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Chapter Two Competitiveness, Strategy, and Productivity 65
13. Name 10 ways that banks compete for customers.
14. Explain the rationale of an operations strategy that seeks to increase the opportunity for use of tech-nology by reducing variability in processing requirements.
15. Identify two companies that have time-based strategies, and two that have quality-based strategies.
1. Who needs to be involved in formulating organizational strategy?
2. Name some of the competitive trade-offs that might arise in a fast-food restaurant.
3. How can technology improve
a. Competitiveness?
b. Productivity?
TAKING STOCK
1. In the past there was concern about a “productivity paradox” related to IT services. More recently,
there have been few references to this phenomenon. Using the Internet, explain the term “produc-tivity paradox.” Why do you think that the discussion of that topic has faded?
2. A U.S. company has two manufacturing plants, one in the United States and one in another country.
Both produce the same item, each for sale in their respective countries. However, their productivity
figures are quite different. The analyst thinks this is because the U.S. plant uses more automated
equipment for processing while the other plant uses a higher percentage of labor. Explain how that
factor can cause productivity figures to be misleading. Is there another way to compare the two
plants that would be more meaningful?
Operations Problems
3. While it is true that increases in efficiency generate productivity increases, it is possible to get
caught in an “efficiency improvement trap.” Explain what this means.
4. It is common knowledge that Sam’s boss Dom has been fudging the weekly productivity figures.
Several employees, including Sam, have spoken to him about this, but he continues to do it. Sam
has observed a drop in morale among his coworkers due to this. Sam is thinking about sending an
anonymous note to Dom’s boss. Would that be ethical? What would you do if you were Sam?
5. Give two examples of what would be considered unethical involving competition and the ethical
principles (see Chapter 1) that would be violated.
CRITICAL
THINKING
EXERCISES
1. A catering company prepared and served 300 meals at an anniversary celebration last week using
eight workers. The week before, six workers prepared and served 240 meals at a wedding reception.
a. For which event was the labor productivity higher? Explain.
b. What are some possible reasons for the productivity differences?
2. The manager of a crew that installs carpeting has tracked the crew’s output over the past several
weeks, obtaining these figures:
Operations Problems
Week Crew Size Yards Installed
14 96 23 72 34 92 42 50 53 69 62 52
Compute the labor productivity for each of the weeks. On the basis of your calculations, what can
you conclude about crew size and productivity?
3. Compute the multifactor productivity measure for each of the weeks shown for production of choc-olate bars. What do the productivity figures suggest? Assume 40-hour weeks and an hourly wage of
$12. Overhead is 1.5 times weekly labor cost. Material cost is $6 per pound.
Week Output (units) Workers Material (lbs)
1 30,000 6 450
2 33,600 7 470
3 32,200 7 460
4 35,400 8 480
4. A company that makes shopping carts for supermarkets and other stores recently purchased some
new equipment that reduces the labor content of the jobs needed to produce the shopping carts.
Prior to buying the new equipment, the company used five workers, who produced an average of
80 carts per hour. Workers receive $10 per hour, and machine cost was $40 per hour. With the new
PROBLEMS
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66 Chapter Two Competitiveness, Strategy, and Productivity
equipment, it was possible to transfer one of the workers to another department, and equipment cost
increased by $10 per hour while output increased by four carts per hour.
a. Compute labor productivity under each system. Use carts per worker per hour as the measure of
labor productivity.
b. Compute the multifactor productivity under each system. Use carts per dollar cost (labor plus
equipment) as the measure.
c. Comment on the changes in productivity according to the two measures, and on which one you
believe is the more pertinent for this situation.
5. An operation has a 10 percent scrap rate. As a result, 72 pieces per hour are produced. What is the
potential increase in labor productivity that could be achieved by eliminating the scrap?
6. A manager checked production records and found that a worker produced 160 units while working
40 hours. In the previous week, the same worker produced 138 units while working 36 hours. Did
the worker’s productivity increase, decrease, or remain the same? Explain.
7. The following table shows data on the average number of customers processed by several bank
service units each day. The hourly wage rate is $25, the overhead rate is 1.0 times labor cost, and
material cost is $5 per customer.
Unit Employees
Operations Problems
Customers
Processed/Day
A4 36 B5 40 C8 60 D3 20 a. Compute the labor productivity and the multifactor productivity for each unit. Use an eight-hour
day for multifactor productivity.
b. Suppose a new, more standardized procedure is to be introduced that will enable each employee
to process one additional customer per day. Compute the expected labor and multifactor produc-tivity rates for each unit.
