Case studies

Neons Fashion LLP was an entrepreneurial venture of Arthi Ramalingam after completion of her MBA. Arthi had an interest in jewellery since childhood and she decided to focus on design, manufacturing and retailing of fashion and costume jewellery items under the brand name of Eternz through different sales channels like exhibitions, retail stores, own website and as an independent seller on e-commerce marketplaces. She initially started selling on Amazon marketplace through a third party, Cloudtail India Pvt. Ltd., and later sold through other e-commerce marketplace operators like Flipkart, Jabong and FirstCry. As her business grew, Arthi planned to add the kids' shoes category and also decided to participate in Bangalore Fashion Week to build the Eternz brand. However, in November 2016, Cloudtail terminated her contract which played havoc with the sales and profitability of her start-up. Neons Fashion LLP (A) provides details of how independent sellers are at the mercy of marketplace operators and ends with the need to review the choices of sales channels for different categories like fashion garments and fashion accessories, and for the upcoming launch of kids' shoes. Neons Fashion LLP (B) describes the events after the Bangalore Fashion Week that ultimately led to closure of business.

John Dong, the founder and CEO of Kaffee Kostuum developed the idea of Kaffee Kostuum in his own MBA capstone project five years ago. Shortly after graduation, he received seed money from business angels, as well as a favorable bank loan. His value proposition was clear from the beginning: “Be a provider of an unlimited variety of affordable suits, directly available from stock.” The idea sprang from his frustration with two less-than-ideal circumstances: He either had to wait four weeks to get a pricey tailor-made suit or purchase from among the limited selection of affordable suits in his local department store. To keep his company's prices down, Dong worked with a production unit in Vietnam.

In January 2019, Benedict Clarke needed to address the vacancies at retail shopping center Tulaberry Plaza. The rise in online shopping forced Tulaberry's anchor tenant into bankruptcy and weakened the outlook for retail more generally. Clarke must devise a plan that presents the most logical and profitable way forward for the shopping center. The case asks students to make leasing decisions from the perspective of the property owner, Clarke, giving them an appreciation for both the quantitative and qualitative factors that influence optimal leasing decisions.

Kiera, a young, enthusiastic sales rep, was recently promoted to manager of a sales team of five. In her first year on the job, she tackled a major revamp of the company's outdated training materials and organized a regional conference for her area, but neither her boss nor corporate seemed to appreciate the work she had been doing. Without support or guidance from her boss, Kiera was confused. What was she supposed to do? Parts A and B of the case present two different perspectives on coaching. Part A contains a narrative from the point of view of the “coachee,” Kiera, who was learning how to work with her boss, ultimately with the assistance of an executive coach. This case focuses on coaching as a tool to enhance self-management and relationship management and to improve personal performance. Part B describes how Kiera started to learn the “coach approach” to managing her team with the continued guidance of her executive coach. She learned to apply the same skills that her coach used with her in Part A to diagnose her team, share feedback, and communicate expectations. She was learning how to listen and ask thoughtful questions, but she also needed to expand her awareness to “other-management” and build her own coaching skills to enhance her team's performance.

Kiera, a young, enthusiastic sales rep, was recently promoted to manager of a sales team of five. In her first year on the job, she tackled a major revamp of the company's outdated training materials and organized a regional conference for her area, but neither her boss nor corporate seemed to appreciate the work she had been doing. Without support or guidance from her boss, Kiera was confused. What was she supposed to do? Parts A and B of the case present two different perspectives on coaching. Part A contains a narrative from the point of view of the “coachee,” Kiera, who was learning how to work with her boss, ultimately with the assistance of an executive coach. This case focuses on coaching as a tool to enhance self-management and relationship management and to improve personal performance. Part B describes how Kiera started to learn the “coach approach” to managing her team with the continued guidance of her executive coach. She learned to apply the same skills that her coach used with her in Part A to diagnose her team, share feedback, and communicate expectations. She was learning how to listen and ask thoughtful questions, but she also needed to expand her awareness to “other-management” and build her own coaching skills to enhance her team's performance.

This case challenges students to solve a riddle: How did Motorola's share in the Indian market fall so dramatically while cell phone adoption in India skyrocketed and Motorola was launching one of its most successful products globally? The case is set in the mid-2000s, when Motorola had just rolled out the Razr phone and the firm was approaching the ten-year anniversary of its entry to the Indian market. Motorola's market share in India had fallen from as high as 31% in 1998 to less than 5% in 2006. This dramatic downturn came at a time of immense growth in the Indian cell phone market.

