This case follows a fictional hedge fund manager as she works to finalize an investment thesis on Comerica Incorporated to present to her manager, who is undecided as to whether the fund should buy (go long) or sell (short) the stock. Assessing Comerica's value and outlook is complex. She needs to have a view on Comerica's future earnings, which are clearly linked to the gravity and duration of the COVID-19 pandemic and the resiliency of the banking sector as a whole. This case is taught at Darden in a course on "Artificial Intelligence and the Future of Work"; it would also be well suited for in-person or online MBA courses in banking and financial markets, new technologies, or communication and crisis response.

When Brian Huseman, vice president of public policy for the Seattle-based internet retailer and technology company Amazon.com (Amazon), prepared to meet economic-development officials and community leaders from Arlington, Virginia, in the wake of the company's February 2019 decision to pull a second headquarters location out of New York City, a lot was on the line. Facing a limit on its growth in Seattle, Amazon had embarked on a search for a second corporate headquarters, dubbed HQ2, in September 2017, and ultimately surprised the country when it announced its decision to split its HQ2 into two locations, Arlington and New York City, in late 2018. New York ultimately failed to give Amazon the warm welcome it was looking for, so Amazon focused solely on Arlington to claim the "biggest economic development prize in recent memory." Amazon was making a huge commitment to Arlington-including plans to develop up to eight million square feet of office space and hire 25,000 employees (each with an average salary higher than $100,000) over the next 15 years -one that would make it the region's largest private-sector employer. Huseman wanted to be sure Virginia was fully prepared to create the right ecosystem for Amazon's HQ2 to thrive. How should the e-retail giant approach the meeting, considering what could be asked of it-and what it should request in return?

In October 2018, Mike Bogan, CEO of LandCare, a nationwide commercial landscaping firm, was concerned about the significant headwinds facing not only LandCare but the entire landscaping industry at the time. As LandCare struggled to hire and retain employees who could prove their legal working status in the United States, it faced fierce competition from small firms, which frequently did not play by the same rules. Hoping to attract and motivate the right workers, Bogan enacted significant organizational change at LandCare after he became CEO in 2014; these changes included new practices and systems to improve performance, increase employee satisfaction, and drive cultural shifts within the organization. When Bogan saw positive results from his initial round of changes, he continued to expand. Readers are presented with Bogan's decision of whether to implement two additional organizational design elements: "jersey technology," which would allow him to accurately track individual movement and performance of his frontline landscape teams, and a daily pay system, which could potentially provide his lower-income workers with money on a more regular basis. Students must use their emerging understanding of the organizational design model (ODM) to consider each of these new systems and debate whether either system should be implemented.

Ford's F-Series of trucks were first introduced in 1948, and ever since they have represented American identity for their consumers. Both earned media, in movies like Urban Cowboy, and Ford's paid media positioned Ford as part of the pioneering culture. Ford also constantly introduced innovations to the F-Series to make the trucks more suitable to the changing needs of its consumers. In 2018, Ford's management decided to retreat from the low-margin cars segment and focus on trucks and SUVs. Ford was also working toward robot taxis and driverless delivery by 2021. These two parallel trajectories converge to pose a pivotal challenge for Ford: Should the company invest in developing driverless capabilities for its best-selling and highest-margin product, the F-150? The case provides students with a context in which to discuss the changing technologies in the auto industry and their implications for industry structure, along with the specific aspects of software-driven business models, consumer preferences, and brand identity. It also offers an opportunity to explore the challenges faced by traditional businesses as they develop digital capabilities and reimagine their business models to fully leverage artificial intelligence (AI). The competition among Ford, Google Inc. (Google), Uber Technologies, Inc. (Uber), and Tesla, Inc. (Tesla) in the automonous vehicle industry highlights the different routes these companies have taken to obtain develop autonomous vehicle capability that leverages their respective strategic capabilities.