8. A property title search firm is contemplating using online software to increase its search productiv-ity. Currently an average of 40 minutes is needed to do a title search. The researcher cost is $2 per
minute. Clients are charged a fee of $400. Company A’s software would reduce the average search
time by 10 minutes, at a cost of $3.50 per search. Company B’s software would reduce the average
search time by 12 minutes at a cost of $3.60 per search. Which option would have the highest pro-ductivity in terms of revenue per dollar of input?
9 . A company offers ID theft protection using leads obtained from client banks. Three employees work
40 hours a week on the leads, at a pay rate of $25 per hour per employee. Each employee identifies an aver-age of 3,000 potential leads a week from a list of 5,000. An average of 4 percent actually sign up for the
service, paying a one-time fee of $70. Material costs are $1,000 per week, and overhead costs are $9,000
per week. Calculate the multifactor productivity for this operation in fees generated per dollar of input.
Zachary Schiller
Operations Problems
The Rust Belt is back. So say bullish observers as U.S. exports
surge, long-moribund industries glow with newfound profits,
and unemployment dips to lows not seen in a decade. But in the
smokestack citadels, there’s disquiet. Too many machine-tool and
auto parts factories are silent; too many U.S. industries still can’t
hold their own.
What went wrong since the heyday of the 1960s? That’s the issue
Max Holland, a contributing editor of The Nation, takes up in his
nutsy-boltsy but fascinating study, When the Machine Stopped. *
The focus of the story is Burgmaster Corp., a Los Angeles–area
machine-tool maker founded in 1944 by Czechoslovakian immi-grant Fred Burg. Holland’s father worked there for 29 years, and
the author interviewed 22 former employees. His shop-floor view
of this small company is a refreshing change from academic trea-tises on why America can’t compete.
The discussions of spindles and numerical control can be tough
going. But Holland compensates by conveying the excitement and
innovation of the company’s early days and the disgust and cyni-cism accompanying its decline. Moreover, the fate of Burgmas-ter and its brethren is crucial to the U.S. industrial economy: Any
CASE An American Tragedy: How a Good Company Died
* Max Holland, When the Machine Stopped: A Contemporary Tale from
Industrial America (Boston: Harvard Business School Press, 1988). (continued)
68
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a. Predict orders for the following day for each of the products using an appropriate naive method.
Hint: Plot each data set.
b. What should the use of sales data instead of demand imply?
2 . National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period
were as follows:
Month
Sales
(000 units)
Feb. 19
Mar. 18
Apr. 15
May 20
Jun. 18
Jul. 22
Aug. 20
a. Plot the monthly data on a sheet of graph paper.
b. Forecast September sales volume using each of the following:
(1) A linear trend equation.
(2) A five-month moving average.
(3) Exponential smoothing with a smoothing constant equal to .20, assuming a March forecast of
19(000).
Operations Problems
(4) The naive approach.
(5) A weighted average using .60 for August, .30 for July, and .10 for June.
c. Which method seems least appropriate? Why? ( Hint: Refer to your plot from part a. )
d. What does use of the term sales rather than demand presume?
3 . A dry cleaner uses exponential smoothing to forecast equipment usage at its main plant. August
usage was forecasted to be 88 percent of capacity; actual usage was 89.6 percent of capacity. A
smoothing constant of .1 is used.
a. Prepare a forecast for September.
b. Assuming actual September usage of 92 percent, prepare a forecast for October usage.
4 . An electrical contractor’s records during the last five weeks indicate the number of job requests:
Week: 1 2 3 4 5
Requests: 20 22 18 21 22
Predict the number of requests for week 6 using each of these methods:
a. Naive.
b. A four-period moving average.
c. Exponential smoothing with .30. Use 20 for week 2 forecast.
5 . A cosmetics manufacturer’s marketing department has developed a linear trend equation that can be
used to predict annual sales of its popular Hand & Foot Cream.
Ftt 80 15
where
F
t
Annual sales (000 bottles)
Operations Problems
t 0 corresponds to 1990
a. Are annual sales increasing or decreasing? By how much?
b. Predict annual sales for the year 2006 using the equation.
6 . From the following graph, determine the equation of the linear trend line for time-share sales for
Glib Marketing, Inc.
124
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600
500
400
300
200
10 0
0
Year
Sales (units)
12345678910 0
Annual Sales, Glib Sales, Inc.
7 . Freight car loadings over a 12-year period at a busy port are as follows:
Week Number Week Number Week Number
1 220 7 350 13 460
2 245 8 360 14 475
3 280 9 400 15 500
4 275 10 380 16 510
5 300 11 420 17 525
6 310 12 450 18 541
a. Determine a linear trend line for expected freight car loadings.
b. Use the trend equation to predict expected loadings for weeks 20 and 21.
c. The manager intends to install new equipment when the volume exceeds 800 loadings per week.
