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The case is set in April 2023, soon after DBS Bank Limited (DBS) reported a 20% net profit growth of US$6.02 billion. The bank's CEO Piyush Gupta had attributed this growth to the company's continuing digital transformation journey that had started more than a decade ago. Central to this journey was the bank's adaptation of Artificial Intelligence (AI), to improve and diversify products and services. To become AI-fuelled, DBS had created a "Data First" culture and hired hundreds of technology professionals to build its technology capabilities. In addition, the bank had set aside substantial budgets to allow for experimentation, motivated individual departments to build and deploy AI-based applications, implemented an automation strategy to guide solution building, and embedded AI into nearly every part of the customer journey. Prior to the transformation, DBS was sometimes irreverently referred to as 'Damm Bloody Slow' due to its poor customer service, but had emerged as a customer-savvy, market-responsive, AI-fuelled company with more successes than failures, diversified lines of business, and dramatic growth in revenues. However, the financial services sector was seeing increased competition due to the entry of purely technology companies like Grab, PayPal, Alibaba, etc. with innovative solutions. How could DBS compete in a rapidly changing banking marketplace? Had the 'All in on AI' approach given the bank a competitive advantage? Could DBS's prior 10 years of successful efforts with digitalisation, analytics and AI position it to take advantage of the newest generation of Generative AI in an accelerated manner?

Inter IKEA Systems B.V. (IKEA) entered Korea at a relatively late stage of its global expansion and encountered an overwhelmingly positive customer response, which emboldened it to open several additional stores at a relatively fast pace. However, IKEA encountered much stronger headwinds after the COVID-19 pandemic hit Korea. It had to shift to online sales channels, mitigate customer dissatisfaction, face aggressive Korean competitors, accommodate a major slump in furniture demand, and address employee dissatisfaction and strong demands from its labour union. What could the company do to address these challenges and renew its success?

This case presents a dilemma that professional golfers face when having to choose a target point for landing the ball. Key to this case is to acknowledge uncertainty as reflected in less-than-perfect accuracy. Thus the ball will land in a ""cloud"" around the intended target. On such a cloud, some spots (e.g., the fairway) are better than others (e.g., sand bunkers or rough). There is therefore a conflict between advancing the ball as close to the hole as possible, while at the same time reducing the chance of being in trouble on the next shot. The idea is to find a sweet spot between these two competing goals. To operationalize this problem, we use data from the Professional Golfers' Association (PGA) tour to estimate the average number of shots to complete the hole as a function of (i) distance to the hole, and (ii) type of surface (fairway, rough, recovery, sand, or the green). The case comes with a companion Excel spreadsheet, UVA-QA-0953X, which shows a map of a classical hole in the PGA Tour (the 10th at the Riviera Country Club in Los Angeles). This Excel file also displays a heat map of a bivariate normal around any chosen target, and a heat map with the average number of strokes to complete the hole. Students' goal is to understand the model and use it to find a good target.

Spreadsheet Supplement for Case UV8782

<p align="justify">The case describes how Zhuiyi, a leading conversational artificial intelligence (AI) start-up in China, developed its growth strategy and made transitions in the face of product commercialization challenges. The crux lies in the low customer satisfaction rate of AI products, which could be endogenously attributed to mismatched expectations among customers and the founding team in the product development process as well as to the lack of vertical industry knowledge among executives and employees. Zhuiyi needs to make a strategic choice between: a) developing new AI products by making large and risky research-and-development investments or b) devoting more resources to product customization and expanding the market through client diversification.

Student spreadsheet for Ivey product W21155.

Second Place Winner; 2023 DEI Global Case Writing Competition Rhino Foods is a U.S.-based Benefit Corporation (B Corp) owned and operated by the Castle family. A food ingredients supplier to global brands, the company grew to $60 million in annual revenue by 2019. Rhino Foods was best known for inventing and manufacturing the cookie dough found in Ben & Jerry's top-selling ice cream flavor. The case's central topic is how Rhino creatively emphasized inclusive hiring and retention, though balancing people-centric, product quality, and financial goals were continuing challenges. Many Rhino employees were new Americans who came through waves of refugee resettlement programs. Integrating these non-English-speakers into a production floor laden with heavy machinery necessitated investments such as translating the operations manual, adding subtitles to training videos, and pairing new employees with experienced workers with the same native language. Religious and cultural factors new to Rhino became important, as well. Rhino then began to recruit people who had dropped out of the labor force, including coming out of incarceration or rehabilitation for substance use. It created a No Background Checks program to remove barriers to entry like proof of past experience or having a criminal history. Students are challenged to suggest how the leadership team can better understand employee turnover, provide innovative methods of support, alleviate employee concerns regarding new hires, and continue to grow the company in a healthy way.

Israeli generative artificial intelligence company AI21 Labs was founded in 2017 to realize the vision of true machine intelligence. It sought to reinvent writing and reading and in 2020 it launched Wordtune, an app using GenAI software to offer alternate text suggestions to help improve users' prose; in 2021 it released Wordtune Read, an app that summarized documents. In 2021 the company unveiled its first Large Language Model (LLM), and it also offered five application program interfaces on its Studio platform. Following a 2023 partnership with Amazon Bedrock, AI21 Labs' LLM was available to third parties. After Generative AI burst onto the global scene in 2022, AI21 Labs considered the best strategy to stay relevant among tech giants in the GenAI arena.

