Question: What is the amount of cash received from the sale of special materials if Horizon Insurance elects to outsource publishing to G-Art?
Use the following case to help answer this question:
Horizon Insurance (HI) was a full-service regional insurance agency that has done all the printing and publishing of its own promotional brochures, newsletters, informational pamphlets, and required regulatory reports. Linda Wolfe, the business manager of the agency, had for some time thought that the firm might save money and get equally good services by contracting the publishing work G-Art Inc. She asked G-Art Inc. to give her a quote at the same time she asked Bob Myer her controller to prepare an up-to-date statement of the cost of operating Horizon’s publishing department.
Within a few days, the quote from G-Art Inc. arrived. The firm was prepared to provide all the required publications work for $ 410,000 a year with the contract running a guaranteed term of 4 years with annual renewals thereafter. If the estimated number or assumed mix of publications changed in any given year beyond the baseline planning estimates, the contract price would be adjusted accordingly. Wolfe compared G-Art’s quote with the internal cost figures prepared by Myer:
Table 1; Annual cost of operating HI’s publications department: Myer’s figures.
Materials $40,000
Labor $290,000
Department overhead
Manager’s salary $48,000
Allocated cost of office space $10,000
Depreciation of equipment $32,500
Other expenses (travel, education, ect.) $25,000
$115,500
$445,500
Share of company administrative overhead $30,000
Total cost of department for year $475,000
Wolfe’s initial conclusion was to close Horizon’s publications department and immediately sign the contact offered by G-Art. However, she felt it prudent to give the manager of the department, George Richards, an opportunity to question that tentative conclusion. She called him in and put the facts before him, while at the same time making it clear that Richards’ own job at the agency was not in jeopardy.
Richard came up with the following to keep in mind before his department was closed:
For instance, what will you do with the customed graphic design and printing equipment? It cost $260,000 four years ago, but you’d be lucky if you got $80,000 for it now, even though we had planned on using it for another four years at least. Andthen there is the sizable supply of print materials that includes a lot of specialized ink, specialty card stock, paper, envelopes ect. We bought the custom supplies a year ago when we were pretty flush with cash. At that time it cost us about 125,000 and at the rate we are using it now, it will last us another four years. We used up about one-fifth of it last year. As best as I an tell, Myer’s figure of $40,000 for materials includes about $25,000 for these customized sipplies and $15,000 for generic supplies we use on a regular basis. If we were to buy these custom supplies today it would probably cost us 110% of what we paid for it. But if we try to sell it, we would probably get only 60% of what we paid for it.
Wolf thought that Myer ought to be present during this discussion. She called him in and put Richard’s points to him. Myer said:
If we are going to have all of this talk about “what will happen if” don’t forget the problem of space we’re faced with. We’re paying 12,000 a year in outside office space. If we close Richard’s department we could use of the freed-up space as office space and not need to rent it on the outside.
Wolfe replied:
That’s a good point, though I must say I’m a bit worried about the people if we close the publications department. I don’t think we can find room for any of them elsewhere in the firm. I could see whether G-rt can take any of them, but some of them are getting odler. There’s Walters and Hines, for example. They’ve been with us since they left school 40 years ago, and I think their contract requires us to give them a total severance payoff of about $60,000 each, payable in equal amounts over four years.
Richards showed some relief at this. “ But I still don’t like Myer’s figures” he said. “What about the $30,000 for general administrative overhead. You surely don’t expect to fire anyone in the corporate office if Im closed, do you?
“Probably not” said Myer, but someone has to pay for those costs. We can’t ignore them when we look at an individual department, because fi we do that with each department in turn, we will convince ourselves that accountants, laywers, vice presidents, and the like don’t’ have to be paid for. And they do, believe me”
|
Myer’s figures |
Total cost inside |
Total cost with G-Art Contract |
Savings (higher cost) contracting outside |
|
|
Material: Generic supplies |
$15,000 |
|||
|
Custom supplies |
$25,000 |
|||
|
Labor: Wages |
$290,000 |
|||
|
Severance |
||||
|
Overhead: Manger’s Salary |
$48,000 |
|||
|
Office (internal) |
$10,000 |
|||
|
Office rental |
||||
|
Equipment deprec. |
$32,500 |
|||
|
Other |
$25,000 |
|||
|
Share of general and administrative |
$30,000 |
|||
|
Total |
475,000 |
|||
|
G-Art Contract |
410,000 |
|||
|
Net Difference |
65,500 |
Clarification: In the fact set, Custom Supplies are expected to sell for 60% of what the company paid for them. Assume (to make numbers cleaner), that this is 60% of their 'current' book value of $100,000 (derived from the fact set), not the original cost.
In: Accounting
Selling Web Site Services
Judy Reiser and Elyse Larsen are college friends who followed the dot.com boom together into a Web site services company that hired them right after they graduated in 1995. In 1998, the company imploded — it ran out of cash, failed to meet the needs of their customers, and lost key employees faster than they could be replaced. By 1999, the company closed and Judy and Elyse were thinking about graduate school, in part because job opportunities in technology industries were so few.