Assuming the current trend continues, the loading volume will reach that level in approximately
what week?
8 . a. Obtain the linear trend equation for the following data on new checking accounts at Fair Savings
Bank and use it to predict expected new checking accounts for periods 16 through 19.
Period
Operations Problems
New
Accounts Period
New
Accounts Period
New
Accounts
1 200 6 232 11 281
2 214 7 248 12 275
3 211 8 250 13 280
4 228 9 253 14 288
5 235 10 267 15 310
b. Use trend-adjusted smoothing with .3 and .2 to smooth the new account data in part a.
What is the forecast for period 16?
9 . After plotting demand for four periods, an emergency room manager has concluded that a trend-adjusted exponential smoothing model is appropriate to predict future demand. The initial estimate of
trend is based on the net change of 30 for the three periods from 1 to 4, for an average of 10 units.
Use .5 and .4, and TAF of 250 for period 5. Obtain forecasts for periods 6 through 10.
Period Actual Period Actual
1 210 6 265
2 224 7 272
3 229 8 285
4 240 9 294
5 255 10
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10. A manager of a store that sells and installs spas wants to prepare a forecast for January, February,
and March of next year. Her forecasts are a combination of trend and seasonality. She uses the fol-lowing equation to estimate the trend component of monthly demand: Ft 70 5 t, where t 0 in
June of last year. Seasonal relatives are 1.10 for January, 1.02 for February, and .95 for March. What
demands should she predict?
11. The following equation summarizes the trend portion of quarterly sales of condominiums over a
long cycle. Sales also exhibit seasonal variations. Using the information given, prepare a forecast of
sales for each quarter of next year (not this year), and the first quarter of the year following that.
Ftt t 40 6 5 2
2
.
where
F
t
Unit sales
Operations Problems
t 0 at the first quarter of last year
Quarter Relative
1 1.1
2 1.0
3 .6 4 1.3
1 2 . A tourist center is open on weekends (Friday, Saturday, and Sunday). The owner-manager hopes
to improve scheduling of part-time employees by determining seasonal relatives for each of these
days. Data on recent traffic at the center have been tabulated and are shown in the following table:
WEEK
123456
Friday 149 154 152 150 159 163
Saturday 250 255 260 268 273 276
Sunday 166 162 171 173 176 183
a. Develop seasonal relatives for the shop using the centered moving average method.
b. Develop seasonal relatives for the shop using the SA method (see Example 8B).
c. Explain why the results of the two methods correlate the way they do.
13. The manager of a fashionable restaurant open Wednesday through Saturday says that the restaurant
does about 35 percent of its business on Friday night, 30 percent on Saturday night, and 20 percent
on Thursday night. What seasonal relatives would describe this situation?
14. Air travel on Mountain Airlines for the past 18 weeks was:
Week Passengers Week Passengers
1 405 10 440
2 410 11 446
3 420 12 451
4 415 13 455
5 412 14 464
6 420 15 466
7 424 16 474
8 433 17 476
9 438 18 482
Operations Problems
a. Explain why an averaging technique would not be appropriate for forecasting.
b. Use an appropriate technique to develop a forecast for the expected number of passengers for the
next three weeks.
1 5 . Obtain estimates of daily relatives for the number of customers at a restaurant for the evening meal,
given the following data.
a. Use the centered moving average method. ( Hint: Use a seven-day moving average.)
b. Use the SA method.
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Day
Number
Served Day
Number
Served
1 80 15 84
2 75 16 78
3 78 17 83
4 95 18 96
5 130 19 135
6 136 20 140
7 40 21 44
8 82 22 87
9 77 23 82
10 80 24 88
11 94 25 99
12 131 26 144
13 137 27 144
14 42 28 48
1 6 . A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales dur-ing the last 15 days were
Day: 1 2 3 4 5 6 7 8 9
Operations Problems
Number sold: 36 38 42 44 48 49 50 49 52
Day: 10 11 12 13 14 15
Number sold: 48 52 55 54 56 57
a. Which method would you suggest using to predict future sales—a linear trend equation or trend-adjusted exponential smoothing? Why?
b. If you learn that on some days the store ran out of the specific pain reliever, would that knowl-edge cause you any concern? Explain.
c. Assume that the data refer to demand rather than sales. Using trend-adjusted smoothing with an
initial forecast of 50 for week 8, an initial trend estimate of 2, and .3, develop forecasts
for days 9 through 16. What is the MSE for the eight forecasts for which there are actual data?
