three months ago 6 Sum of weights 3 Last month Actual Shed Sales 3-Month Weighted Moving Average Month January February March April May June July 10 12 13 10 12 13 16 19 23 26 [(3 x 13) + (2 x 12) + (10)]/6 = 121/6 [(3 x 16) + (2 x 13) + (12)]/6 = 141/3 [(3 x 19) + (2 x 16) + (13)]/6 = 17 [(3 x 23) + (2 x 19) + (16)]/6 = 201/2

  8. Potential Problems With Moving Average Increasing n smooths the forecast but makes it less sensitive to changes Do not forecast trends well Require extensive historical data

  9. Moving Average And Weighted Moving Average Weighted moving average 30 25 Sales demand Actual sales 20 15 Moving average 10 5 | | F | M | A M | | J | J | A | S | O | N | D J Figure 4.2

  10. Exercise 4.1 Week of Pints Used The following gives the number of pints of Type A blood used at Woodlawn Hospital in the past six weeks. August 31 360 September 7 389 September 14 410 September 21 381 September 28 368 October 5 374 a) Forecast the demand for the week of October 12 using a three-week moving average. b) Use a three week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12.

  11. Exercise 4.1 a) Forecast the demand for the week of October 12 using a three-week moving average. 374 + 368 + 381 3 =374.33 pints

  12. Exercise 4.1 b) Use a three week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12.

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