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business
operations management 6th

Operations Management Sustainability And Supply Chain Management 13th Global Edition Jay Heizer, Barry Render, Chuck Munson - Solutions

How would you build a culture of quality in an organization such as Arnold Palmer Hospital?••• What techniques does Arnold Palmer Hospital practice in its drive for quality and continuous improvement? kio5
Develop a fish-bone diagram illustrating the quality variables for a patient who just gave birth at Arnold Palmer Hospital (or any other hospital). kio5
What are some ways that Alaska can ensure that quality and performance metric standards are met when the company outsources its ground operations to a contract provider? kio5
Identify several quality metrics, in addition to those identified earlier, that you think Alaska tracks or should be tracking. kio5
Think about a previous problem that you had when flying, for example, a late flight, a missed connection, or lost luggage.How, if at all, did the airline respond? Did the airline adequately address your situation? If not, what else should they have done? Did your experience affect your desire
See the accompanying table. The contractor received a perfect Time to Carousel score of 10 total points, even though its performance was not “perfect.” How many total points would the contractor have received with the following performance scores: 93.2% of flights scanned, 63.5% of bags
What unique aspects of the cruise industry make quality service more difficult to attain? What aspects help raise quality? kio5
How does the cruise operation differ from that at a land-based hotel? kio5
How could control charts, Pareto diagrams, and cause-andeffect diagrams be used to identify quality problems at Celebrity? kio5
Suppose that on two successive cruises of the same ship, the cruise line receives NPS scores of: (Trip 1) 78% “advocates,” 4% “neutrals,”and 18% “detractors” and (Trip 2) 70% “advocates,” 20% “neutrals,” and 10% “detractors.” Which would be preferable and why? kio5
List a dozen quality indicators (besides NPS) that Celebrity also measures. (There are 35 on its guest evaluation form.) kio5
In this chapter, quality is defined as:a) the degree of excellence at an acceptable price and the control of variability at an acceptable cost.b) how well a product fits patterns of consumer preferences.c) the totality of features and characteristics of a product or service that bears on its
ISO 9000 is an international standard that addresses _____. kio5
If 1 million passengers pass through the Jacksonville Airport with checked baggage each year, a successful Six Sigma program for baggage handling would result in how many passengers with misplaced luggage?a) 3.4b) 6.0c) 34d) 2,700e) 6 times the monthly standard deviation of passengers kio5
The process of identifying other organizations that are best at some facet of your operations and then modeling your organization after them is known as:a) continuous improvement.b) employee empowerment.c) benchmarking.d) copycatting.e) patent infringement. kio5
The Taguchi method includes all except which of the following major concepts?a) Employee involvementb) Remove the effects of adverse conditionsc) Quality loss functiond) Target specifications kio5
The seven tools of total quality management are ______, ______, ______, ______, ______, ______, and ______. kio5
Understand the three time horizons and which models apply for each 140
Explain when to use each of the four qualitative models 143
Apply the naive, moving-average, exponential smoothing, and trend methods 145
Compute three measures of forecast accuracy 150
Develop seasonal indices 159
Conduct a regression and correlation analysis 163
Use a tracking signal 170
What is a qualitative forecasting model, and when is its use appropriate? LOP1
Identify and briefly describe the two general forecasting approaches. LOP1
Briefly describe the steps that are used to develop a forecasting system. LOP1
A skeptical manager asks what medium-range forecasts can be used for. Give the manager three possible uses/purposes. LOP1
Explain why such forecasting devices as moving averages, weighted moving averages, and exponential smoothing are not well suited for data series that have trends. LOP1
What is the basic difference between a weighted moving average and exponential smoothing? LOP1
What three methods are used to determine the accuracy of any given forecasting method? How would you determine whether time-series regression or exponential smoothing is better in a specific application? LOP1
Research and briefly describe the Delphi technique. How would it be used by an employer you have worked for? LOP1
What is the primary difference between a time-series model and an associative model? LOP1