1 7 . New car sales for a dealer in Cook County, Illinois, for the past year are shown in the follow-ing table, along with monthly indexes (seasonal relatives), which are supplied to the dealer by the
regional distributor.
Month
Units
Sold Index Month
Units
Sold Index
Jan. 640 0.80 Jul. 765 0.90
Feb. 648 0.80 Aug. 805 1.15
Mar. 630 0.70 Sept. 840 1.20
Apr. 761 0.94 Oct. 828 1.20
May 735 0.89 Nov. 840 1.25
Jun. 850 1.00 Dec. 800 1.25
a. Plot the data. Does there seem to be a trend?
b. Deseasonalize car sales.
c. Plot the deseasonalized data on the same graph as the original data. Comment on the two
graphs.
d. Assuming no proactive approach on the part of management, discuss (no calculations necessary)
how you would forecast sales for the first three months of the next year.
e. What action might management consider based on your findings in part b?
18. The following table shows a tool and die company’s quarterly sales for the current year. What sales
would you predict for the first quarter of next year? Quarter relatives are SR
Operations Problems
1 1.10, SR
2 .99, SR
3 .90, and SR
4 1.01.
Quarter 1 2 3 4
Sales 88 99 108 141.4
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1 9 . Compute seasonal relatives for this quarterly data.
a. Use the SA method.
b. Use the centered moving average method.
c. Which set of relatives is better? Why?
YEAR
Quarter 1 2 3
1 111417
2 202326
3 293235
4 384144
2 0 . An analyst must decide between two different forecasting techniques for weekly sales of roller blades:
a linear trend equation and the naive approach. The linear trend equation is F
t
124 2 t, and it was
developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in
the table, which of these two methods has the greater accuracy if MAD and MSE are used?
t Units Sold
11 147
12 148
13 151
14 145
15 155
16 152
17 155
18 157
19 160
20 165
Operations Problems
2 1 . Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled
water. Actual demand and the two sets of forecasts are as follows:
PREDICTED
DEMAND
Period Demand F1 F2
1686666 2756868 3707270 4747172 5697274 6727076 7807178 8787480
a. Compute MAD for each set of forecasts. Given your results, which forecast appears to be more
accurate? Explain.
b. Compute the MSE for each set of forecasts. Given your results, which forecast appears to be
more accurate?
c. In practice, either MAD or MSE would be employed to compute forecast errors. What factors
might lead a manager to choose one rather than the other?
d. Compute MAPE for each data set. Which forecast appears to be more accurate?
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22. Two independent methods of forecasting based on judgment and experience have been prepared
each month for the past 10 months. The forecasts and actual sales are as follows:
Month Sales Forecast 1 Forecast 2
1 770 771 769
2 789 785 787
3 794 790 792
4 780 784 798
5 768 770 774
6 772 768 770
7 760 761 759
8 775 771 775
9 786 784 788
10 790 788 788
Operations Problems
a. Compute the MSE and MAD for each forecast. Does either forecast seem superior? Explain.
b. Compute MAPE for each forecast.
c. Prepare a naive forecast for periods 2 through 11 using the given sales data. Compute each of the
following; (1) MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2 s control limits. How do
the naive results compare with the other two forecasts?
23. Long-Life Insurance has developed a linear model that it uses to determine the amount of term life
insurance a family of four should have, based on the current age of the head of the household. The
equation is:
yx150 1.
where
y Insurance needed ($000)
x Current age of head of household
a. Plot the relationship on a graph.
b. Use the equation to determine the amount of term life insurance to recommend for a family of
four if the head of the household is 30 years old.
24. Timely Transport provides local delivery service for a number of downtown and suburban busi-nesses. Delivery charges are based on distance and weight involved for each delivery: 10 cents per
pound and 15 cents per mile. Also, there is a $10 handling fee per parcel.
a. Develop an expression that summarizes delivery charges.
b. Determine the delivery charge for transporting a 40-pound parcel 26 miles.
25. The manager of a seafood restaurant was asked to establish a pricing policy on lobster dinners.
Experimenting with prices produced the following data:
Average Number
Sold per Day, y Price, x
Average Number
Sold per Day, y Price, x
200 $6.00 155 $8.25
190 6.50 156 8.50
188 6.75 148 8.75
180 7.00 140 9.00
170 7.25 133 9.25
162 7.50
160 8.00
Operations Problems
a. Plot the data and a regression line on the same graph.
b. Determine the correlation coefficient and interpret it.