Three months after they lost their jobs, Judy and Elyse were having dinner at an inexpensive local restaurant. They shared news about former colleagues, other dot. com businesses that had closed, and talked about graduate school options. Elyse mentioned that she had run into one of her former clients, the owner of a custom- made furniture business, who complained that he was having trouble finding someone to host and update his Web site. He had asked Elyse if she was doing any work independently. Judy had a similar experience when her aunt, the manager of a medical practice, asked if Judy knew any people who could create a Web site. Judy knew of two people who could, but she didn’t admire their work enough to recommend them to her aunt.
At this point, Elyse had an epiphany: Their old company had failed because it spent too much money and was badly managed, not because the demand for Web site services was small. In fact, demand was growing faster than ever, as virtually every business realized it needed a Web site. Judy agreed and within 15 minutes, the two friends had consented to start their own company. They even had a name for it: Finesse Systems. The two friends knew the technology, where to rent inexpensive offices with high-speed connections, and who to hire as demand for their services grew. The only thing they didn’t know how to do was sign up clients.
The next week, Judy and Elyse met with several people who worked in sales and sales management to learn more about the selling process. After these meetings, they didn’t have the answers but they did have some specific questions.
Case Questions:
Margo Switches Coasts
For 17 years Margo Williams owned a jewelry store called Margo’s Diamond Mine near the naval base in San Diego. The large majority of her customers were sailors and their families and her most successful items were wedding rings, inexpensive necklaces, and low-priced brand-name watches. Because her customers were often stretching their finances to make what they felt was a major purchase, Margo’s store provided lay-away plans that allowed her clients to pay for items over time.
Margo’s mother, who lived in Ft. Lauderdale, recently became ill, so Margo decided it was time to close the store in San Diego and relocate both her home and business to Florida. She found a vacant store at a reasonable price in a small upscale strip mall in which the other businesses included an expensive dress shop, a gourmet food store, and a craft outlet. The surrounding area consisted mostly of high-end condominium developments which catered to retirees and people who spent about half the year in Florida.
Margo knows the jewelry business, including how to value items she takes on trade-ins, which suppliers are best to work with, and how to design and manage a store. Although she doesn’t know her new Florida market very well, some issues are clear:
• Advertising and promotion tend to be concentrated in newspapers and pennysavers.
Margo was not sure she wanted to use the Margo’s Diamond Mine name in this new market and she really did not know how to go about designing a marketing and promotion plan for the Florida market. To get started, Margo focused on two issues. First, she wanted a preliminary plan that would address—as best she could—the new marketing challenge she faces. Second, she wanted to research background information so she could refine her preliminary marketing plan.
Case exercise:
You are Margo. What are the new marketing challenges you face? Based on the material covered in this chapter, use the 4 Ps of marketing to create a preliminary marketing plan.
In: Operations Management
Case:
Forty years ago, Starbucks was a single store in Seattle’s Pike Place Market selling premium roasted coffee. Today, it is a global roaster and retailer of coffee with some 21,536 stores, 43 percent of which are in 63 countries outside the United States. China (1,716 stores), Canada (1,330 stores),
Japan (1,079 stores), and the United Kingdom (808 stores) are large markets internationally for Starbucks. Starbucks set out on its current course in the 1980s when the company’s director of marketing, Howard Schultz, came back from a trip to Italy enchanted with the Italian coffeehouse experience. Schultz, who later became CEO, persuaded the company’s owners to experiment with the coffeehouse format—and the Starbucks experience was born. The strategy was to sell the company’s own premium roasted coffee and freshly brewed espressostyle coffee beverages, along with a variety of pastries, coffee accessories, teas, and other products, in a tastefully designed coffeehouse setting. From the outset, the company focused on selling “a third place experience,” rather than just the coffee. The formula led to spectacular success in the United States, where Starbucks went from obscurity to one of the best-known brands in the country in a decade. Thanks to Starbucks, coffee stores became places for relaxation, chatting with friends, reading the newspaper, holding business meetings, or (more recently) browsing the web. In 1995, with 700 stores across the United States, Starbucks began exploring foreign market opportunities. The first target market was Japan. The company established a joint venture with a local retailer, Sazaby Inc. Each company held a 50 percent stake in the venture, Starbucks Coffee of Japan. Starbucks initially invested $10 million in this venture, its first foreign direct investment. The Starbucks format was then licensed to the venture, which was charged with taking over responsibility for growing Starbucks’ presence in Japan.