What type of forecasting method would you recommend to a start-up retailer in terms of quantity, number of products, etc.? Would you use the same method after, say, 5 years of operation? Explain. LOP1
What effect does the value of the smoothing constant have on the weight given to the recent values? LOP1
Explain the value of seasonal indices in forecasting. How are seasonal patterns different from cyclical patterns? LOP1
Which forecasting technique can place the most emphasis on recent values? How does it do this? LOP1
How can an exponential smoothing model be made more responsive? LOP1
What is the purpose of a tracking signal? LOP1
Explain, in your own words, the meaning of the correlation coefficient. Discuss the meaning of a negative value of the correlation coefficient. LOP1
If the benefits of implementing CPFR are so evident, why are companies reticent to commit to this concept? LOP1
Give examples of industries that are affected by seasonality.Why would these businesses want to filter out seasonality? LOP1
Summarize in the form of a table the (a) characteristics, (b)strengths, and (c) weaknesses of the following qualitative methods: (i) jury of executive opinion, (ii) Delphi method, and (iii) market survey. LOP1
What happens to the ability to forecast for periods farther into the future? LOP1
CEO John Goodale, at Southern Illinois Power and Light, has been collecting data on demand for electric power in its western subregion for only the past 2 years. Those data are shown in the table below.To plan for expansion and to arrange to borrow power from neighboring utilities during peak
a) Plot the above data on a graph. Do you observe any trend, cycles, or random variations?b) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average. Plot your forecast on the same graph as the original data.c) Starting in year 4 and going to year 12, forecast demand
Refer to Problem 4.2. Develop a forecast for years 2 through 12 using exponential smoothing with a = .4 and a forecast for year 1 of 6. Plot your new forecast on a graph with the actual data and the naive forecast. Based on a visual inspection, which forecast is better? LOP1
The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows:YEAR MILEAGE 1 3,000 2 4,000 3 3,400 4 3,800 5 3,700a) Forecast the mileage for next year
The monthly sales for Yazici Batteries, Inc., were as follows:MONTH SALES January 20 February 21 March 15 April 14 May 13 June 16 July 17 August 18 September 20 October 20 November 21 December 23a) Plot the monthly sales data.b) Forecast January sales using each of the following:i) Naive method.ii)
The actual demand for the patients at Providence Emergency Medical Clinic for the first 6 weeks of this year follows:WEEK ACTUAL NO. OF PATIENTS 1 65 2 62 3 70 4 48 5 63 6 52 Clinic administrator Dara Schniederjans wants you to forecast patient demand at the clinic for week 7 by using this data.
Lenovo uses the ZX-81 chip in some of its laptop computers. The prices for the chip during the past 12 months were as follows:MONTH PRICE PER CHIP ($) MONTH PRICE PER CHIP ($)January 1.80 July 1.80 February 1.67 August 1.83 March 1.70 September 1.70 April 1.85 October 1.65 May 1.90 November 1.70
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table:YEAR 1 2 3 4 5 6 7 8 9 10 11 REGISTRATIONS (000) 4 6 4 5 10 8 7 9 12 14 15a) Develop a 3-year moving average to forecast registrations from year 4 to year 12.b) Estimate demand
Consider the following actual and forecast demand levels for Big Mac hamburgers at a local McDonald’s restaurant:DAY ACTUAL DEMAND FORECAST DEMAND Monday 88 88 Tuesday 72 88 Wednesday 68 84 Thursday 48 80 Friday The forecast for Monday was derived by observing Monday’s demand level and setting
As you can see in the following table, demand for heart transplant surgery at Washington General Hospital has increased steadily in the past few years:YEAR 1 2 3 4 5 6 HEART TRANSPLANTS 45 50 52 56 58 ?The director of medical services predicted 6 years ago that demand in year 1 would be 41
A local retailer is thinking of using exponential smoothing to forecast one of his well-selling products. His problem is that he is not sure if he should use a low or a high value of a.For this reason, he uses the historical data available and tries with values for a = 0.1 and a = 0.2 to find which
Refer to Solved Problem 4.1 on page 176.a) Use a 3-year moving average to forecast the sales of Volkswagen Beetles in Nevada through year 6.b) What is the MAD? LOP1c) What is the MSE?
Refer to Solved Problem 4.1 on page 176. Using smoothing constants of .6 and .9, develop forecasts for the sales of VW Beetles. What effect did the smoothing constant have on the forecast?Use MAD to determine which of the three smoothing constants (.3,.6, or .9) gives the most accurate forecast.
