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Solution Manual for Operations Management: Sustainability and Supply Chain Management, 13th Edition

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    Operations Management Thirteenth Edition Principles of Operations Management Eleventh Edition Jay Heizer Barry Render Chuck Munson Solutions Manual (Download only) for Operations Management, 13e and Principles of Operations Management 11e

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    3 Contents Chapter 1 Operations and Productivity 1 Discussion Questions 1 Ethical Dilemma 3 American Car Battery Industry 3 End-of-Chapter Problems 3 Case Study 7 Uber Technologies, Inc. 7 Video Case Studies 7 Frito-Lay: Operations Management in Manufacturing 7 Hard Rock Cafe: Operations Management in Services 8 Additional Case Studies 11 National Air Express 11 Zychol Chemicals Corporation 11 Chapter 2 Operations Strategy in a Global Environment 13 Discussion Questions 13 Ethical Dilemma 15 End-of-Chapter Problems 16 Case Study 18 Rapid-Lube 18 Video Case Studies 19 Strategy at Regal Marine 19 Hard Rock Cafe’s Global Strategy 20 Outsourcing Offshore at Darden 20 Additional Case Study 21 Outsourcing to TATA 21 Chapter 3 Project Management 22 Discussion Questions 22 Ethical Dilemma 24 Active Model Exercise 25 ACTIVE MODEL 3.1: Gantt Chart 25 End-of-Chapter Problems 26 Video Case Studies 41 Project Management At Arnold Palmer Hospital 41 Managing Hard Rock’s Rockfest 42 Additional Case Studies 44 Shale Oil Company 44 Southwestern University: A 46 Chapter 4 Forecasting 48 Discussion Questions 48 Ethical Dilemma 51 Active Model Exercises* 51 ACTIVE MODEL 4.1: Moving Averages 51 ACTIVE MODEL 4.2: Exponential Smoothing 51 ACTIVE MODEL 4.3: Exponential Smoothing with Trend Adjustment 51 ACTIVE MODEL 4.4: Trend Projections 52 End-of-Chapter Problems 52 Case Study 82

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    4 Southwestern University: B 82 Video Case Studies 83 Forecasting Ticket Revenue for Orlando Magic Basketball Games 83 Forecasting at Hard Rock Cafe 84 Additional Case Studies 85 The North-South Airlines 85 Digital Cell Phone, Inc. 87 Chapter 5 Design of Goods and Services 89 Discussion Questions 89 Ethical Dilemma 91 Active Model Exercise 92 Active Model 5.1: Decision Tree 92 End-of-Chapter Problems 92 Case Study 104 De Mar’s Product Strategy 104 Video Case Studies 105 Product Design at Regal Marine 105 Celebrity Cruises Designs A New Ship 106 Supplement 5 Sustainability in the Supply Chain 107 Discussion Questions 107 End-of-Supplement Problems 108 Video Case Studies 112 Building Sustainability at the Orlando Magic’s Amway Center 112 Green Manufacturing And Sustainability at Frito-Lay 113 “Saving The Waves” At Celebrity Cruises 113 Additional Case Study 114 Environmental Sustainability at Walmart 114 Chapter 6 Managing Quality 116 Discussion Questions 116 Ethical Dilemma 118 Active Model Exercise* 119 ACTIVE MODEL 6.1: Pareto Charts 119 End-of-Chapter Problems 119 Case Study 128 Southwestern University: C 128 Video Case Studies 131 The Culture of Quality at Arnold Palmer Hospital 131 Quality Counts at Alaska Airlines 132 Celebrity Cruises: A Premium Experience 133 Additional Case Studies 134 Westover Electrical, Inc. 134 Quality at the Ritz-Carlton Hotel 135 Supplement 6 Statistical Process Control 137 Discussion Questions 137 Active Model Exercises* 139 ACTIVE MODEL S6.1: - X bar Chart 139 ACTIVE MODEL S6.2: p -Chart—with data 139 ACTIVE MODEL S6.3: Process Capability 140 End-of-Supplement Problems 140 Case Study 160

