Saint Marys University TOMS Manufacturing Operations Management Question Question 1 TOMS Manufacturing Tom Street is the CEO of TOMS Manufacturing, a comp

Saint Marys University TOMS Manufacturing Operations Management Question Question 1 TOMS Manufacturing Tom Street is the CEO of TOMS Manufacturing, a company that makes various components for its wireless technology division.In all, the company makes about 200 different items.The two markets (the major manufacturer and 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.Instead, the operations manager decides which items to produce, and the batch size, based partly on orders, and the amounts in inventory.The products that have the fewest amounts in inventory get the highest priority. Demand is uneven, and the company has experienced being overstocked on some items and out of stock on others.Being understocked has occasionally created tensions with the manger of retail outlets.Another problem is that prices of raw materials have been creeping up, although the operations manager thinks that this might be a temporary condition. Because of competitive pressures and falling profits, Tom has asked the Operations Manager 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.These products are important for several reasons.First, they account for a disproportionately large share of the company’s profits.Second, the manager believes that one of these products will become increasingly important to future growth plans; and third, the other product has experienced periodic out-of-stock instances.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:( I PUT THE TABLE AND THE RIGHT VISION OF THE QUESTION IN THE UPLOAD FILE SECTION. ) Questions: What are some of the potential benefits of a more formalized approach to forecasting?I’m looking for at least 5 benefits. Prepare a weekly forecast for weeks 15 through 18 for each of Product 1 and Product 2.You must plot the data for the first 14 weeks for both products and then plot it again for all 18 weeks after you have prepared your forecast and include the plotted graphs in your answer.In explaining the technique that you decided to use for each product, look at your plotted data.Do the forecasted weeks make sense visually from what you observed in the first 14 weeks?If not, you likely did not choose the correct technique.And remember one real world hint – the formulas are very useful to help guide you with forecasting but as a manager you have the authority to adjust the forecasted numbers if you think it makes sense to do so.If you do adjust your numbers you must still tell me the technique you used but why you chose to adjust some of your forecasted numbers. Question 1
TOMS Manufacturing
Tom Street is the CEO of TOMS Manufacturing, a company that makes various
components for its wireless technology division. In all, the company makes about 200
different items. The two markets (the major manufacturer and 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. Instead, the
operations manager decides which items to produce, and the batch size, based partly on
orders, and the amounts in inventory. The products that have the fewest amounts in
inventory get the highest priority. Demand is uneven, and the company has experienced
being overstocked on some items and out of stock on others. Being understocked has
occasionally created tensions with the manger of retail outlets. Another problem is that
prices of raw materials have been creeping up, although the operations manager thinks
that this might be a temporary condition.
Because of competitive pressures and falling profits, Tom has asked the
Operations Manager 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. These products are important for several reasons. First, they account for a
disproportionately large share of the company’s profits. Second, the manager believes
that one of these products will become increasingly important to future growth plans; and
third, the other product has experienced periodic out-of-stock instances. 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:
Product
Product
Product
Product
Week
1
2
Week
1
2
1
50
40
8
76
47
2
54
38
9
79
42
3
57
41
10
82
43
4
60
46
11
85
42
5
64
42
12
87
49
6
67
41
13
92
43
7
90*
41
14
96
44
* unusual order due to overstocking at customer’s warehouse
Questions:
1. What are some of the potential benefits of a more formalized approach to
forecasting? I’m looking for at least 5 benefits.
2. Prepare a weekly forecast for weeks 15 through 18 for each of Product 1 and
Product 2. You must plot the data for the first 14 weeks for both products and
then plot it again for all 18 weeks after you have prepared your forecast and
include the plotted graphs in your answer. In explaining the technique that you
decided to use for each product, look at your plotted data. Do the forecasted
weeks make sense visually from what you observed in the first 14 weeks? If not,
you likely did not choose the correct technique. And remember one real world
hint – the formulas are very useful to help guide you with forecasting but as a
manager you have the authority to adjust the forecasted numbers if you think it
makes sense to do so. If you do adjust your numbers you must still tell me the
technique you used but why you chose to adjust some of your forecasted numbers.
FORMULAS 3308
Value = Perceived Benefits
Price (cost) to the customer
Break-even Formula for Outsourcing: Q = FC
VC2 – VC1
Where:
VC1 = variable cost per unit if produced in house
VC2 = variable cost per unit if outsourced
Productivity = Output
Input
Productivity = current period productivity-previous period productivity
Growth
previous period productivity
Value of a Loyal Customer: VLC = (P)(RF)(CM)(BLC)
Where:
P = the revenue per unit
CM = contribution margin to profit and overhead expressed as a fraction (eg .45; .50, etc)
RF = repurchase frequency = number of purchases per year (eg if they buy one every 4 years it is
represented as ¼ = .25; but four times a year would be 4)
BLC = buyer’s life cycle, computed as 1 divided by the defection rate, expressed as a fraction (eg 1 / 0.2 =
5 years).