To make sure the Japanese operations replicated the “Starbucks experience” in North America, Starbucks transferred some employees to the Japanese operation. The licensing agreement required all Japanese store managers and employees to attend training classes similar to those given to U.S. employees. The agreement also required that stores adhere to the design parameters established in the United States. In 2001, the company introduced a stock option plan for all Japanese employees, making it the first company in Japan to do so. Skeptics doubted that Starbucks would be able to replicate its North American success overseas, but by June 2015, Starbucks had some 1,079 stores and a profitable business in Japan. After Japan, the company embarked on an aggressive foreign investment program. In 1998, it purchased Seattle Coffee, a British coffee chain with 60 retail stores, for $84 million. An American couple originally from Seattle had started Seattle Coffee with the intention of establishing a Starbucks-like chain in Britain. In the late 1990s, Starbucks opened stores in Taiwan, Singapore, Thailand, New Zealand, South Korea, Malaysia, and—most significantly— China. In Asia, Starbucks’ most common strategy was to license its format to a local operator in return for initial licensing fees and royalties on store revenues. As in Japan, Starbucks insisted on an intensive employee-training program and strict specifications regarding the format and layout of the store. By 2002, Starbucks was pursuing an aggressive expansion in mainland Europe. As its first entry point, Starbucks chose Switzerland. Drawing on its experience in Asia, the company entered into a joint venture with a Swiss company, Bon Appetit Group, Switzerland’s largest food service company. Bon Appetit was to hold a majority stake in the venture, and Starbucks would license its format to the Swiss company using a similar agreement to those it had used successfully in Asia. This was followed by a joint venture in other countries. The United Kingdom leads the charge in Europe with 808 Starbucks stores. By 2014, Starbucks emphasized the rapid growth of its operations in China, where it had 1,716 stores and planned to roll out another 500 in three years. The success of Starbucks in China has been attributed to a smart partnering strategy. China is not one homogeneous market; the culture of northern China is very different from that of the east, and consumer spending power inland is not on par with that of the big coastal cities. To deal with this complexity, Starbucks entered into three different joint ventures: in the north with Beijong Mei Da coffee, in the east with Taiwan-based UniPresident, and in the south with Hong Kong-based Maxim’s Caterers. Each partner brought different strengths and local expertise that helped the company gain insights into the tastes and preferences of local Chinese customers, and to adapt accordingly. Starbucks now believes that China will become its second-largest market after the United States by 2020.
Question:
2. Many would argue that Starbucks coffee is expensive, and yet customers get “value” for their money. How do you think Starbucks has been able to transfer this business model and value proposition to international markets?
In: Economics
Evaluate the capital budgeting project using the traditional Net Present Value (NPV) approach and the Internal Rate of Return (IRR) criterion and present findings.
Find if this new proposal will turn out to be a good investment for his company.
Capital budgeting and investment proposal – a new product line of branded shirts that the committee was considering for launch. What would be the basis for calculating the after-tax operating cash flows for the capital project? How would you arrive at the depreciation and working capital requirements for computing the NPV? What would be the basis for calculating the terminal year cash flows?
Indian Retail Market The Indian retail market is at the cusp of a sweet spot driven by strong GDP (Gross Domestic Product) growth, benign inflation, and rising per capita income and purchasing power of consumers. Currently, the retail industry accounts for more than ten percent of the Indian Gross Domestic Product and approximately eight percent of employment. The industry is expected to nearly double, from US$ 600 billion in 2015 to US$ 1 trillion, by 2020 driven by income growth, urbanization, and attitudinal shifts (Indian Terrain Annual Report, 2015–16). It has been estimated that, by 2030, the Indian apparel market, in particular, is expected to grow at a CAGR (compounded annual growth rate) of approximately 10–12%, backed by increasing affordability on account of an increase in disposable incomes, increase in aspirations, and a shift from unbranded to branded products by the burgeoning middle class. This trend is likely to be further accentuated by the rise of e-commerce companies that enable shopping from anywhere, thereby leading to increased penetration in small cities and towns (Indian Terrain Annual Report, 2015–16).
Company Background: Case
Bhatia Textiles is a small, privately-owned clothing company based in New Delhi, India. It was founded in 1995 by Harish Bhatia, a retired executive. Since then, the company had grown steadily by catering to middle to low income consumers in the Delhi-National Capital Region (NCR). The company recorded stellar growth of 50% in its sales during the last financial year of 2015–16. With a healthy operating margin ratio and low leverage levels, the company had been able to grow its profits at a CAGR of 25% during the last 10 years. With a good brand name and healthy financial metrics, the company was now looking to expand its footprint to new product lines catering to middle to high income customers. Project Investment Proposal Details The project is estimated to be of 10 years duration. It involves setting up new machinery with an estimated cost of as much as INR 500 million, including installation. This amount could be depreciated using the straight-line method (SLM) over a period of 10 years with a resale value of INR 15 million. The project would require an initial working capital of INR 20 million with cumulative investment in net working capital to be maintained at 10% of each year’s projected revenue. With the planned new capacity, the company would be able to produce 240,000 pieces of shirts each year for the next 10 years. In terms of pricing, each shirt can initially be sold at INR 1,300 apiece, which takes into account the target segment and competitor pricing.
The project proposal incorporates an annual increase of 3% in the price of the shirt to compensate for the inflationary impact. With regards to the raw material costs and other expenses, the project estimated the following details: • Raw material cost for manufacturing shirts at INR 400 per shirt, slated to rise by 5% per annum on account of inflation. • Other direct manufacturing costs at INR 125 per shirt with an annual increase of 5% per annum on account of inflation. • Selling, general, and administrative expenses (including employee expenses) at INR 35 million per annum, expected to increase by 10% each year. • Depreciation expense on the basis of SLM. • Tax rate was assumed to be 25%. Funding For funding of the expansion project, the promoters agreed to infuse 50% in the form of equity with the rest (50%) being financed from issue of new debt. Based on the current credit position and market scenario, new debt can be raised by the company at 12% per annum. Cost of equity was assumed to be 15%. The requisite discounting rate or weighted average cost of capital (WACC) for NPV and IRR calculations can now be calculated with the help of the above assumptions.