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    5 Bayfield Mud Company 160 Video Case Studies 162 Frito-Lay’s Quality-Controlled Potato Chips 162 Farm to Fork: Quality at Darden Restaurants 162 Additional Case Study 163 Green River Chemical Co. 163 Chapter 7 Process Strategies 164 Discussion Questions 164 Ethical Dilemma 166 Active Model Exercise 167 ACTIVE MODEL 7.1: Crossover Chart 167 End-of-Chapter Problems 167 Case Study 172 Rochester Manufacturing’s Process Decision 172 Video Case Studies 172 Process Strategy at Wheeled Coach 172 Alaska Airlines 20-Minute Baggage Process—Guaranteed! 173 Process Analysis at Arnold Palmer Hospital 174 Additional Case Study 176 Matthew Yachts, Inc. 176 Supplement 7 Capacity and Constraint Management 177 Discussion Questions 177 Active Model Exercises 178 ACTIVE MODEL S7.1: Productivity 178 ACTIVE MODEL S7.2: Break-even Analysis 179 End-of-Supplement Problems 179 Video Case Study 191 Capacity Planning at Arnold Palmer Hospital 191 Additional Case Study 192 Southwestern University: D 192 Chapter 8 Location Strategies 194 Discussion Questions 194 Ethical Dilemma 196 Active Model Exercise 196 ACTIVE MODEL 8.1: Center of Gravity 196 End-of-Chapter Problems 196 Case Study 209 Southern Recreational Vehicle Company 209 Video Case Studies 210 Locating the Next Red Lobster Restaurant 210 Where to Place the Hard Rock Cafe 210 Additional Case Study 214 Southwestern University: E 214 Chapter 9 Layout Strategies 216 Discussion Questions 216 Ethical Dilemma 219 Active Model Exercise 219 ACTIVE MODEL 9.1: Process Layout 219 End-of-Chapter Problems 219

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    6 Case Study 243 State Automobile License Renewals 243 Video Case Studies 245 Laying out Arnold Palmer Hospital’s New Facility 245 Facility Layout at Wheeled Coach 246 Additional Case Study 247 Microfix, inc. 247 Chapter 10 Human Resources, Job Design, and Work Measurement 248 Discussion Questions 248 Active Model Exercise 250 ACTIVE MODEL 10.1: Work Sampling 250 Ethical Dilemma 250 End-of-Chapter Problems 250 Case Study 270 Jackson Manufacturing Co. 270 Video Case Studies 271 The “People” Focus: Human Resources at Alaska Airlines 271 Hard Rock’s Human Resource Strategy 272 Additional Case Studies 272 Chicago Southern Hospital 272 The Fleet that Wanders 273 Chapter 11 Supply Chain Management 274 Discussion Questions 274 Ethical Dilemma 276 End-of-Chapter Problems 276 Video Case Studies 279 Darden’s Global Supply Chains 279 Supply Chain Management at Regal Marine 280 Arnold Palmer Hospital’s Supply Chain 280 Supplement 11 Supply Chain Management Analytics 282 Discussion Questions 282 End-of-Supplement Problems 284 Chapter 12 Inventory Management 293 Discussion Questions 293 Ethical Dilemma 295 Active Model Exercises 295 ACTIVE MODEL 12.1: Economic Order Quantity (EOQ) Model 295 ACTIVE MODEL 12.2: Production Order Quantity Model 296 End-of-Chapter Problems 296 Case Study 312 Zhou Bicycle Company 312 Video Case Studies 313 Managing Inventory at Frito-Lay 313 Inventory Management At Celebrity Cruises 314 Inventory Control at Wheeled Coach 315 Additional Case Studies 315 Southwestern University: F 315 Laplace Power and Light 317