Stella Artois, an AB InBev brand, is the world's best-selling Belgian beer. In early 2017, Ricardo Tadeu, AB InBev Zone President for Africa, is planning the brand's entry into its next export market: South Africa. The case explores Stella's introduction strategies into three of its export markets—the UK (1976), the US (2000), and Mexico (2016)—examining the drivers of the brand's success as well as its failures. Students will analyze the brand's previous launches to determine what made it successful in some markets and not in others. They will apply these learnings to develop a strategy for the brand's introduction to the South African market. Beyond the central discussion of growth through international expansion, the case addresses issues of brand positioning for premium products, changing consumer perceptions, the use of cause marketing, category development and maturity, and competitive strategy.

First National Healthcare (FNH) runs a large network of hospitals and has worked to systematically reduce waiting times in its emergency departments. One of FNH's regional networks has run a successful marketing campaign promoting its low ED waiting times that other regions want to emulate. The corporate quality manager must now determine whether to allow these campaigns to be rolled out and, if so, which waiting time estimates to use. Are the numbers currently being reported accurate? Is there a more accurate way of estimating patient waiting time that can be easily understood by consumers?

This case series describes the startup of Farm to School of Park County, an emerging nonprofit organization in the US state of Montana. Case (A) describes the community, the need, and the origins of Farm to School in Livingston, Montana. The leaders of Farm to School face a budget crisis and need to evaluate four options to decide whether, when, and how it should become an independent organization. As Case (B) begins, Farm to School has decided to enter into a fiscal sponsorship agreement with the local community foundation. The next task for the organization's leaders is recruiting founding board members. They need to decide whom to ask and how to do it. In Case (C), the board develops a strategic plan and establishes committees. However, the board members and leaders start to feel fatigue in the face of the demands of a startup organization, leading to questions about what is truly strategic and how work will get done. The Farm to School organization in Case (D) has just issued its first annual report, filled with meaningful accomplishments. The leaders of the organization begin to plan to build an organization that will outlast them and the founding board members.

This case series describes the startup of Farm to School of Park County, an emerging nonprofit organization in the US state of Montana. Case (A) describes the community, the need, and the origins of Farm to School in Livingston, Montana. The leaders of Farm to School face a budget crisis and need to evaluate four options to decide whether, when, and how it should become an independent organization. As Case (B) begins, Farm to School has decided to enter into a fiscal sponsorship agreement with the local community foundation. The next task for the organization's leaders is recruiting founding board members. They need to decide whom to ask and how to do it. In Case (C), the board develops a strategic plan and establishes committees. However, the board members and leaders start to feel fatigue in the face of the demands of a startup organization, leading to questions about what is truly strategic and how work will get done. The Farm to School organization in Case (D) has just issued its first annual report, filled with meaningful accomplishments. The leaders of the organization begin to plan to build an organization that will outlast them and the founding board members.

This case series describes the startup of Farm to School of Park County, an emerging nonprofit organization in the US state of Montana. Case (A) describes the community, the need, and the origins of Farm to School in Livingston, Montana. The leaders of Farm to School face a budget crisis and need to evaluate four options to decide whether, when, and how it should become an independent organization. As Case (B) begins, Farm to School has decided to enter into a fiscal sponsorship agreement with the local community foundation. The next task for the organization's leaders is recruiting founding board members. They need to decide whom to ask and how to do it. In Case (C), the board develops a strategic plan and establishes committees. However, the board members and leaders start to feel fatigue in the face of the demands of a startup organization, leading to questions about what is truly strategic and how work will get done. The Farm to School organization in Case (D) has just issued its first annual report, filled with meaningful accomplishments. The leaders of the organization begin to plan to build an organization that will outlast them and the founding board members.

In 2008, Starbucks was in crisis as a result of undisciplined growth and loss of focus, and its stock declined almost 70%. In August of that year, Howard Schultz, the founder of Starbucks, came out of retirement to take over as the CEO. The company regained its footing by refocusing on its core and driving strong organic growth. By 2014, the stock price had reached $40, an all-time high. To prevent history from repeating itself, Schultz wanted to ensure that Starbucks' growth strategies not only addressed market opportunities, but also were aligned with the company's brand image, assets, and capabilities.