Consider the following actual (At) and forecast (Ft)demand levels for a commercial multiline telephone at Office Max:TIME PERIOD, t ACTUAL DEMAND, At FORECAST DEMAND, Ft 1 50 50 2 42 50 3 56 48 4 46 50 5The first forecast, F1, was derived by observing A1 and setting F1 equal to A1. Subsequent
Income at the architectural firm Spraggins and Yunes for the period February to July was as follows:MONTH FEBRUARY MARCH APRIL MAY JUNE JULY Income(in $ thousand) 70.0 68.5 64.8 71.7 71.3 72.8 Use trend-adjusted exponential smoothing to forecast the firm’s August income. Assume that the initial
Refer to the trend-adjusted exponential smoothing illustration in Example 7 on pages 154–155. Using a = .2 and b = .4, we forecast sales for 9 months, showing the detailed calculations for months 2 and 3. In Solved Problem 4.2, we continued the process for month 4.In this problem, show your
Refer to Problem 4.21. Complete the trend-adjusted exponential-smoothing forecast computations for periods 7, 8, and 9. Confirm that your numbers for Ft, Tt, and FITt match those in Table 4.2 (p. 155).
A warehouse manager wants to estimate the inventory moving in and out of his warehouse each week. An analyst suggests using a 3-, 5-, or 7-week moving average. However, before deciding, he wants to compare the accuracy of each for the most recent 10-week period.WEEK 1 2 3 4 5 6 7 8 9 10 ACTUAL
In the past, Peter Kelle’s tire dealership in Baton Rouge sold an average of 1,000 radials each year. In the past 2 years, 200 and 250, respectively, were sold in fall, 350 and 300 in winter, 150 and 165 in spring, and 300 and 285 in summer. With a major expansion planned, Kelle projects sales
A logistics company has been in business for 4 years and wants to develop monthly indices. Monthly inventory quantities for these years are shown in the table below.a) Develop monthly indices.b) Estimate next year’s forecast for the months April, July, and December, assuming that the annual
Attendance at Orlando’s newest Disneylike attraction, Lego World, has been as follows:QUARTER GUESTS (IN THOUSANDS) QUARTER GUESTS(IN THOUSANDS)Winter Year 1 73 Summer Year 2 124 Spring Year 1 104 Fall Year 2 52 Summer Year 1 168 Winter Year 3 89 Fall Year 1 74 Spring Year 3 146 Winter Year 2 65
North Dakota Electric Company estimates its demand trend line (in millions of kilowatt hours) to be:D = 77 + 0.43Q where Q refers to the sequential quarter number and Q 5 1 for winter of Year 1. In addition, the multiplicative seasonal factors are as follows:QUARTER FACTOR (INDEX)Winter .8 Spring
The number of disk drives (in millions) made at a plant in Taiwan during the past 5 years follows:YEAR DISK DRIVES 1 140 2 160 3 190 4 200 5 210a) Forecast the number of disk drives to be made next year, using linear regression.b) Compute the mean squared error (MSE) when using linear regression.c)
Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during
Emergency calls to the 911 system of Durham, North Carolina, for the past 24 weeks are shown in the following table:WEEK 1 2 3 4 5 6 7 8 9 10 11 12 CALLS 50 35 25 40 45 35 20 30 35 20 15 40 WEEK 13 14 15 16 17 18 19 20 21 22 23 24 CALLS 55 35 25 55 55 40 35 60 75 50 40 65a) Compute the
Using the 911 call data in Problem 4.31, forecast calls for weeks 2 through 25 with a trend-adjusted exponential smoothing model. Assume an initial forecast for 50 calls for week 1 and an initial trend of zero. Use smoothing constants of a = .3 and b = .2. Is this model better than that of Problem
Storrs Cycles has just started selling the new Cyclone mountain bike, with monthly sales as shown in the table. First, coowner Bob Day wants to forecast by exponential smoothing by initially setting February’s forecast equal to January’s sales with a = .1.Co-owner Sherry Snyder wants to use a
Given the following data, use exponential smoothing(a = 0.2) to develop a demand forecast. Assume the forecast for the initial period is 5.PERIOD 1 2 3 4 5 6 DEMAND 7 9 5 9 13 8 LOP1
Calculate (a) MAD and (b) MSE for the following forecast versus actual sales figures:FORECAST 100 110 120 130 ACTUAL 95 108 123 130 LOP1
4.38 Sales of industrial vacuum cleaners at Larry Armstrong Supply Co. over the past 13 months are shown below:MONTH SALES (IN THOUSANDS)Jan.11 Feb.14 March 16 April 10 May 15 June 17 July 11 MONTH SALES (IN THOUSANDS)Aug.14 Sept.17 Oct.12 Nov.14 Dec.16 Jan.11a) Using a moving average with three