This technical note gives students an overview of artificial intelligence (AI) and machine learning (ML) in order to help them understand how these fields can contribute to the future of marketing. To provide context, students are first introduced to the history of AI and the basic parameters of AI, ML, and deep learning (DL). The differences between ML and statistical modeling are also described to help students understand that collaboration between these two fields results in better decision-making. The note also provides a description of descriptive, predictive, and prescriptive analytics and how various ML tools span those categories. In order to illustrate AI's applications and the many ways managers can use it to promote their brands, real-world examples are provided, including: (1) 1-800-Flowers' collaboration with the Facebook messenger platform to process orders through chatbots (using DL), (2) Facebook's use of DeepText to determine the meaning of words within their contexts (using DL) and then direct users to related products; and (3) online educator Udacity's use of an ML algorithm to create a bot that advises salespeople on successful words and phrases, but also allows the humans to answer more obscure customer questions, among others. As students consider how AI advances are helping brands such as these market their goods and services to new customers online, students also must consider the ways that AI will continue to shape marketing in the future.

After Dwyer and Gazin had bought the domain name www.witchsy.com and researched the construction of multiple-seller websites using Google, the entrepreneurs quickly realized they'd need to bring in outsiders to help. Turning to Craigslist to post ads on their required work and solicit resumes, Gazin and Dwyer eventually began engaging with various male developers willing to build the technical aspects of their site. Early on in these interactions, however, an upsetting pattern started to emerge wherein the entrepreneurs constantly felt they were faced with disrespect, condescension, and poor collaboration from their male contractors. Hoping to mitigate this treatment, Dwyer and Gazin decided to create a fake male colleague they could rope into their email interactions with outsiders. They named this "colleague" Keith Mann and gave him an email address and Twitter personality. As soon as Mann started to engage with contractors and developers over email, the entrepreneurs were amazed to see the different tone and respect that was paid to Mann. When Witchsy finally launched in the summer of 2016, Dwyer and Gazin didn't have to wait long to see markers of success-within a year, their platform already had 45,000 Instagram followers and was generating a monthly profit. Even though Mann had existed only by name over email and was put to rest shortly after the site's launch, Dwyer and Gazin looked back on their experience of building Witchsy and had to wonder, would they have succeeded without Mann? Why had they faced so much antagonism without him, and was there a way to make sense of it?

In April 2017, Kevin Johnson took over the reigns as CEO of Starbucks, the iconic coffee giant. He faced a number of key decisions to keep the global retail giant competitive, but one in particular loomed large. Over the last few years, Johnson's predecessor, Howard Schultz, had increasingly used Starbucks as a progressive platform in an attempt to influence the world around its stores, whether he was aiming to smooth out race relations in the United States or support marriage equality. (Schultz was so vocal about these issues, in fact, that many people speculated he harbored secret political ambitions for his post-Starbucks career.) The case examines Schultz's memorable 2015 Race Together campaign and invites students to debate whether Johnson's work should be focused on (1) similar attempts to align Starbucks with progressive ideals and social causes, or (2) Starbucks' profitability and shareholder value alone. Were there certain times or circumstances where it was appropriate to engage in brand activism, and what impact might these initiatives have on brand integrity and the bottom line? In addition to inviting students to analyze the financial, branding, and employee- and customer-relations implications of social activism at Starbucks, the case also allows them to develop a framework for when and how brand activism might be appropriate in the future.

This technical note offers students a definition of brand activism (as contrasted to corporate social responsibility) along with an explanation of the different forms that this corporate practice can take. Specifically, students are introduced to the concepts of both progressive and regressive brand activism, in addition to the different causes the activist efforts may champion, whether social, legal, or environmental, to name a few. In order to illustrate these different categories and the sensible ways for managers to approach brand activism, examples of both successful and unsuccessful brand activism initiatives are provided, including those of Benetton Group, Dove, Patagonia, and Pepsi. While these companies' moves were intentionally designed to resonate with consumers, students are also presented examples of companies that unwillingly elicited activist customer responses (including GrubHub, Uber, Nordstrom, Starbucks, and Papa John's). Finally, the examples of Jack Daniels and Chick-fil-A illustrate deliberate corporate decisions not to communicate their values, while an explanation of boycotting and buycotting helps students understand the impact that brand activism initiatives can have on the bottom line.