Starbucks announced a five-year growth plan in December 2014 with ambitious goals that included nearly doubling its revenues from $16 billion to $30 billion, doubling operating income, and expanding its footprint to more than 30,000 stores globally by 2019. The growth plan consisted of seven specific growth strategies, one of which was the New Occasions strategy. The objective of New Occasions was to drive growth by diversifying Starbucks' revenues beyond breakfast to the lunch, afternoon, and evening dayparts. Starbucks created specific offerings for each daypart, called the Lunch, Sunset, and Evenings programs. The case focuses on evaluating these three occasions-based growth opportunities and identifying the best path forward.

Polaris Battery Labs was an Oregon-based startup that provided innovation services to companies in the lithium ion battery industry. Its operating philosophy and expertise in this fast-growing industry enabled it to provide great value to its clients, but as a startup that was seeking growth the company was subject to multiple risks.

For Polaris, taking clients, developing new manufacturing capabilities to meet unproven battery technologies, and even extending credit to its clients posed real risk. Many of its clients were startups themselves and had a significant probability of failure. Others were established firms testing new and unproven battery technologies, many of which were unlikely to gain traction in the market.

The case examines how a technology-driven firm managed the risk of working with startups, claiming appropriate intellectual property, and developing a sustainable portfolio of clients.

Dr. Phillip Hoopes, a LASIK surgeon, is considering how to respond to discounting by his competitors. He had built a high-end practice with costly advanced technology, but discounters had recently entered the market and other high-end practices in the area were starting to offer deep promotions in an effort to compete.

In this case, students step into the shoes of a brand manager at UK-based online peer-to-peer lending company Zopa as she decides whether or not to recommend that the company undertake a brand redesign. Students are provided a brand design worksheet to help them understand the component parts of brand strategy and brand design and to help structure their assessment of Zopa's current brand. They are then challenged to consider if, to what extent, and how Zopa's brand design should change as a function of the company's brand strategy. Finally, they will learn a set of best practices, or guidelines, for approaching brand redesigns.

This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM).

The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]).

The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.

Uber China is a strategy pricing case that examines the role of customer acquisition tactics and brand positioning in entering the tantalizingly large Chinese market. The case adopts the perspective of an outside observer looking at Uber's efforts to compete in China from its entry in 2013 to its exit through its acquisition by Didi Chuxing, the highly dominant industry leader in China's ride-sharing market. After laying out the market opportunity, consumer and competitive landscape, and the various acquisition-related moves of Uber and the other major players, the case asks students to conduct a postmortem on Uber's failure in China. Specifically, they must consider what drew Uber to the opportunity in China and what it might have done differently in terms of positioning and customer acquisition to compete more effectively. First and foremost a pricing-related discussion, the case illustrates the relationship between pricing and acquisition tactics and brand positioning and the use of both in market entry and penetration.

This case features Lucas Lopez Lince, a rising leader in Colombian consumer goods company Grupo Familia. Lopez Lince had inherited a digital marketing program built around a newly identified customer persona–a young low-income mother. The program represented a significant shift in Familia's target customer as well as a shift in the way marketing funds were spent. The program appeared to be working, so he increased the digital spend even as he had to reduce his overall marketing budget in the face of challenging economic headwinds. Activity metrics such as page views, social media “likes,” and video views rose dramatically, and at the same time sales began to rise again. By the beginning of 2017, Lopez Lince faced a deeper set of questions. How could he be certain that the rising sales were due to the digital efforts? Would the existing digital programs and tactics continue to deliver against chosen metrics? And what could he do next in order to continue driving growth of revenue and margin through digital efforts? Students assume the role of Lopez Lince and are asked to apply concepts such as customer personas, micro-moments, and customer journey mapping to develop their own point of view on what they would do next.

Jennifer McDougall is considering investing in mutual funds for the first time, and has narrowed her options down to three: one that is domiciled in Germany, and two that are domiciled in Luxembourg. As a cautious and risk-averse investor, Jennifer has done extensive research on the three funds, and has come across a curious fact: the beta of the German fund is surprisingly low. After speaking to her financial planner, she learns there is no legal requirement in Germany for mutual funds to compute net asset values at a particular time of the day. If the German fund is closing its books in the middle of the day and its net asset values reflect its midday holdings, rather than end-of-day holdings, this could explain the low beta. Thus, the German fund might appear less risky, without actually being so. Jennifer needed to get a clearer picture of what was going on before making her decision.

Using the data provided with the case, students will determine the closing time of the three funds and how that affects the beta of each. Then they must make a recommendation about which fund would be the best investment for Jennifer.