Moving Average = ∑ Demand in selected time series
n
where:
n = number of periods (data points) in the moving average
Single Exponential Smoothing:
Ft = α(previous period’s actual) + (1 – α)(previous period’s new forecast)
Linear Trend Equation Line: Coefficients of the line a, and b can be computed from historical data
using the following two equations for b and a
Step 1. Fill in your template and sum the columns: Year Time Period(x) Demand (y)
x²
xy
Step 2. Then calculate:
b = n∑xy – ∑x∑y
a = ∑y – b∑x
n∑x² – (∑x)²
n
where: n = total number of periods
y = value of the time series
Then apply formula to a and b: Yt = a + bt
Mean Square Error:
Σ(At – Ft)²
T
Mean Absolute Percentage Error:
Σ[(At – Ft) / At] x 100
T
Tracking Signal:
Σ(At – Ft)
MAD
Mean Absolute Deviation:
At – Ft
T
Annual Holding Cost not using EOQ:
Q x Ch
2
Where: Q = order quantity in units
Ch = holding costs per unit per year
Annual Ordering or Setup Cost not using EOQ:
D x Co
Q
Where: D = demand in units per year
Co = cost or ordering per order
Q = number of units in each order
Economic Order Quantity:
EOQ = square root of 2(D)(Co)
Ch
Annual Holding Cost using EOQ:
EOQ x Ch
2
Annual Ordering Cost using EOQ:
D
x Co
EOQ
TC = Annual Carrying Cost + Annual Ordering Cost
ROP (under constant demand and lead time) = d(LT)
Annual Stockout costs:
Template to use: Safety Stock
Holding Cost
Where d = demand rate; LT = lead time
Stockout Cost
Total Cost
Where: stockout costs are = (the sum of the units short)(the historical probability)(the stockout cost per
unit) (the numbers of orders per year)
Reorder Point for Service Level Model:
r = UL + ZσL
Where:
UL = average demand during the lead time
Z = the number of standard deviations necessary to achieve the acceptable
service level
σL = standard deviation of demand during the lead time
Slack = LS – ES; or LF – EF
Expected Activity Time: t = (a + 4m + b)/6 a=optimistic m = most likely b = pessimistic
Variance of Activity completion time: Variance = (b-a) ² /36 where b = pessimistic time and a =
optimistic time
Project variance (σ²p) = add up the variances of all the critical path activities
Project Standard Deviation (σp) = square root of the project variance
Probability of completing project on or before deadline: Z = (due date – expected date of
completion)/σp. From this calculation, find the probability in the normal distribution chart.
Computing probability for any completion date: Find the percentage you want to test on the normal
distribution chart (Z). Then apply the formula: Due date = Expected date of completion + (Z x σp)
Two ways to compute resource utilization: (you have to know which one to use!). Also use these
formulas for capacity calculations such as numbers required (eg equipment, servers, etc) and target
utilization. For target utilization you need to set up your formula as a quadratic equation and solve
for “X” based on what you are being asked to solve in the problem.
Utilization (U) = Demand Rate / [(Service Rate x Number of Servers)]
Utilization (U) = Resources Used / Resources Available
Average Safety Capacity (%) = 100% – Average resource utilization (%)
Break-Even = Fixed Costs / (price per unit – variable cost per unit)
Multi-Product Break Even:
Template to use is:
Item
Price
V (V/P) 1-(V/P) Annual Forecasted Sales %of Sales Weighted Contribution
% of Sales Calculation = annual sales for individual items divided by total annual forecasted sales for all
items
Weighted Contribution Calculation = 1-(V/P) x % of Sales for each individual product
Break-Even in Dollars = Fixed Costs / Total Weighted Contribution of all products
Daily Sales Required to break-even = Break-Even in dollars / # of operating days a year
Daily Sales required to break-even for individual Products =
% of sales for individual item x daily total dollar break-even
Price of individual item
Crash cost per unit of time = crash cost – normal cost
normal time – crash time
System Reliability of an n-component series system = Rs = (pı)(p2)(p3) …(pn)
System Reliability of an n-component parallel system = Rp = 1 – (1- lowest reliability) (1- lowest
reliability).

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