Although the project proposal estimates maximum annual production of 240,000 shirts, find the capital budgeting analysis under two demand scenarios: Optimistic and Expected. The likely annual demand estimated under each scenario is as follows:
Scenario Annual demand
Optimistic 240,000 Shirts
Expected 200,000 Shirts
Question 1
On the basis of the financial information given in the case, calculate the after-tax operating cash flows, NPV, and IRR under the Optimistic and Expected scenarios. Clearly specify the calculations required for the same.
In: Finance
please no handwriting
Learning Outcome:
Understand the issues involved with transfer pricing in multidivisional companies (question 1)
Provide an appreciation of logistics activities and their relationship to supply chain management, other business functions and enterprises. (Question 2)
ECR in the UK
Dutchman Paul Polman, now CEO of Unilever, did a stint as General Manager of Procter & Gamble UK and Eire from 1995 to 1999. While admiring the UK’s advanced retailing systems, he saw opportunities for all four of the ‘pillars of ECR’ – range, new items, promotions and replenishment. The following is extracted from the text of a speech he made to the Institute of Grocery Distribution.
Range
The average store now holds 35 per cent more than five years ago, yet a typical consumer buys just 18 items on a trip. A quarter of these skus[1] sell less than six units a week!
The number of skus offered by manufacturers and stores has become too large and complex. My company is equally guilty in this area. No question, we make too many skus. I can assure you we are working on it. Actually, our overall sku count in laundry is already down 20 per cent compared to this time last year. What’s more, business is up.
Clearly, we have an opportunity to rationalise our ranges. As long as we do this in an ECR way – focusing on what consumers want – we will all win. The consumer will see a clearer range. Retailers and manufacturers will carry less inventory and less complexity.
The result will be cost savings across the whole supply chain and stronger margins.
New items
There were 16,000 new skus last year. Yet 80 per cent lasted less than a year. You don’t need to be an accountant to imagine the costs associated with this kind of activity. And look how this has changed. Since 1975, the number of new sku introductions has increased eightfold. Yet their life expectancy has shrunk from around five years in 1975 to about nine months now. We can hardly call this progress.
Promotions
In promotions it’s the same story. Take laundry detergents. This is a fairly stable market. Yet we’re spending 50 per cent more on promotions than two years ago, with Consumers buying nearly 30 per cent more of their volume on promotions. This not only creates an inefficient supply chain, or in some cases poor in-store availability, but, more importantly, has reduced the value of the category and likely the retailers’ profit. We are all aware of the inefficiencies promotions cause in the system, such as problems in production, inventory and in-store availability. They all create extra costs, which ultimately have to be recouped in price. But there’s a higher cost. As promotions are increasing, they are decreasing customer loyalty to both stores and brands by 16 per cent during the period of the promotion. We commissioned a report by Professor Barwise of the London Business School. He called it ‘Taming the Multi-buy
Dragon’. The report shows us that over 70 per cent of laundry promotional investment goes on multi-buys. The level of investment on multi-buys has increased by 60 per cent over the last three years. There’s been a 50 per cent increase behind brands and a doubling of investment behind own labels. Contrary to what we thought, most of this volume is not going to a broad base of households. It is going to a small minority.
Seventy-one per cent of all multi-buy volume is bought by just 14 per cent of households. Just 2 per cent of multi-buy volume goes to 55 per cent of households.
We really are focusing our spending on influencing and rewarding a very small minority of people indeed.
Replenishment
Based on the escalating activity I’ve just [referred to], costs are unnecessarily high. There are huge cost savings also here, up to 6 per cent, by removing the non-value-added skus and inefficient new brand and promotional activity.
Questions
1 - Cutting down on range, new items and promotions is presumably going to lead to ‘everyday low prices’. Discuss the implications to the trade-off between choice and price. (2 points)
2- Procter & Gamble’s major laundry brand in the US is Tide. This is marketed in some 60 pack presentations, some of which have less than 0.1 per cent share. The proliferation of these pack presentations is considered to have been instrumental in increasing Tide’s market share from 20 to 40 per cent of the US market in recent years. Clearly, this is a major issue within P&G.
What are the logistics pros and cons of sku proliferation? (2points)
In: Operations Management
please no handwriting
Learning Outcome:
Understand the issues involved with transfer pricing in multidivisional companies (question 1)
Provide an appreciation of logistics activities and their relationship to supply chain management, other business functions and enterprises. (Question 2)
CASE STUDY
ECR in the UK
Dutchman Paul Polman, now CEO of Unilever, did a stint as General Manager of Procter & Gamble UK and Eire from 1995 to 1999. While admiring the UK’s advanced retailing systems, he saw opportunities for all four of the ‘pillars of ECR’ – range, new items, promotions and replenishment. The following is extracted from the text of a speech he made to the Institute of Grocery Distribution.
Range
The average store now holds 35 per cent more than five years ago, yet a typical consumer buys just 18 items on a trip. A quarter of these skus[1] sell less than six units a week!
The number of skus offered by manufacturers and stores has become too large and complex. My company is equally guilty in this area. No question, we make too many skus. I can assure you we are working on it. Actually, our overall sku count in laundry is already down 20 per cent compared to this time last year. What’s more, business is up.