The case discusses the decision of a hypothetical London-based hedge fund manager, Greg Rubin, who manages a fund primarily investing in emerging and frontier markets to decide whether to buy (or short) Safaricom, a Kenya-based telecom and financial services company that became globally known more than a decade ago (2007) for its use of technology to facilitate payments via mobile phones. There was a real need in Kenya for a different system of payments and money transfers, given the large underbanked population (almost 80% lacking a formal bank account) and the widespread use of cash. M-Pesa, the system introduced by Safaricom was an astounding success and quickly achieved a dominant position in the Kenyan marketplace. Kenyans embraced the use of mobile phones to transfer money and pay bills. More than 10 years later, at the time of the case (March 2018), Safaricom's dominance is challenged by a series of missteps expanding abroad (e.g., to South Africa), increased competition at home, as well as the introduction of 3G and advanced smartphone technology. The case allows for an examination of the investment thesis for Safaricom and its valuation. This requires the analysis of payment systems and their evolution in frontier markets as well as the analysis of country/political risk, among others. It is the combination of an innovative company from a frontier market and the introduction of new technologies that make this case interesting (and challenging) to analyze-by no means an obvious decision for Rubin.

This is a three-part, disguised case series. In June 2009, Diana Zanzi was hired by Ventoso Ship Supply, an Italian sailboat manufacturer, to help them understand their boats' puzzling selling patterns. Zanzi was informed that sales rates for two higher-end boat models were especially odd. Despite one's superior technical specifications, speed, amenities, and overall value-for-money, their higher end models were hard to sell. However, a lower-quality boat was sold at an astonishing rate. Existing survey work conducted by the company only served to confirm the rational assumption that customers generally preferred more technically advanced sailboats; as such, the survey would not solve the mystery. Tasked with solving this mystery, Zanzi was given the contact information for Ventoso's roster of potential customers and asked to conduct her own interviews to discover what could possibly explain customers' preferences when acquiring sailboats. Zanzi was told that consumers may not be consciously aware of how they choose sailboats, and so she needed to figure out a good method to understand these unconscious preferences. In part A of the series, the reader is faced with the task of designing a test that might reveal buyers' sailing-related thoughts. For instance, what should Zanzi ask consumers to understand their implicit and unconscious perceptions of the ideal sailboat? More importantly, the reader is invited to consider when and why such a tool is needed. In other words, what marketing technique should we use when consumers don't seem to be fully aware of their decision process?

This is a three-part, disguised case series. In June 2009, Diana Zanzi was hired by Ventoso Ship Supply, an Italian sailboat manufacturer, to help them understand their boats' puzzling selling patterns. Zanzi was informed that sales rates for two higher-end boat models were especially odd. Despite one's superior technical specifications, speed, amenities, and overall value-for-money, their higher end models were hard to sell. However, a lower-quality boat was sold at an astonishing rate. Existing survey work conducted by the company only served to confirm the rational assumption that customers generally preferred more technically advanced sailboats; as such, the survey would not solve the mystery. Tasked with solving this mystery, Zanzi was given the contact information for Ventoso's roster of potential customers and asked to conduct her own interviews to discover what could possibly explain customers' preferences when acquiring sailboats. Zanzi was told that consumers may not be consciously aware of how they choose sailboats, and so she needed to figure out a good method to understand these unconscious preferences. In part C of the series, the reader is tasked with interpreting multiple levels of data (including selected stimuli covering multiple senses, consumer-generated adjectives linked to those stimuli, and word clusters of shared meaning composed of those adjectives) that resulted from Zanzi's interviews. What does this data indicate about consumers' preferred sailboat qualities and, more expansively, how Ventoso can effectively market its sailboats across different cultures? This discussion again allows the professor to talk about various market research techniques.