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    7 Chapter 13 Aggregate Planning and S&OP 319 Discussion Questions 319 Ethical Dilemma 321 Active Model Exercise 321 ACTIVE MODEL 13.1: Aggregate Planning 321 End-of-Chapter Problems 322 Case Study 339 Andrew-Carter, Inc. 339 Video Case Study 340 Using Revenue Management to Set Orlando Magic Ticket Prices 340 Additional Case Studies 340 Cornwell Glass 340 Southwestern University: (G) 342 Chapter 14 Material Requirements Planning (MRP) and ERP 344 Discussion Questions 344 Ethical Dilemma 347 Active Model Exercise 347 ACTIVE MODEL 14.1: Order Releases 347 End-of-Chapter Problems 347 Video Case Studies 372 When 18,500 Orlando Magic Fans Come to Dinner 372 MRP At Wheeled Coach 374 Additional Case Studies 374 IKON’S Attempt at ERP 374 Hill’s Automotive, Inc. 375 Chapter 15 Short-Term Scheduling 376 Discussion Questions 376 Ethical Dilemma 377 Active Model Exercise 377 ACTIVE MODEL 15.1: Job Shop Sequencing 377 End-of-Chapter Problems 378 Case Study 398 Old Oregon Wood Store 398 Video Case Studies 400 From the Eagles to The Magic: Converting the Amway Center 400 Scheduling at Hard Rock Cafe 401 Additional Case Study 402 Payroll Planning, Inc. 402 Chapter 16 Lean Operations 403 Discussion Questions 403 Ethical Dilemma 404 End-of-Chapter Problems 404 Video Case Studies 407 Lean Operations at Alaska Airlines 407 JIT at Arnold Palmer Hospital 408 Additional Case Studies 408 JIT After a Catastrophe 408 Mutual Insurance Company of Iowa 409

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    8 Chapter 17 Maintenance and Reliability 411 Discussion Questions 411 Ethical Dilemma 413 Active Model Exercises 413 ACTIVE MODEL 17.1: Series Reliability 413 ACTIVE MODEL 17.2: Redundancy 413 ACTIVE MODEL 17.3: Parallel Systems 413 End-of-Chapter Problems 414 Video Case Study 417 Maintenance Drives Profits at Frito-Lay 417 Additional Case Studies 418 Cartak’s Department Store 418 Worldwide Chemical Company 418 Business Analytics Module A Decision-Making Tools 420 Discussion Questions 420 End-of-Module Problems 421 Case Study 433 Tom Thompson’s Liver Transplant 433 Additional Case Studies 433 Arctic, Inc. 433 Ski Right Corp. 434 Warehouse Tenting At The Port Of Miami 435 Business Analytics Module B Linear Programming 436 Discussion Questions 436 Active Model Exercise 437 ACTIVE MODEL B.1: LP Graph 437 End-of-Module Problems 438 Case Study 460 Quain Lawn and Garden Inc. 460 Video Case Study 461 Using LP to Meet Scheduling Challenges at Alaska Airlines 461 Additional Case Studies 462 Chase Manhattan Bank 462 Coastal States Chemical 464 Business Analytics Module C Transportation Models 466 Discussion Questions 466 End-of-Module Problems 467 Case Study 480 Custom Vans, Inc. 480 Additional Case Study 482 Consolidated Bottling: B 482 Business Analytics Module D Waiting-Line Models 484 Discussion Questions 484 Active Model Exercises 488 ACTIVE MODEL D.1: Single Server Model 488 ACTIVE MODEL D.2: Multiple Server System with Costs 488