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2 6 . The following data were collected during a study of consumer buying patterns:
Observation xy Observation xy
1 15 74 8 18 78
2 25 80 9 14 70
3 40 84 10 15 72
4 32 81 11 22 85
5 51 96 12 24 88
6 47 95 13 33 90
7 30 83
a. Plot the data.
b. Obtain a linear regression line for the data.
c. What percentage of the variation is explained by the regression line?
d. Use the equation determined in part b to predict the expected value of y for x 41.
27. Lovely Lawns, Inc., intends to use sales of lawn fertilizer to predict lawn mower sales. The store
manager estimates a probable six-week lag between fertilizer sales and mower sales. The pertinent
data are:
Period
Fertilizer
Sales
(tons)
Number of
Mowers Sold
(six-week lag) Period
Fertilizer
Sales
(tons)
Operations Problems
Number of
Mowers Sold
(six-week lag)
1 1.6 10 8 1.3 7
2 1.3 8 9 1.7 10
3 1.8 11 10 1.2 6
4 2.0 12 11 1.9 11
5 2.2 12 12 1.4 8
6 1.6 9 13 1.7 10
7 1.5 8 14 1.6 9
a. Determine the correlation between the two variables. Does it appear that a relationship between
these variables will yield good predictions? Explain.
b. Obtain a linear regression line for the data.
c. Predict expected lawn mower sales for the first week in August, given fertilizer sales six weeks
earlier of 2 tons.
28. The manager of a travel agency has been using a seasonally adjusted forecast to predict demand for
packaged tours. The actual and predicted values are as follows:
Period Demand Predicted
1 129 124
2 194 200
3 156 150
4 91 94
5 85 80
6 132 140
7 126 128
8 126 124
9 95 100
10 149 150
11 98 94
12 85 80
13 137 140
14 134 128
Operations Problems
a. Compute MAD for the fifth period, then update it period by period using exponential smoothing
with .3.
b. Compute a tracking signal for periods 5 through 14 using the initial and updated MADs. If limits
of 4 are used, what can you conclude?
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29. Refer to the data in problem 22.
a. Compute a tracking signal for the 10th month for each forecast using the cumulative error for
months 1 to 10. Use action limits of 4. Is there bias present? Explain.
b. Compute 2 s control limits for each forecast.
30. The classified department of a monthly magazine has used a combination of quantitative and qualita-tive methods to forecast sales of advertising space. Results over a 20-month period are as follows:
Month Error Month Error
1 8 11 1
2 2 12 6
3 4 13 8
4 7 14 4
5 9 15 1
6 5 16 2
7 0 17 4
8 3 18 8
9 9 19 5
10 4 20 1
Operations Problems
a. Compute a tracking signal for months 11 through 20. Compute an initial value of MAD for
month 11, and then update it for each month using exponential smoothing with .1. What can
you conclude? Assume limits of 4.
b. Using the first half of the data, construct a control chart with 2 s limits. What can you conclude?
c. Plot the last 10 errors on the control chart. Are the errors random? What is the implication of this?
31. A textbook publishing company has compiled data on total annual sales of its business texts for the
preceding nine years:
Year: 1 23456789
Sales (000): 40.2 44.5 48.0 52.3 55.8 57.1 62.4 69.0 73.7
a. Using an appropriate model, forecast textbook sales for each of the next five years.
b. Prepare a control chart for the forecast errors using the original data. Use 2 s limits.
c. Suppose actual sales for the next five years turn out as follows:
Year: 10 11 12 13 14
Sales (000): 77.2 82.1 87.8 90.6 98.9
Is the forecast performing adequately? Explain.
32. A manager has just received an evaluation from an analyst on two potential forecasting alternatives.
The analyst is indifferent between the two alternatives, saying that they should be equally effective.
Period: 12345678910
Data: 37 39 37 39 45 49 47 49 51 54
Alt. 1: 36 38 40 42 46 46 46 48 52 55
Alt. 2: 36 37 38 38 41 52 47 48 52 53
a. What would cause the analyst to reach this conclusion?
b. What information can you add to enhance the analysis?
33. A manager uses this equation to predict demand for landscaping services: F
t
10 5 t. Over the
past eight periods, demand has been as follows:
Period, t: 12345678
Demand: 15 21 23 30 32 38 42 47
Is the forecast performing adequately? Explain.
34. A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives are
SR
1
.90, SR
2
.95, SR
3
1.05, and SR
4
1.10. The trend equation is: Ft 10 5 t. Over the
past nine quarters, demand has been as follows:
Period, t: 123456789
Demand: 14 20 24 31 31 37 43 48 52
Is the forecast performing adequately? Explain.
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