- M&L Manufacturing produces printer and copier components for a major manufacturer as well as for replacement parts distribution. They produce about 20 different items. - Due to competitive pressures and falling profits, the manager wants to introduce formal forecasting to improve production planning and inventory management for two products. - Historical demand data for the past 14 weeks is provided for the two products. Forecasts for the next 4 weeks will be generated using linear regression for Product 1 and an intuitive average-based approach for Product 2.

1. M&L Manufacturing
GSM 5113-Operations
Management
Dr Affendy Abu Hassim

2. M&L Manufacturing
M&L Manufacturing makes various components for printers and
copiers. In addition to supplying these items to a major
manufacturer, the company distributes these and similar items to
office supply stores and computer stores as replacement parts for
printers and desktop copiers. In all, the company makes about 20
different items. The two markets (the major manufacturer and the
replacement market) require somewhat different handling.
For example, replacement products must be packaged
individually whereas products are shipped in bulk to the major
manufacturer.
The company does not use forecasts for production planning.

3. M&L Manufacturing
Because of competitive pressures and falling
profits, the manager has decided to undertake a
number of changes. One change is to introduce
more formal forecasting procedures in order to
improve production planning and inventory
management.
With that in mind, the manager wants to begin
forecasting for two products.

4. M&L Manufacturing
The manager has compiled data on product demand for the
two products from order records for the previous 14 weeks.
These are shown in the following table.

5. Questions
1. What are some of the potential benefits of a more formalized
approach to forecasting?
2. Prepare a weekly forecast for the next four weeks for each
product.
Briefly explain why you chose the methods you used. ( Hint:
For product 2, a simple approach, possibly some sort of naive/
intuitive approach, would be preferable to a technical approach
in view of the manager’s disdain of more technical methods.)

6. ANSWER #1.
The potential benefit of using a formalized
approach to forecasting is that it will be easier to
utilize the computer and easier to quantify the
information.
A less formalized approach is more likely to
utilize personal intuition. For small forecasting
problems, intuition may involve personal bias, which
may be reflected in the forecast.
As the forecasting problem gets larger, it will be
impossible to rely solely on a less formalized
approach because a person’s intuition will be unable
to process the large quantity of information.

7. ANSWER #2.Product 1
Product 1
Plotting the data for Product 1 reveals a linear pattern with the
exception of demand in week 7. Demand in week 7 is unusually
high and does not fit the linear trend pattern of the remaining
data. Thus, the demand for the 7th week is considered an
outlier. There are different ways of dealing with outliers. A
simple and intuitive way is to replace the demand for the week
in question with the average demand from the previous week
and the next week in the time-series. Therefore in this case, the
demand of 90 in week 7 will be replaced with 71.5 = [(67 + 76)/2].

8. ANSWER #2.Product 1
t Y t*Y t2
1 50 50.00 1
2 54 108.00 4
3 57 171.00 9
4 60 240.00 16
5 64 320.00 25
6 67 402.00 36
7 71.5 500.50 49
8 76 608.00 64
9 79 711.00 81
10 82 820.00 100
11 85 935.00 121
12 87 1,044.00 144
13 92 1,196.00 169
14 96 1,344.00 196
105 1,020.5 8,449.50 1,015
3.50
Round b & a to two decimals:
= -
14(8,449.50) 105(1,020.5)
b n tY t Y
= å -å å
n t t
=
2 ( )2 14(1,015) -
(105)
2 å - å
46.64
a Y b t
= å - å = 1,020.5 -3.50(105) =
14
n
Y = 46.64 + 3.50t
The next four forecasts (t = 15, 16, 17, 18) are:
Period Forecast (T = 46.64 + 3.50t)
15 T = 46.64 + 3.50(15) = 99.14
16 T = 46.64 + 3.50(16) = 102.64
17 T = 46.64 + 3.50(17) = 106.14
18 T = 46.64 + 3.50(18) = 109.64

9. ANSWER #2 Product 2.
Product 2
Plotting the data for Product 2 yields a more complex pattern:
There is a spike once every four weeks; the values between the spikes are
fairly close to each other. In addition, the data appear to be increasing at
the rate of about one unit per week. An intuitive approach would be to use
the average of the three nonspike periods plus 1.0 to predict the next three
nonspike periods. Doing so for the data up to period 15 yields a very small
average forecast error (MAD = 0.54). Given the fact that we have only two
data points following the last spike, a reasonable forecast might be to use
the last three period average plus 1.0 (i.e., 43.33 to predict orders for
period 15, and use the average of the values for periods 13 and 14 plus 1.0
(i.e., 43.5 + 1.0 = 44.5) as a forecast for periods 17 and 18.

10. ANSWER #2.Product 2
The values of the spikes also seem to be increasing. The initial
increase was 1.0 and the second increase was 2.0. A naive
forecast here would be 49 + 2 = 51. However, the average
increase was 1.5. Using that would yield a value of 50.50. One
might even be tempted to project an increase of 3.0, although
either of the others seems more justifiable. Still, the fact that
there is a limited amount of data makes this forecast more risky.
Hence, the forecasts are:
Period Forecast
15 43.33
16 50.50
17 44.50
18 44.50