This is a three-part, disguised case series. In June 2009, Diana Zanzi was hired by Ventoso Ship Supply, an Italian sailboat manufacturer, to help them understand their boats' puzzling selling patterns. Zanzi was informed that sales rates for two higher-end boat models were especially odd. Despite one's superior technical specifications, speed, amenities, and overall value-for-money, their higher end models were hard to sell. However, a lower-quality boat was sold at an astonishing rate. Existing survey work conducted by the company only served to confirm the rational assumption that customers generally preferred more technically advanced sailboats; as such, the survey would not solve the mystery. Tasked with solving this mystery, Zanzi was given the contact information for Ventoso's roster of potential customers and asked to conduct her own interviews to discover what could possibly explain customers' preferences when acquiring sailboats. Zanzi was told that consumers may not be consciously aware of how they choose sailboats, and so she needed to figure out a good method to understand these unconscious preferences. In part C of the series, the reader is tasked with interpreting multiple levels of data (including selected stimuli covering multiple senses, consumer-generated adjectives linked to those stimuli, and word clusters of shared meaning composed of those adjectives) that resulted from Zanzi's interviews. What does this data indicate about consumers' preferred sailboat qualities and, more expansively, how Ventoso can effectively market its sailboats across different cultures? This discussion again allows the professor to talk about various market research techniques.

In March 2009, Ulrich Bez, CEO of British carmaker Aston Martin Lagonda Ltd., found himself grappling with some tough news from Switzerland. The company had just debuted a novel car concept, its first crossover model under its rarely used historic Lagonda brand, at the Geneva Motor Show, but the negative press criticizing the four-wheel drive, four-seater car's design and concept was troubling and unexpected.

Supplement to case UV7459. In 2016 Andrew Rose, CEO of Compare.com, an online price comparison website for car insurance shoppers, faced a troubling problem. Completion rates for the site's detailed online questionnaire were at an alarming low. Site visitors, increasingly accessing the site on mobile devices, were proving they did not have the time or incentive to answer the site's requisite questions and thus were dropping off the site before purchasing policies from the site's partner insurance carriers. As Rose and his management team struggled to lift the completion rates, they narrowed their options to three potential solutions. A task for Kyle Brodie, a summer intern, was to design and run an experiment that could yield valuable insights from an estimates display, including which customer groups, if any, responded best to the estimates, and where the estimates should be included in the questionnaire. In the A case of the series, readers are faced with selecting the best solution for lifting Compare.com's completion rate. In the B case, readers must design an experiment to test the selected option, and decide on the location and content of an estimate display test. In the C case, readers are presented with the design implemented by Brodie and a summary of the results of that experiment. They must then figure out the implications of those results for Compare.com. This case was originally written for an MBA marketing class examining Marketing Analytics. It would also be suitable for similar classes in undergraduate, Executive MBA, and Executive Education programs.

Supplement to case UV7459. In 2016 Andrew Rose, CEO of Compare.com, an online price comparison website for car insurance shoppers, faced a troubling problem. Completion rates for the site's detailed online questionnaire were at an alarming low. Site visitors, increasingly accessing the site on mobile devices, were proving they did not have the time or incentive to answer the site's requisite questions and thus were dropping off the site before purchasing policies from the site's partner insurance carriers. As Rose and his management team struggled to lift the completion rates, they narrowed their options to three potential solutions. A task for Kyle Brodie, a summer intern, was to design and run an experiment that could yield valuable insights from an estimates display, including which customer groups, if any, responded best to the estimates, and where the estimates should be included in the questionnaire. In the A case of the series, readers are faced with selecting the best solution for lifting Compare.com's completion rate. In the B case, readers must design an experiment to test the selected option, and decide on the location and content of an estimate display test. In the C case, readers are presented with the design implemented by Brodie and a summary of the results of that experiment. They must then figure out the implications of those results for Compare.com. This case was originally written for an MBA marketing class examining Marketing Analytics. It would also be suitable for similar classes in undergraduate, Executive MBA, and Executive Education programs.