Clearly, we have an opportunity to rationalise our ranges. As long as we do this in an ECR way – focusing on what consumers want – we will all win. The consumer will see a clearer range. Retailers and manufacturers will carry less inventory and less complexity.
The result will be cost savings across the whole supply chain and stronger margins.
New items
There were 16,000 new skus last year. Yet 80 per cent lasted less than a year. You don’t need to be an accountant to imagine the costs associated with this kind of activity. And look how this has changed. Since 1975, the number of new sku introductions has increased eightfold. Yet their life expectancy has shrunk from around five years in 1975 to about nine months now. We can hardly call this progress.
Promotions
In promotions it’s the same story. Take laundry detergents. This is a fairly stable market. Yet we’re spending 50 per cent more on promotions than two years ago, with Consumers buying nearly 30 per cent more of their volume on promotions. This not only creates an inefficient supply chain, or in some cases poor in-store availability, but, more importantly, has reduced the value of the category and likely the retailers’ profit. We are all aware of the inefficiencies promotions cause in the system, such as problems in production, inventory and in-store availability. They all create extra costs, which ultimately have to be recouped in price. But there’s a higher cost. As promotions are increasing, they are decreasing customer loyalty to both stores and brands by 16 per cent during the period of the promotion. We commissioned a report by Professor Barwise of the London Business School. He called it ‘Taming the Multi-buy
Dragon’. The report shows us that over 70 per cent of laundry promotional investment goes on multi-buys. The level of investment on multi-buys has increased by 60 per cent over the last three years. There’s been a 50 per cent increase behind brands and a doubling of investment behind own labels. Contrary to what we thought, most of this volume is not going to a broad base of households. It is going to a small minority.
Seventy-one per cent of all multi-buy volume is bought by just 14 per cent of households. Just 2 per cent of multi-buy volume goes to 55 per cent of households.
We really are focusing our spending on influencing and rewarding a very small minority of people indeed.
Replenishment
Based on the escalating activity I’ve just [referred to], costs are unnecessarily high. There are huge cost savings also here, up to 6 per cent, by removing the non-value-added skus and inefficient new brand and promotional activity.
Questions
1 - Cutting down on range, new items and promotions is presumably going to lead to ‘everyday low prices’. Discuss the implications to the trade-off between choice and price. (2 points)
2- Procter & Gamble’s major laundry brand in the US is Tide. This is marketed in some 60 pack presentations, some of which have less than 0.1 per cent share. The proliferation of these pack presentations is considered to have been instrumental in increasing Tide’s market share from 20 to 40 per cent of the US market in recent years. Clearly, this is a major issue within P&G.
What are the logistics pros and cons of sku proliferation? (2points)
please long answer
In: Operations Management
You've been hired by Water Wonders to write a C++ console application that analyzes lake level data. MichiganHuronLakeLevels.txt. Place the input file in a folder where your development tool can locate it (on Visual Studio, in folder \). The input file may be placed in any folder but a path must be specified to locate it.
MichiganHuronLakeLevels.txt Down below:
Lake Michigan and Lake Huron - Average lake levels - 1860-2015
Year Average level (meters)
1860 177.3351667
1861 177.3318333
1862 177.316
1863 177.1796667
1864 176.9955833
1865 176.90525
1866 176.80575
1867 176.9365833
1868 176.7891667
1869 176.8250833
1870 177.1
1871 177.0769167
1872 176.7318333
1873 176.9188333
1874 177.0413333
1875 176.9683333
1876 177.2855833
1877 177.1971667
1878 177.1183333
1879 176.85325
1880 176.90425
1881 177.0205
1882 177.1250833
1883 177.2096667
1884 177.2734167
1885 177.3208333
1886 177.3893333
1887 177.1890833
1888 176.9931667
1889 176.8393333
1890 176.788
1891 176.6149167
1892 176.564
1893 176.6204167
1894 176.6811667
1895 176.4201667
1896 176.3256667
1897 176.5094167
1898 176.5564167
1898 176.5595
1900 176.5626667
1901 176.64175
1902 176.5305833
1903 176.5748333
1904 176.7460909
1905 176.7561667
1906 176.7635
1907 176.7844167
1908 176.7670909
1909 176.5988333
1910 176.5025
1911 176.3356667
1912 176.4768333
1913 176.67025
1914 176.5297273
1915 176.3535833
1916 176.5715833
1917 176.7980833
1918 176.8866667
1919 176.745
1920 176.625
1921 176.4883333
1922 176.445
1923 176.2641667
1924 176.1866667
1925 175.9191667
1926 175.885
1927 176.1483333
1928 176.4433333
1929 176.8958333
1930 176.6508333
1931 176.1183333