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    9 ACTIVE MODEL D.3: Constant Service Times 489 End-of-Module Problems 489 Case Studies 505 New England Foundry 505 The Winter Park Hotel 506 Additional Case Study 506 Pantry Shopper 506 Business Analytics Module E Learning Curves 508 Discussion Questions 508 Active Model Exercise 509 ACTIVE MODEL E.1: Unit Curve, Cumulative Curve, and Costs 508 End-of-Module Problems 509 Case Study 515 SMT’S Negotiation with IBM 515 Business Analytics Module F Simulation 516 Discussion Questions 516 End-of-Module Problems 518 Case Study 531 Alabama Airlines Call Center 531 Additional Case Study 533 Saigon Transport 533 Business Analytics Module G Applying Analytics to Big Data in Operations Management 534 Discussion Questions 534 End-of-Module Problems 535 Online Tutorial 1 Statistical Tools for Managers 538 Discussion Questions 538 End-of-Tutorial Problems 538 Online Tutorial 2 Acceptance Sampling 543 Discussion Questions 543 End-of-Tutorial Problems 543 Online Tutorial 3 The Simplex Method of Linear Programming 545 Discussion Questions 545 End-of-Tutorial Problems 545 Online Tutorial 4 The MODI and VAM Methods of Solving Transportation Problems 551 Discussion Questions 551 End-of-Tutorial Problems 551 Online Tutorial 5 Vehicle Routing and Scheduling 557 Discussion Questions 557 End-of-Tutorial Problems 558 Case Study 559 Routing And Scheduling Of Phlebotomists 559

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    1 1 1 C H A P T E R Operations and Produ c tivity D ISCUSSION Q UESTIONS 1. The text suggests four reasons to study OM. We want to understand (1) how people organize themselves for productive enterprise, (2) how goods and services are produced, (3) what operations managers do, and (4) this costly part of our economy and most enterprises. LO 1.1: Define operations management AACSB: Application of knowledge 2. With some 40% of all jobs being in the OM field, the career opportunities are prolific. The text suggests many career opportunities. OM students find initial jobs throughout the OM field, including supply chain, logistics, purchasing, production planning and scheduling, plant layout, maintenance, quality control, inventory management, etc. LO 1.3: Identify career opportunities in operations management AACSB: Application of knowledge 3. Possible responses include: Adam Smith (work specialization/ division of labor), Charles Babbage (work specialization/division of labor), Frederick W. Taylor (scientific management), Walter Shewart (statistical sampling and quality control), Henry Ford (moving assembly line), Charles Sorensen (moving assembly line), Frank and Lillian Gilbreth (motion study), Eli Whitney (standardization). LO 1.1: Define operations management AACSB: Application of knowledge 4. See references in the answer to Question 3. LO 1.1: Define operations management AACSB: Application of knowledge 5. The actual charts will differ, depending on the specific organization the student chooses to describe. The important thing is for students to recognize that all organizations require, to a greater or lesser extent, (a) the three primary functions of operations, finance/accounting, and marketing; and (b) that the emphasis or detailed breakdown of these functions is dependent on the specific competitive strategy employed by the firm. LO 1.1: Define operations management AACSB: Application of knowledge 6. The answer to this question may be similar to that for Question 5. Here, however, the student should be encouraged to utilize a more detailed knowledge of a past employer and indicate on the chart additional information such as the number of persons employed to perform the various functions and, perhaps, the position of the functional areas within the overall organization hierarchy. LO 1.1: Define operations management AACSB: Application of knowledge