In 2016 Andrew Rose, CEO of Compare.com, an online price comparison website for car insurance shoppers, faced a troubling problem. Completion rates for the site's detailed online questionnaire were at an alarming low. Site visitors, increasingly accessing the site on mobile devices, were proving they did not have the time or incentive to answer the site's requisite questions and thus were dropping off the site before purchasing policies from the site's partner insurance carriers. As Rose and his management team struggled to lift the completion rates, they narrowed their options to three potential solutions. A task for Kyle Brodie, a summer intern, was to design and run an experiment that could yield valuable insights from an estimates display, including which customer groups, if any, responded best to the estimates, and where the estimates should be included in the questionnaire. In the A case of the series, readers are faced with selecting the best solution for lifting Compare.com's completion rate. In the B case, readers must design an experiment to test the selected option, and decide on the location and content of an estimate display test. In the C case, readers are presented with the design implemented by Brodie and a summary of the results of that experiment. They must then figure out the implications of those results for Compare.com. This case was originally written for an MBA marketing class examining Marketing Analytics. It would also be suitable for similar classes in undergraduate, Executive MBA, and Executive Education programs.

Supplement to case UV7317

This case is set on the verge of Microsoft initiating a TV white-space pilot in the Philippines in the summer of 2013; the uncertainty surrounding the new technology's performance in the region provides a view of the risks organizations face early on in the innovation process, particularly when decisions are decentralized and overseen at a local level. MS and its public partners in the Philippines were excited about the possibility of setting up the country's first TV white space-enabled broadband network in a remote area that required the connectivity for fisher registrations and government biodiversity initiatives. The technology had proven its success in a few other pilots in Singapore and the UK. In the Philippines, however, risks loomed. Unprecedented complications from an untested hardware supplier and a lack of an essential database arose as the launch date approached. A key decision MS had to make was whether to proceed with the pilot or focus on TV white space pilots elsewhere. The case introduces students to methods through which they can identify the sources and types of uncertainty associated with a project. Through this they can better evaluate the tradeoff between undertaking a project with a high risk of failure and the benefits that could be obtained through learning about unknown unknowns within such a setting despite the outcome. Moreover, students uncover the necessary conditions for projects to achieve their objectives within this setting. The public-private partnership setting allows students to analyze the type of uncertainty associated with a project; the project, product, and organizational complexity; stakeholder objectives; and discuss the role escalation of commitment could play when an organization seeks to pilot a new technology.

In October 2016, Timothy Sloan, the newly appointed CEO of American banking giant Wells Fargo, faced a massive public-relations crisis. A few weeks earlier, a United States government agency had announced the results of its regulatory review of the bank and exposed a shocking practice common in the retail division, in which aggressive community bankers had created more than a million fraudulent accounts and credit card applications on behalf of unaware customers for the past several years. Over the next few weeks, the bank-and Sloan's predecessor, John Stumpf, in particular-suffered from harsh criticism from politicians, journalists, and former employees alike, ultimately forcing Stumpf's resignation. As Sloan sought to minimize the public-image backlash and restore general trust in Wells Fargo, he struggled to construct the best communication strategy for the bank's next chapter.

This case invites students to assess the impact that Brexit, the withdrawal of the United Kingdom from the European Union, might have on a New York-based hedge fund's portfolio and, specifically, its UK assets. The case is designed to prompt students to make market assumptions and investment hypotheses based on a combination of numerical data and qualitative information. It requires no numerical computations; instead, it asks the student to interpret both markets' short-term reactions to the Brexit vote and strategy shifts from UK and European business leaders in order to evaluate longer-term implications for the economies of the United Kingdom, Europe, and the world.