In early December 2013, Roxann Biller, Associate at the Chicago-based private equity firm Delta Quantitative Real Estate Capital, was asked to assess the risk associated with the firm's first potential overseas investment. Haifu Sentā Gendaino (HSG) was a large multi-tenant logistics property located in the Gaikando area of Tokyo. High-quality tenants currently occupied the property, so at first glance the risks of investing in the property seemed minimal. However, Biller knew that she had to consider the potential drawbacks. This would mean gaining a better understanding of each tenant, trying to forecast the future condition of the Tokyo logistics market, and considering what new risks her firm would face because the property's cash flows were in a foreign currency.

Read any news report on the housing market, and inevitably it will include facts or figures from the real estate data giant Zillow.com. The company initially set out to solve two key economic frictions in the real estate industry information asymmetry and the principal-agent problem by empowering users to access real-time housing data and eliminating the need for realtors. The company soon realized, however, that American homeowners and buyers were not willing to give up the traditional real estate agent model and changed course. In the end, Zillow decided to join rather than replace the middlemen in the real estate industry.

The case illustrates the application of the concepts of demand elasticities of an agricultural product with high protein content - pulses. It considers the current situation where a good monsoon has raised hopes for a bumper crop of pulses in India. From a deficit of about 20% met by imports, the county now is looking at attaining self-sufficiency. Public Policy options such as exports, imports or allowing domestic price adjustments or changing the minimum support price (MSP) in this regard are also considered.

ThinkAlike, a fictitious marketing consulting firm, was asked by TiVo to segment the market for its new digital video recorder (DVR) product. Students are asked to analyze realistic data and generate segments that will be useful for TiVo s marketing strategy.

Two recently graduated MBA students are tasked with developing an ad-serving learning algorithm for a mobile ad-serving company. The case illustrates the way in which hypotheses can be tested in an A/B format or “horse race” in order to establish customer preferences and superior profitability. The case was written for a course elective covering hypothesis testing.

The Global Networks Company (GNC), headquartered in Boston, Massachusetts, made its global footprint in India in 1994 by establishing a presence in Bangalore. Although mainly a sales support office, GNC grew name recognition from its contracts with India’s government to help build nationwide networks. Not quite 20 years later, GNC decided to further invest in India and tapped a manager from the Boston office, Jim Notrika, to establish and then manage GNC’s first global software center in Mumbai. Split between Mumbai and Boston, the project team successfully completed several minor projects, but only months into its first major project, the team was struggling to meet deadlines. Blame was being passed in both directions, and when three talented engineers in Mumbai quit, Notrika makes an emergency trip to Mumbai to better understand the problem.

This case describes three common cross-cultural communication obstacles in teams: a preference for direct versus indirect confrontation of problems; a clash of collectivist versus individualistic cultural values related to reporting bad news or giving negative feedback; and different expectations of team leaders based on power-distance values.

This is the first implementation of Revenue Management System in a major international hotel chain in India. The case describes the history of development, corporate story of overdrive for profit, system integration issues. It describes two components of a revenue management system, forecasting and optimization. It also raises several questions that need to be addressed before implementing a RMS.

In the first case of a two-part series, a strategic finance manager at Wells Fargo with experience installing solar panel systems on bank branches crunches the numbers for a similar project in the Los Angeles area given the uncertain future of a government rebate.

The organizers of a music festival may use video from the Friday concert to create a DVD to sell to those who come to the Saturday concert. Attendance on Saturday is uncertain, as is the percentage of those who attend on Saturday who will buy the DVD. Is this a good project? If so, what number of DVDs should be burned early Saturday morning and offered for sale at that evening’s performance? By that time, Friday attendance is known, as well as whether it rained on Friday, and there is a forecast for whether it will rain on Saturday. Historical information on these variables may help us predict Saturday attendance using multiple regression; together with the results of a marketing survey, such analysis will help us make better purchasing decisions. This case series (see also the B case, UVA-QA-0708) can be used to illuminate a multitude of concepts that are covered in basic decision-analysis courses. The series starts by examining the role of uncertainty in decision-making, proceeds through the estimation of probability distributions from sample data with multiple regression, culminates in the development of a full decision model, and ends with a qualitative and quantitative analysis (with a tornado diagram) of how to add value and reduce risk. Key pitfalls for students are failing to recognize both limits on sales (supply and demand), incomplete reasoning in the determination of the attendance probability distribution, and oversimplifying the full forecast model.