Given the following data, use least-squares regression to derive a trend equation. What is your estimate of the demand in period 7? In period 12?PERIOD 1 2 3 4 5 6 DEMAND 7 9 5 11 10 13
The director of the Riley County, Kansas, library system would like to forecast evening patron usage for next week.Below are the data for the past 4 weeks:MON TUE WED THU FRI SAT WEEK 1 210 178 250 215 160 180 WEEK 2 215 180 250 213 165 185 WEEK 3 220 176 260 220 175 190 WEEK 4 225 178 260 225 176
Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Mark has collected the data shown in the following table:DEMAND FOR GUITARS 3 6 7 5 10 7 MAROON
Lori Cook has developed the following forecasting model:where yn = demand for Kool Air conditioners and x 5 the outside temperature (°F)a) Forecast demand for the Kool Air when the temperature is 70° F.b) What is demand when the temperature is 80° F?c) What is demand when the temperature is 90°
The following data relate the sales figures of the bar in Mark Kaltenbach’s small bed-and-breakfast inn in Portand, to the number of guests registered that week:WEEK GUESTS BAR SALES 1 16 $330 2 12 270 3 18 380 4 14 300a) Perform a linear regression that relates bar sales to guests (not to
Kalamia Company tries to forecast the value of its business based on money spent on advertising. The company has been tracking the relationship between sales and money spent on advertising, summarized in the table below (all numbers expressed in thousands of euro).SALES Y 42 6 35 1 3 8 4 5 1 2
Accountants at the Tucson firm, Larry Youdelman, CPAs, believed that several traveling executives were submitting unusually high travel vouchers when they returned from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple
City government has collected the following data on annual sales tax collections and new car registrations:ANNUAL SALES TAX COLLECTIONS(IN MILLIONS)1.0 1.4 1.9 2.0 1.8 2.1 2.3 NEW CAR REGISTRATIONS(IN THOUSANDS)10 12 15 16 14 17 20 Determine the following:a) The least-squares regression equation.b)
Develop a forecasting model, justifying its selection over other techniques, and project attendance through 2020. LOP1
What revenues are to be expected in 2019 and 2020? LOP1
Discuss the school’s options. LOP1
Use the data in Table 4.3 to build a regression model with day of the week as the only independent variable. LOP1
Use the data to build a model with rating of the opponent as the sole independent variable. LOP1
Using Perez’s multiple regression model, what would be the additional sales potential of a Thursday Miami Heat game played during the Christmas holiday? LOP1
What additional independent variables might you suggest to include in Perez’s model? LOP1
Describe three different forecasting applications at Hard Rock.Name three other areas in which you think Hard Rock could use forecasting models. LOP1
What is the role of the POS system in forecasting at Hard Rock? LOP1
Justify the use of the weighting system used for evaluating managers for annual bonuses. LOP1
Name several variables besides those mentioned in the case that could be used as good predictors of daily sales in each cafe. LOP1
At Hard Rock’s Moscow restaurant, the manager is trying to evaluate how a new advertising campaign affects guest counts.Using data for the past 10 months (see the table), develop a least-squares regression relationship and then forecast the expected guest count when advertising is $65,000. LOP1
Forecasting time horizons include:a) long range.b) medium range.c) short range.d) all of the choices. LOP1
Qualitative methods of forecasting include:a) sales force composite.b) jury of executive opinion.c) consumer market survey.d) exponential smoothing.e) all except (d). LOP1
The difference between a moving-average model and an exponential smoothing model is that . LOP1
Average demand for iPods in the Apple store in Rome, Italy, is 800 units per month. The May monthly index is 1.25. What is the seasonally adjusted sales forecast for May?a) 640 unitsb) 798.75 unitsc) 800 unitsd) 1,000 unitse) cannot be calculated with the information given LOP1
The main difference between simple and multiple regression is LOP1.
The tracking signal is the:a) standard error of the estimate.b) cumulative error.c) mean absolute deviation (MAD).d) ratio of the cumulative error to MAD.e) mean absolute percent error (MAPE). LOP1

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