Neeraj Bakshi, who bought a vodka distillery in 2019 in Mississauga, Ontario, had big dreams for the distillery and purchased a 2.5-hectare property in Welland, Ontario, to increase its production capacity. Bakshi had invested significantly in NB Distillers, which now produced three types of vodka, two types of whisky, and one type of gin, and he wanted to see nothing but success. He had advertised on billboards, bus shelters, and radio, but he wanted to spend his communication budget more strategically and was open to trying new ideas. Now, in May 2021, he needed answers to several important questions: What audience segment should NB Distillers target? How should Bakshi position the distillery? What other promotional tools might help him achieve greater brand awareness?

Recent research shows that rather than engaging in comprehensive decision-making, CEOs may be better off relying on heuristics simple rules of thumb that require little information and analysis. Often based on direct learning experiences, heuristics are used consciously and deliberately, and frequently result in superior decision outcomes.

This case highlights Wärtsilä's significant role in the decarbonization journey of the energy and marine sectors. Despite the difficult financial situation and challenging market dynamics - Wärtsilä was active in industries that relied heavily on fossil fuels with little potential for future growth - CEO Hakan Agnevall took a bold decision to convert threats into opportunities and use decarbonization as a vehicle to transform the company. His vision was to turn the company into a leader in sustainable solutions. The ambitious goal set by Agnevall presented Wärtsilä with numerous challenges. The industries in which the company operated were undergoing disruptive changes, but the transition to sustainable alternatives would take decades. Both the energy and maritime industries were characterized by long-term investment cycles and a certain conservatism in terms of adopting new technologies. One of the major hurdles faced by Agnevall was timing. Wärtsilä already had a portfolio of green technologies ready to be offered to customers, but the market demand for these solutions was not yet fully established. The transition to green solutions would require time. As the industry gradually transformed, Wärtsilä understood that it would take several years before the company could fully benefit from its new strategy and investments in green technologies. Balancing the long-term strategic commitment to decarbonization with the need to address short-term financial imperatives and satisfy shareholders was a critical challenge. Wärtsilä was making long-term investments in various green technologies, but the uncertainty surrounding which technology would eventually prevail added to the complexity of the situation.

Spreadsheet supplement for case 723430.

Every organization can-and should-generate more revenue from its data than it invests in producing and managing it. Yet the idea of turning data into money is often associated with sneaky tactics or 'going too far' with unacceptable privacy violations. As a result, some organizations, especially non-commercial ones, have very little appetite for the term 'data monetization.' The authors say it's time to embrace the concept. They present three approaches to monetizing data: Selling, which entails the exchange of data for money; Improving, which uses data to create efficiencies for cheaper or faster operations; and Wrapping, which uses data to enhance products such that customers want to buy more. In the end they show that, if you will limit what you view as data monetization opportunities, you leave money on the table. Often, a lot of money.

Did you know that waves, tides and currents in bodies of water could provide more reliable sources of energy than either wind or solar? Or that volcanic sand and genetically-edited crops could be significant natural carbon-capture and storage opportunities? Of course, such tech trends on their own cannot predict the future. But by understanding the changes shaping the technology landscape, leaders can make informed decisions and capitalize on new opportunities. The author, who heads up the Future Today Institute, shares three key categories of trends from the Institute's annual Tech Trends Report: Financial Services, Artificial Intelligence and Climate, Green Tech & Energy.

As of 2023, Netflix is the largest streaming-video provider. However, it faces increased competition, as well as slower growth in subscriptions, which have caused it to reconsider its past practices. This case describes the history of Netflix's business model and the antecedents that have led it to make some significant changes-the most important of which is an ad-supported subscription option. It is also engaged in cost-cutting measures, discouraging password sharing, and even making a small foray into video gaming. This case is suitable for a capstone strategy course or an advanced elective in competitive strategy at the MBA level. It has been used by MBAs and executives (both in the United States and in Europe) in classes covering strategic management.

This case covers Ripple's events from 2020-2023. The focus of this case is Ripple's 2023 victory over the SEC, which sued Ripple in 2020 claiming that they did not register their XRP coins as securities. After Ripple's victory, CEO Garlinghouse faced numerous decisions, including whether to invest other companies to building out the crypto ecosystem, launch a stablecoin (as several crypto companies had done), and whether he should take a leadership position on government policies on crypto or remain in the background.

This case aims to provide a deep understanding of two important dimensions of Indian society, which are instrumental in determining most socioeconomic outcomes: caste and gender. The case discussion is divided into two parts. The first part examines the roles of caste and gender in modern Indian society. The second part seeks to encourage students to think about actionable, policy-relevant solutions that can be implemented by different social stakeholders (businesses, governments, individuals, etc.) to mitigate caste and gender barriers and build an inclusive labor force. The case is taught at Darden in the second-year elective, "India in the Global Economy." It is taught in the first week of the course, with the aim of introducing students on the role of caste and gender in modern Indian society. It would also be suitable in courses related to social identity, ethics, business strategy, and social inclusion, where individual identity plays an important role in influencing socioeconomic outcomes.

James Waite, the manager at Western Film, must decide which film to screen at his cinema in the upcoming week. He must evaluate whether to continue showing Spider-Man: Far From Home (Spider-Man), or replace it with one of three other films available for him to screen. Western Film, a second-run theatre, has the advantage of having domestic box office information available, and Waite must analyze whether this information is helpful to him in making this decision.