The BCG Matrix is a business model or portfolio planning tool that was developed by Bruce Henderson of the Boston Consulting Group in the 1970's. The main purpose of the BCG Matrix is therefore to make investment decisions on a corporate level?.

If the number of competitors in Example 11.1 doubles, how does the optimal bid change?

Sometimes curvature in a scatterplot can be fit adequately (especially to the naked eye) by several trend lines. We discussed the exponential trend line, and the power trend line is discussed in the previous problem. Still another fairly simple trend line is the parabola, a polynomial of order 2 (also called a quadratic). For the demand-price data in the file P13_10.xlsx, fit all three of these types of trend lines to the data, and calculate the MAPE for each. Which provides the best fit? (Hint: Note that a polynomial of order 2 is still another of Excels Trend line options.)

When you use a RISKSIMTABLE function for a decision variable, such as the order quantity in the Walton model, explain how this provides a fair comparison across the different values tested.

Suppose you currently have a portfolio of three stocks, A, B, and C. You own 500 shares of A, 300 of B, and 1000 of C. The current share prices are 42.76, 81.33, and, 58.22, respectively. You plan to hold this portfolio for at least a year. During the coming year, economists have predicted that the national economy will be awful, stable, or great with probabilities 0.2, 0.5, and 0.3. Given the state of the economy, the returns (one-year percentage changes) of the three stocks are independent and normally distributed. However, the means and standard deviations of these returns depend on the state of the economy, as indicated in the file P11_23.xlsx. a. Use @RISK to simulate the value of the portfolio and the portfolio return in the next year. How likely is it that you will have a negative return? How likely is it that you will have a return of at least 25%? b. Suppose you had a crystal ball where you could predict the state of the economy with certainty. The stock returns would still be uncertain, but you would know whether your means and standard deviations come from row 6, 7, or 8 of the P11_23.xlsx file. If you learn, with certainty, that the economy is going to be great in the next year, run the appropriate simulation to answer the same questions as in part a. Repeat this if you learn that the economy is going to be awful. How do these results compare with those in part a?

The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Can you guess the results of a sensitivity analysis on the initial inventory in the Pigskin model? See if your guess is correct by using SolverTable and allowing the initial inventory to vary from 0 to 10,000 in increments of 1000. Keep track of the values in the decision variable cells and the objective cell.

The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Modify the Pigskin model so that there are eight months in the planning horizon. You can make up reasonable values for any extra required data. Dont forget to modify range names. Then modify the model again so that there are only four months in the planning horizon. Do either of these modifications change the optima] production quantity in month 1?

The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. As indicated by the algebraic formulation of the Pigskin model, there is no real need to calculate inventory on hand after production and constrain it to be greater than or equal to demand. An alternative is to calculate ending inventory directly and constrain it to be nonnegative. Modify the current spreadsheet model to do this. (Delete rows 16 and 17, and calculate ending inventory appropriately. Then add an explicit non-negativity constraint on ending inventory.)

Seas Beginning sells clothing by mail order. An important question is when to strike a customer from the companys mailing list. At present, the company strikes a customer from its mailing list if a customer fails to order from six consecutive catalogs. The company wants to know whether striking a customer from its list after a customer fails to order from four consecutive catalogs results in a higher profit per customer. The following data are available: If a customer placed an order the last time she received a catalog, then there is a 20% chance she will order from the next catalog. If a customer last placed an order one catalog ago, there is a 16% chance she will order from the next catalog she receives. If a customer last placed an order two catalogs ago, there is a 12% chance she will order from the next catalog she receives. If a customer last placed an order three catalogs ago, there is an 8% chance she will order from the next catalog she receives. If a customer last placed an order four catalogs ago, there is a 4% chance she will order from the next catalog she receives. If a customer last placed an order five catalogs ago, there is a 2% chance she will order from the next catalog she receives. It costs 2 to send a catalog, and the average profit per order is 30. Assume a customer has just placed an order. To maximize expected profit per customer, would Seas Beginning make more money canceling such a customer after six nonorders or four nonorders?

Located in the picturesque Berkshire Mountains of Western Massachusetts, Ski Butternut has been a family-owned, family-oriented ski destination for more than 50 years. The resort includes 22 trails for downhill skiing and snowboarding, two terrain parks for riding, and a dedicated area for snow tubing. Although Ski Butternut hosts some non-ski events during summer and fall, its business goes into high gear when snowy weather arrives, bringing skiers and riders from across Massachusetts, Connecticut, New York, and New Jersey. Matt Sawyer, Ski Butternuts director of marketing, says the primary target market has always been families with young children who are seeking affordable skiing. Everything from the snack-bar menus to the ski-shop merchandise is presented with families in mind. So that parents can have fun in the snow without worry, the resort has a Childrens Center for children who are too young to ski or have no interest. Fifth-graders are invited to ski for free when accompanied by an adult who buys an adult lift ticket. The resort also created two terrain parks for young snowboarders who were clamoring for a more exciting riding experience. Without the terrain parks, Sawyer says, these boarders would have asked their parents to take them to competing mountains in Vermont. Ski Butternuts research shows that first-timers are a particularly important segment, because they tend to have a strong allegiance to the resort where they learn to ski. First-timers typically visit the resort seven times before seeking out more challenging mountains. As a result, Ski Butternut has made teaching first-timers to ski or snowboard one of its specialties. For this market, the resort bundles ski or board rentals, lift tickets, and also offers a wide range of individual and group lessons for all ages and abilities at a value price. Because Ski Butternut has trails for different skill levels, beginners can challenge themselves by changing trails within the resort once they feel confident. Ski Butternut also targets seniors and college students. Knowing that weekends are the busiest period, the resort offers special midweek prices to attract seniors who have free time to ski on weekdays. College students are particularly value-conscious, and they often travel to ski resorts as a group. As a result, Ski Butternut offers weekend and holiday discounts to bring in large numbers of students who would otherwise ski elsewhere. Thanks to Facebook, Twitter, and other social media, students quickly spread the word about special pricing, which enhances Ski Butternuts ability to reach this key segment. In addition, the resort highlights discount pricing for families when targeting specific segments, such as scout troops, military personnel, emergency services personnel, and members of local ski clubs. Another segment Ski Butternut has selected for marketing attention is ski racers. The resort features professional coaching, lessons, and programs for ski racers in the age group of 8 to 20. Sawyer notes that these ski racers are extremely dedicated to training, which means theyre on the slopes as often as possible, a positive for the resorts attendance and revenue. To stay in touch with racers, Ski Butternut has a special website and a dedicated Facebook page. Sawyer conducts up to 1,200 customer surveys every year to better understand who his customers are and what they need. He also compares the results with skiers who visit mountains of a similar size in other areas. Digging deeper, he analyzes data drawn from the ski shops rental business to build a detailed picture of customers demographics, abilities, and preferences. Based on this research, he knows that the typical family at Ski Butternut consists of two children under age 18 who ski or ride, and at least one parent who skis. Because they can obtain so much information from and about their customers, Sawyer and his team are able to make better decisions about the marketing mix for each segment. By better matching the media with the audience, they get a better response from advertising, e-mail messages, and other marketing communications. As one example, they found that 15 percent of the visitors to Ski Butternuts website were using a smartphone to access the site. Sawyer has now created a special version of the site specifically for mobile use and created a text-message contest to engage skiers who have smartphones.16 Of the four categories of variables, which one seems to be the most central to Ski Butternuts segmentation strategy, and why?