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    2 CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y 7. The basic functions of a firm are marketing, accounting/ finance, and operations. An interesting class discussion: “Do all firms/organizations (private, government, not-for-profit) perform these three functions?” The authors’ hypothesis is yes, they do. LO 1.1: Define operations management AACSB: Application of knowledge 8. The 10 strategic decisions of operations management are product design, quality, process, location, layout, human resources, supply-chain management, inventory, scheduling (intermediate and short-term), and maintenance. We find this structure an excellent way to help students organize and learn the material. LO 1.1: Define operations management AACSB: Application of knowledge 9. Four areas that are important to improving labor productivity are (1) basic education (basic reading and math skills), (2) diet of the labor force, (3) social overhead that makes labor available (water, sanitation, transportation, etc.), and (4) maintaining and expanding the skills necessary for changing technology and knowledge, as well as for teamwork and motivation. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Application of knowledge 10. Productivity is harder to measure when the task becomes more intellectual. A knowledge society implies that work is more intellectual and therefore harder to measure. Because the U.S. and many other countries are increasingly “knowledge” societies, productivity is harder to measure. Using labor-hours as a measure of productivity for a postindustrial society versus an industrial or agriculture society is very different. For example, decades spent developing a marvelous new drug or winning a very difficult legal case on intellectual property rights may be significant for postindustrial societies, but not show much in the way of productivity improvement measured in labor-hours. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Analytical thinking 11. Productivity is difficult to measure because precise units of measure may be lacking, quality may not be consistent, and exogenous variables may change. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Reflective thinking 12. Mass customization is the flexibility to produce to meet specific customer demands, without sacrificing the low cost of a product-oriented process. Rapid product development is a source of competitive advantage. Both rely on agility within the organization. LO 1.1: Define operations management AACSB: Application of knowledge 13. Labor productivity in the service sector is hard to improve because (1) many services are labor intensive and (2) they are individually (personally) processed (the customer is paying for that service—the haircut), (3) it may be an intellectual task performed by professionals, (4) it is often difficult to mechanize and automate, and (5) it is often difficult to evaluate for quality. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Reflective thinking 14. Taco Bell designed meals that were easy to prepare; with actual cooking and food preparation done elsewhere; automation to save preparation time; reduced floor space; manager training to increase span of control. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Application of knowledge

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    CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y 3 15. Bureau of Labor Statistics (stats.bls.gov) is a good place to start. Results will vary for each year, but overall data for the economy will range from 0.9% to 4.8%, and mfg. could be as high as 5% and services between 1% and 2%. The data will vary even more for months or quarters. The data are frequently revised, often substantially. LO 1.7: Compute multifactor productivity AACSB: Application of knowledge E THICAL D ILEMMA AMERICAN CAR BATTERY INDUSTRY You may want to begin the discussion by asking how ethical it is for you to be in the lead battery business when you know that any batteries you recycle will very likely find their way to an overseas facility (probably Mexico) with, at best, marginal pollution containment. Then after a likely conclusion of “Well someone has to provide batteries,” you can move to the following discussion. (a) As owner of an independent auto repair shop trying to dispose of a few old batteries each week, your options may be limited. But as an ethical operator, your first option is to put pressure on your battery supplier to take your old batteries. Alternatively, shop for a battery supplier who wants your business enough to dispose of your old batteries. Third, because there is obviously a market for the lead in old batteries, some aggressive digging may uncover an imaginative recycler who can work out an economical arrangement for pickup or delivery of your old batteries. Another option is, of course, to discontinue the sale of batteries. (This is a problem for many small businesses; ethical decisions and regulation may be such that they often place an expensive and disproportionate burden on a small firm.) (b) As manager of a large retailer responsible for disposal of thousands of used batteries each week, you should have little trouble finding a battery supplier with a reverse supply chain suitable for disposal of old batteries. Indeed, a sophisticated retailer, early on in any supply-chain development process, includes responsible disposal of environmentally dangerous material as part of the negotiations. Disposal of old batteries should be a minor issue for a large retailer. (c) For both a small and large retailer, the solution is to find a “sustainable” solution or get out of the battery business. Burying the batteries behind the store is not an option. Supplement 5: Sustainability in the Supply Chain provides some guidelines for a deeper class discussion. E ND - OF - C HAPTER P RO B LEMS 120 boxes (a) = 3.0 boxes/hour 40 hours 1.1 125 boxes (b) = 3.125 boxes/hour 40 hours (c) Change in productivity = 0.125 box/hour (d) 0.125 box Percentage change = = 4.167% 3.0 1.2 (a) Labor productivity is 160 valves/80 hours = 2 valves per hour (b) New labor productivity = 180 valves/80 hours = 2.25 valves per hour (c) Percentage change in productivity = .25 valve/2 valves = 12.5% 1.3 So, 57,600 = = 200 (160)(12)(0.15) L laborers employed 57,600 0.15 = , where number of laborers (160)(12)( ) employed at the plant L L =

