Case studies

At the core of this case is a distribution, or sourcing, problem that can be modeled and solved using linear programming (LP). There are also issues of whether to build (a) new plant(s)––and if so, what the capacity should be––and whether to expand or close one or more of the existing plants. These latter issues can be analyzed using a 0/1 LP facility-location model. Alternatively, because the number of options is limited, they can be analyzed using the straight LP model of the distribution problem as a tool to facilitate analysis.

George Lasiter sells special-events T-shirts and must decide how many to order for an upcoming concert. He has high, medium, and low estimates of both concert attendance and the percentage of attendees who will want a shirt. In addition, he has assessed the relative likelihoods of each estimate. The case can be used to introduce or reinforce the fundamental issues surrounding decision making under uncertainty.

Julia Brown, toy buyer for the Hightower Department Stores, has to decide which of three imported stuffed animals will be offered for sale by the 16 Hightower stores during the approaching Christmas shopping season. The case is appropriately used as an introduction to the concepts of least squares and regression analysis. A linear relationship between realized and test-market sales can be used to forecast the sales potential of the three proposed animals, and an explicit treatment of the uncertainty in this forecast is necessary in order to decide how many of each adopted animal to order.

The diamond industry has been subject to significant change. There is increased competition from low-wage countries such as India and China, the concern about blood diamonds, and policy issues affecting the viability of trading diamonds. In this case, we study how Antwerp's dominant position in the diamond trade is being challenged and eroded. The case offers a good opportunity to introduce and discuss comparative advantage and relate it to Heckscher-Ohlin type of trade.

In this case, the managers of quality assurance for a pharmaceutical company must specify a fill target for individual bottles of a new blood-pressure medicine. Higher targets lead to higher material costs but fewer seconds.

A credit-card company must value portfolios of customers based on their future earnings. The payment characteristics of customers serve to classify them into states. This case can be the basis for discussing state dynamics over time in a Markov process.

This corporate strategy case shows how PepsiCo stopped worrying about competing with Coca-Cola, figured out what its real business was, and decided how to build its future. Redefining itself as a beverage and snack business, PepsiCo sheds its restaurant business and acquires Quaker and Tropicana. By rethinking the synergistic relationship between the complementary, combined strengths of the merged companies, it strategizes to develop innovative products that will compete in a changing demographic, cultural, and geographical world. Will this strategy work in an increasingly competitive environment?

This case presents the “best practices” of a highly successful post-merger integrator that grew from $400 million in 1997, to $1.5 billion in 2000, to $4 billion in 2002. The case focus is on the $4.0 billion IT sector of Northrop Grumman, a company confronting immense change in the rapidly consolidating defense business. This integration is unique in that the product is a complete melding of various companies, systems, leaderships, and cultures of 11 legacy organizations. Not only is the result an organization with a new identity, but also one with new strategic capabilities unavailable to any of the stand-alone legacy companies. A teaching note is available to registered faculty, along with video clips that include footage of weapons systems (e.g., B-2 bomber) and information about the company's PMI process.

This case exposes students to predictive analytics as applied to discrete events with logistic regression. The VP of customer services for a successful start-up wants to proactively identify customers most likely to cancel services or “churn.” He assigns the task to one of his associates and provides him with data on customer behavior and his intuition about what drives churn. The associate must generate a list of the customers most likely to churn and the top three reasons for that likelihood.

This case builds on the case "Merck & Company: Product KL-798" (UVA-QA-0582) by providing market uncertainties for the drug (drug quality, the presence of a competitor, market growth, and the time to the drug's release). Student and faculty spreadsheets are provided for the calculation of net present values for the scenarios. There is an additional challenge of how to treat the several downstream decisions (using OptQuest, for example) and how to value the license opportunity. A teaching note is also available to registered faculty members.