1932 175.9408333
1933 175.8675
1934 175.7666667
1935 175.8908333
1936 175.9391667
1937 175.9225
1938 176.1408333
1939 176.2691667
1940 176.1416667
1941 176.1216667
1942 176.3341667
1943 176.6266667
1944 176.5966667
1945 176.57
1946 176.6016667
1947 176.5666667
1948 176.5308333
1949 176.2108333
1950 176.2608333
1951 176.7358333
1952 177.085
1953 176.9333333
1954 176.8291667
1955 176.7225
1956 176.44
1957 176.2633333
1958 176.0675
1959 176.0058333
1960 176.4775
1961 176.3766667
1962 176.2225
1963 175.9225
1964 175.6825
1965 175.9158333
1966 176.1608333
1967 176.3008333
1968 176.4466667
1969 176.6958333
1970 176.6783333
1971 176.805
1972 176.8883333
1973 177.1233333
1974 177.0933333
1975 176.9733333
1976 176.8991667
1977 176.505
1978 176.5908333
1979 176.7941667
1980 176.8033333
1981 176.6983333
1982 176.5983333
1983 176.8333333
1984 176.895
1985 177.1266667
1986 177.2925
1987 176.97
1988 176.5641667
1989 176.4008333
1990 176.35
1991 176.4691667
1992 176.4791667
1993 176.6958333
1994 176.6783333
1995 176.5275
1996 176.6541667
1997 176.9841667
1998 176.7166667
1999 176.2358333
2000 175.9783333
2001 175.9508333
2002 176.1183333
2003 175.8916667
2004 176.1108333
2005 176.09
2006 176.0158333
2007 175.9433333
2008 176.005
2009 176.2583333
2010 176.1108333
2011 176.0366
2012 175.9158
2013 175.9
2014 176.3016667
2015 176.59
Within the app, attempt to open the input file and output file MichiganHuronLakeLevelsHighAndLow.txt. If the input file didn't open, print an error message. If the output file didn't open, print an error message. Read the input file by scanning past the two header rows. Each detail row in the input file contains two fields (year, lake level). Read one token at a time from the input file. See sample Canvas app Text file input – one token per read. Determine the maximum, minimum, and average lake levels. One technique to accomplish this is to use a max variable that starts very small and a min variable that starts very large. After all lines of the input file have been read, use formatted output manipulators (setw, left/right) to print the following rows:
● Column headers.
● Max values.
● Min values.
● Average value.
And columns:
● A left-justified label.
● A right-justified year.
● A right-justified level.
Then write the same information to output file MichiganHuronLakeLevelsHighAndLow.txt. Insure that your code is commented! Provide a complete header comment and body comments. Define constants for the input and output file names and column widths. Format any real numbers to four decimal places. The output should look like this:
Welcome to Wonder Waters
------------------------
Reading lines from file 'MichiganHuronLakeLevels.txt' ...
Writing lines to file 'MichiganHuronLakeLevelsHighAndLow.txt' ...
Year Level (meters)
Max level: … …
Min level: … …
Average level: …
158 line(s) read from file 'MichiganHuronLakeLevels.txt'.
4 line(s) written to file 'MichiganHuronLakeLevelsHighAndLow.txt'.
End of Wonder Waters
In: Computer Science
Case:
Forty years ago, Starbucks was a single store in Seattle’s Pike Place Market selling premium roasted coffee. Today, it is a global roaster and retailer of coffee with some 21,536 stores, 43 percent of which are in 63 countries outside the United States. China (1,716 stores), Canada (1,330 stores),
Japan (1,079 stores), and the United Kingdom (808 stores) are large markets internationally for Starbucks. Starbucks set out on its current course in the 1980s when the company’s director of marketing, Howard Schultz, came back from a trip to Italy enchanted with the Italian coffeehouse experience. Schultz, who later became CEO, persuaded the company’s owners to experiment with the coffeehouse format—and the Starbucks experience was born. The strategy was to sell the company’s own premium roasted coffee and freshly brewed espressostyle coffee beverages, along with a variety of pastries, coffee accessories, teas, and other products, in a tastefully designed coffeehouse setting. From the outset, the company focused on selling “a third place experience,” rather than just the coffee. The formula led to spectacular success in the United States, where Starbucks went from obscurity to one of the best-known brands in the country in a decade. Thanks to Starbucks, coffee stores became places for relaxation, chatting with friends, reading the newspaper, holding business meetings, or (more recently) browsing the web. In 1995, with 700 stores across the United States, Starbucks began exploring foreign market opportunities. The first target market was Japan. The company established a joint venture with a local retailer, Sazaby Inc. Each company held a 50 percent stake in the venture, Starbucks Coffee of Japan. Starbucks initially invested $10 million in this venture, its first foreign direct investment. The Starbucks format was then licensed to the venture, which was charged with taking over responsibility for growing Starbucks’ presence in Japan.