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    4 CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y Units produced 100 pkgs (a) = = 20 pkgs/hour Input 5 1.4 133 pkgs (b) = 26.6 pkgs per hour 5 6.6 (c) Increase in productivity = = 33.0% 20 1.5 Resource Last Year This Year Change Percentage Change Labor 1, 000 = 3.33 300 1, 000 = 3.64 275 0.31 0.31 = 9.3% 3.33 Resin 1, 000 = 20 50 1, 000 = 22.22 45 2.22 2.22 = 11.1% 20 Capital 1, 000 = 0.1 10, 000 1, 000 = 0.09 11, 000 –0.01 0.01 = 10.0% 0.1 − − Energy 1, 000 = 0.33 3, 000 1, 000 = 0.35 2, 850 0.02 0.02 = 6.1% 0.33 1.6 Last Year This Year Production 1,000 1,000 Labor hr. @ $10 $3,000 $2,750 Resin @ $5 250 225 Capital cost/month 100 110 Energy 1,500 1,425 $4,850 $4,510 [(1,000 / 4,510) (1,000 / 4,850)] (1,000 / 4,850) − = − 0.222 0.206 0.016 = = 7.8% improvement* 0.206 0.206 *with rounding to 3 decimal places. Output Productivity = Input 1.7 65 65 (a) Labor productivity = = (520 × 13) $6,760 = .0096 rug per labor $ 65 Multifactor (b) = productivity (520 × $13) + (100 × $5) + (20 × $50) 65 = = .00787 rug per $ $8, 260

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    CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y 5 1.8 (a) Labor productivity = 1,000 tires/400 hours = 2.5 tires/hour. (b) Multifactor productivity is 1,000 tires/(400 × $12.50 + 20,000 × $1 + $5,000 + $10,000) = 1,000 tires/$40,000 = 0.025 tire/dollar. (c) Multifactor productivity changes from 1,000/40,000 to 1,000/39,000, or from 0.025 to 0.02564; the ratio is 1.0256, so the change is a 2.56% increase. 1.9 Last Year This Year Change Percent age Change Labor hrs. 1,500 = 4.29 350 1,500 = 4.62 325 0.33 4.29 = 7.7% Capital invested 1,500 = 0.10 15, 000 1,500 = 0.08 18, 000 0.02 0.1 − = –20% Energy (btu) 1,500 = 0.50 3, 000 1,500 = 0.55 2, 750 0.05 0.50 = 10% Productivity of capital did drop; labor productivity increased as did energy, but by less than the anticipated 15%. 1.10 Multifactor productivity is: 375 autos/[($20 × 10,000) + ($1,000 × 500) + ($3 × 100,000)] = 375/(200,000 + 500,000 +300,000) = 375/1,000,000 = .000375 auto per dollar of inputs 1.11 (a) Before: 500/20 = 25 boxes per hour; 1.12 1,500 × 1.25 = 1,875 (new demand) ≅ ≅ Outputs = Productivity Inputs 1,875 = 2.344 Labor-hours 1,875 New process = 800 labor-hours 2.344 800 = 5 workers 160 1,500 Current process = = 2.344 labor-hours 1,500 = labor-hours 640 2.344 640 = 4 workers 160 Add one worker. After, 650/24 = 27.08 (b) 27.08/25 = 1.083, or an increase of 8.3% in productivity (c) New labor productivity = 700/24 = 29.167 boxes per hour