To make sure the Japanese operations replicated the “Starbucks experience” in North America, Starbucks transferred some employees to the Japanese operation. The licensing agreement required all Japanese store managers and employees to attend training classes similar to those given to U.S. employees. The agreement also required that stores adhere to the design parameters established in the United States. In 2001, the company introduced a stock option plan for all Japanese employees, making it the first company in Japan to do so. Skeptics doubted that Starbucks would be able to replicate its North American success overseas, but by June 2015, Starbucks had some 1,079 stores and a profitable business in Japan. After Japan, the company embarked on an aggressive foreign investment program. In 1998, it purchased Seattle Coffee, a British coffee chain with 60 retail stores, for $84 million. An American couple originally from Seattle had started Seattle Coffee with the intention of establishing a Starbucks-like chain in Britain. In the late 1990s, Starbucks opened stores in Taiwan, Singapore, Thailand, New Zealand, South Korea, Malaysia, and—most significantly— China. In Asia, Starbucks’ most common strategy was to license its format to a local operator in return for initial licensing fees and royalties on store revenues. As in Japan, Starbucks insisted on an intensive employee-training program and strict specifications regarding the format and layout of the store. By 2002, Starbucks was pursuing an aggressive expansion in mainland Europe. As its first entry point, Starbucks chose Switzerland. Drawing on its experience in Asia, the company entered into a joint venture with a Swiss company, Bon Appetit Group, Switzerland’s largest food service company. Bon Appetit was to hold a majority stake in the venture, and Starbucks would license its format to the Swiss company using a similar agreement to those it had used successfully in Asia. This was followed by a joint venture in other countries. The United Kingdom leads the charge in Europe with 808 Starbucks stores. By 2014, Starbucks emphasized the rapid growth of its operations in China, where it had 1,716 stores and planned to roll out another 500 in three years. The success of Starbucks in China has been attributed to a smart partnering strategy. China is not one homogeneous market; the culture of northern China is very different from that of the east, and consumer spending power inland is not on par with that of the big coastal cities. To deal with this complexity, Starbucks entered into three different joint ventures: in the north with Beijong Mei Da coffee, in the east with Taiwan-based UniPresident, and in the south with Hong Kong-based Maxim’s Caterers. Each partner brought different strengths and local expertise that helped the company gain insights into the tastes and preferences of local Chinese customers, and to adapt accordingly. Starbucks now believes that China will become its second-largest market after the United States by 2020.
Question:
1. Starbucks prefers a combination approach to foreign market entry: the use of joint ventures and licensing. Do you agree with this approach? Why or why not?
In: Operations Management
please no handwriting
Learning Outcome:
Understand the issues involved with transfer pricing in multidivisional companies (question 1)
Provide an appreciation of logistics activities and their relationship to supply chain management, other business functions and enterprises. (Question 2)
CASE STUDY
ECR in the UK
Dutchman Paul Polman, now CEO of Unilever, did a stint as General Manager of Procter & Gamble UK and Eire from 1995 to 1999. While admiring the UK’s advanced retailing systems, he saw opportunities for all four of the ‘pillars of ECR’ – range, new items, promotions and replenishment. The following is extracted from the text of a speech he made to the Institute of Grocery Distribution.
Range
The average store now holds 35 per cent more than five years ago, yet a typical consumer buys just 18 items on a trip. A quarter of these skus[1] sell less than six units a week!
The number of skus offered by manufacturers and stores has become too large and complex. My company is equally guilty in this area. No question, we make too many skus. I can assure you we are working on it. Actually, our overall sku count in laundry is already down 20 per cent compared to this time last year. What’s more, business is up.
Clearly, we have an opportunity to rationalise our ranges. As long as we do this in an ECR way – focusing on what consumers want – we will all win. The consumer will see a clearer range. Retailers and manufacturers will carry less inventory and less complexity.
The result will be cost savings across the whole supply chain and stronger margins.
New items
There were 16,000 new skus last year. Yet 80 per cent lasted less than a year. You don’t need to be an accountant to imagine the costs associated with this kind of activity. And look how this has changed. Since 1975, the number of new sku introductions has increased eightfold. Yet their life expectancy has shrunk from around five years in 1975 to about nine months now. We can hardly call this progress.
Promotions
In promotions it’s the same story. Take laundry detergents. This is a fairly stable market. Yet we’re spending 50 per cent more on promotions than two years ago, with Consumers buying nearly 30 per cent more of their volume on promotions. This not only creates an inefficient supply chain, or in some cases poor in-store availability, but, more importantly, has reduced the value of the category and likely the retailers’ profit. We are all aware of the inefficiencies promotions cause in the system, such as problems in production, inventory and in-store availability. They all create extra costs, which ultimately have to be recouped in price. But there’s a higher cost. As promotions are increasing, they are decreasing customer loyalty to both stores and brands by 16 per cent during the period of the promotion. We commissioned a report by Professor Barwise of the London Business School. He called it ‘Taming the Multi-buy
Dragon’. The report shows us that over 70 per cent of laundry promotional investment goes on multi-buys. The level of investment on multi-buys has increased by 60 per cent over the last three years. There’s been a 50 per cent increase behind brands and a doubling of investment behind own labels. Contrary to what we thought, most of this volume is not going to a broad base of households. It is going to a small minority.
Seventy-one per cent of all multi-buy volume is bought by just 14 per cent of households. Just 2 per cent of multi-buy volume goes to 55 per cent of households.
We really are focusing our spending on influencing and rewarding a very small minority of people indeed.
Replenishment
Based on the escalating activity I’ve just [referred to], costs are unnecessarily high. There are huge cost savings also here, up to 6 per cent, by removing the non-value-added skus and inefficient new brand and promotional activity.
Questions
1 - Cutting down on range, new items and promotions is presumably going to lead to ‘everyday low prices’. Discuss the implications to the trade-off between choice and price. (2 points)
2- Procter & Gamble’s major laundry brand in the US is Tide. This is marketed in some 60 pack presentations, some of which have less than 0.1 per cent share. The proliferation of these pack presentations is considered to have been instrumental in increasing Tide’s market share from 20 to 40 per cent of the US market in recent years. Clearly, this is a major issue within P&G.
What are the logistics pros and cons of sku proliferation? (2points)
please long answer
In: Operations Management
You've been hired by Water Wonders to write a C++ console application that analyzes lake level data. Place the input file in a folder where your development tool can locate it (on Visual Studio, in folder <project-name>\<project-name>). The input file may be placed in any folder but a path must be specified to locate it. The input file has 158 lines and looks like this:
Lake Michigan and Lake Huron - Average lake levels - 1860-2015
Year Average level (meters)
1860 177.3351667
1861 177.3318333
…
2014 176.3016667
2015 176.59
Within the app, attempt to open the input file and output file MichiganHuronLakeLevelsHighAndLow.txt. If the input file didn't open, print an error message. If the output file didn't open, print an error message. Read the input file by scanning past the two header rows. Each detail row in the input file contains two fields (year, lake level). Read one token at a time from the input file. See sample Canvas app Text file input – one token per read. Determine the maximum, minimum, and average lake levels. One technique to accomplish this is to use a max variable that starts very small and a min variable that starts very large. After all lines of the input file have been read, use formatted output manipulators (setw, left/right) to print the following rows:
● Column headers.
● Max values.
● Min values.
● Average value.
And columns:
● A left-justified label.
● A right-justified year.
● A right-justified level.
Then write the same information to output file MichiganHuronLakeLevelsHighAndLow.txt. Insure that your code is commented! Provide a complete header comment and body comments. Define constants for the input and output file names and column widths. Format any real numbers to four decimal places.
Lake Michigan and Lake Huron - Average lake levels -
1860-2015
Year Average level (meters)
1860 177.3351667
1861 177.3318333
1862 177.316
1863 177.1796667
1864 176.9955833
1865 176.90525
1866 176.80575
1867 176.9365833
1868 176.7891667
1869 176.8250833
1870 177.1
1871 177.0769167
1872 176.7318333
1873 176.9188333
1874 177.0413333
1875 176.9683333
1876 177.2855833
1877 177.1971667
1878 177.1183333
1879 176.85325
1880 176.90425
1881 177.0205
1882 177.1250833
1883 177.2096667
1884 177.2734167
1885 177.3208333
1886 177.3893333
1887 177.1890833
1888 176.9931667
1889 176.8393333
1890 176.788
1891 176.6149167
1892 176.564
1893 176.6204167
1894 176.6811667
1895 176.4201667
1896 176.3256667
1897 176.5094167
1898 176.5564167
1898 176.5595
1900 176.5626667
1901 176.64175
1902 176.5305833
1903 176.5748333
1904 176.7460909
1905 176.7561667
1906 176.7635
1907 176.7844167
1908 176.7670909
1909 176.5988333
1910 176.5025
1911 176.3356667
1912 176.4768333
1913 176.67025
1914 176.5297273
1915 176.3535833
1916 176.5715833
1917 176.7980833
1918 176.8866667
1919 176.745
1920 176.625
1921 176.4883333
1922 176.445
1923 176.2641667
1924 176.1866667
1925 175.9191667
1926 175.885
1927 176.1483333
1928 176.4433333
1929 176.8958333
1930 176.6508333
1931 176.1183333
1932 175.9408333
1933 175.8675
1934 175.7666667
1935 175.8908333
1936 175.9391667
1937 175.9225
1938 176.1408333
1939 176.2691667
1940 176.1416667
1941 176.1216667
1942 176.3341667
1943 176.6266667
1944 176.5966667
1945 176.57
1946 176.6016667
1947 176.5666667
1948 176.5308333
1949 176.2108333
1950 176.2608333
1951 176.7358333
1952 177.085
1953 176.9333333
1954 176.8291667
1955 176.7225
1956 176.44
1957 176.2633333
1958 176.0675
1959 176.0058333
1960 176.4775
1961 176.3766667
1962 176.2225
1963 175.9225
1964 175.6825
1965 175.9158333
1966 176.1608333
1967 176.3008333
1968 176.4466667
1969 176.6958333
1970 176.6783333
1971 176.805
1972 176.8883333
1973 177.1233333
1974 177.0933333
1975 176.9733333
1976 176.8991667
1977 176.505
1978 176.5908333
1979 176.7941667
1980 176.8033333
1981 176.6983333
1982 176.5983333
1983 176.8333333
1984 176.895
1985 177.1266667
1986 177.2925
1987 176.97
1988 176.5641667
1989 176.4008333
1990 176.35
1991 176.4691667
1992 176.4791667
1993 176.6958333
1994 176.6783333
1995 176.5275
1996 176.6541667
1997 176.9841667
1998 176.7166667
1999 176.2358333
2000 175.9783333
2001 175.9508333
2002 176.1183333
2003 175.8916667
2004 176.1108333
2005 176.09
2006 176.0158333
2007 175.9433333
2008 176.005
2009 176.2583333
2010 176.1108333
2011 176.0366
2012 175.9158
2013 175.9
2014 176.3016667
2015 176.59
In: Computer Science