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    6 CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y 1.13 (a) Labor change: 1,500 1,500 = = .293 loaf/$ (640 × $8) 5,120 1,875 = 0.293 loaf/$ (800 × $8) (b) Investment change: 1,500 1,500 = = .293 loaf/$ (640 × $8) 5,120 1,875 1,875 = = .359 loaf/$ (640 × 8) + (100) 5,220 .293 – .293 (c) Percentage change : = 0 (labor) .293 .359 – .293 Percentage change : = .225 .293 = 22.5% (investment) The better option is to purchase a new blender because it generates more loaves per dollar. 1,500 Old process = (640 8) + 500 + (1,500 0.35) 1,500 = = 0.244 loaf/$ 6,145 1,875 New process = (800 8) + 500 + (1,875 0.35) 1,875 = = 0.248 loaf/$ 7,556.25 0.248 – 0.244 Percentage change = = 1.6% 0.244 × × × × 4 1.1 labor-hours labor-hours 6,600 vans (a) = 0.10 = 66,000 x x 1.15 There are 300 laborers. So, 66,000 labor-hours = 220 labor-hours/laborer 300 laborers on average, per month $ output 52($90) + 80($198) labor-hours 8(45) $20,520 = $57.00 per labor-hour 360 1.16 = = = = 6,600 vans (b) Now = 0.11, so 60,000 labor-hours labor-hours 60,000 labor-hours so, 200 labor-hours/laborer 300 laborers on average, per month x x

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    CHAPTER 1 O P E R A T I O N S A N D P R O D U C T I V I T Y 7 1 1,500 Last year = (350 8) + (15,000 0.0083) + (3,000 0.6) 1.17 × × × = + + 1,500 2,800 124.50 1,800 = = 1,500 0.317 doz / $ 4,724.5 × × × 1500 This year = (325 8) + (18,000 0.0083) + (2,750 0.6) 0.341 doz / $ = 0.341 0.317 Percentage change = 0.317 0.076, or 7.6% increase − = C ASE S TUDY UBER TECHNOLOGIES, INC. 1. First, some drivers (maybe most) may not require a wage that equals those fully engaged in the “taxi” business. It truly could be a supplemental income. . . . “I’m going that way anyhow so let’s make a few dollars while on the way.” Similarly, the capital investment cost approaches zero as the car is going that direction anyhow. These are idle or underutilized resources. From society’s perspective, Uber and its like competitors are desirable because both idle or wasted labor and capital resources are being utilized. At the same time, as a bonus, Uber is reducing traffic and auto pollution while speeding up the transport of individuals and local commerce. As a competitor for the traditional taxi service, Uber seems to be an enhancement in efficiency. For those faculty who what to spend some time on the larger productivity message, this case provides such an opportunity. Uber, as Joseph Schumpeter would suggest, has developed a disruptive technology (creative destruction, in a Schumpeterian translation). Innovations such as this are exactly how economic efficiency is enhanced. The traditional taxi services, with some imagination, could have developed and adopted this technology, but most were ensconced in their own regulatory cocoon. As is often the case, it takes an outsider, such as Uber et al. to be creative by putting unused resources to use and providing society greater efficiency. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Analytical thinking 2. Perhaps a business model similar to Uber’s can be applied to the trucking industry. And, indeed, Uber has established an Uber app for the trucking industry. An estimated 30% of trucking backhauls are empty. However, the number of independent truckers or truckers with the latitude to alter their route may be very small. And this number must be a tiny fraction of independent automobile drivers. So, the ability to “Uberize” trucking may be very difficult, but utilizing that idle 30% would be huge benefit to society. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Analytical thinking 3. Perhaps the Uber model can be used for package delivery, documents, and everything from flowers to groceries. Airbnb (www.airbnb.com) is applying a similar model to short-term rentals of rooms, apartments, and homes—competing with more traditional bed and breakfast facilities and hotels. LO 1.8: Identify the critical variables in enhancing productivity AACSB: Analytical thinking V IDEO C ASE S TUDI ES FRITO-LAY: OPERATIONS MANAGEMENT IN MANUFACTURING This case provides a great opportunity for an instructor to stimulate a class discussion early in the course about the pervasiveness of the 10 decisions of OM with this case alone or in conjunction with the Hard Rock Cafe case. There is a short video (7 minutes) available in MyLab Operations Management that is filmed specifically for this text and supplements this case.

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