個案總覽

On August 21, 2015, Amit Gudka and Hayden Wood, co-founders of Bulb Ltd. (Bulb) launched a new business to supply energy to the United Kingdom's 27 million residential homes with a promise of 100% renewable electricity at affordable prices. By the end of March 2017, Bulb had grown to supply 29,311 properties, well ahead of its Launch Plan of 23,166 and beyond the point of breakeven. It had been a slow start, and growth had been volatile, reaching a rate of over 3,000 new members per week at one point, putting severe strains on service levels. Moreover, Gudka and Wood had been forced to change many aspects of their plan and defer launching value-added services to help customers reduce energy consumption and create Bulb's vision of distributed generation. Now, the company was generating profits; enough to grow, but not at the level of the original plan, and there would be nothing left to invest in value-added services. Should the founders scale back on their growth ambitions and delay adding services until they had reached the scale to support them? Or should they seek more funding and accelerate growth?

After a wild and volatile year, Bulb, a new entrant in the UK residential energy market, ended March 2018 with 329,171 properties, 1.2% of the total residential energy market). This was 150% ahead of a plan for 130,000 properties and almost ten times the size the founders, Amit Gudka and Hayden Wood, had imagined in August 2015 when they first launched. Bulb was now one of the top 12 energy suppliers in the UK. Gudka and Wood were convinced that if they reinvested all their profits in growth, they would reach 500,000 properties by March 2019, and reach more than 1 million by March 2021. This would mean postponing the launch of a range of value-added services they had included in their original Launch Plan, but it could make Bulb number 7 in the industry and the first real challenger to the UK's "Big Six" leading energy suppliers to pass the one million-member mark. Even so, Bulb would still be less than 40% of the size of the smallest member of the Big Six and one sixth the size of the leader, British Gas. Was it time to seek more funding to really challenge the Big Six, making renewable energy mainstream? And did it make sense to delay value-added services to support energy conservation, distributed generation, and the switch to electric vehicles, or should they seek funding to support these initiatives too?

Supplement to case UV7653

The case opens in July 2016 as Barbaros Ozbugutu, co-founder and CEO of the Istanbul-based payment technology start-up iyzico, contemplates the pros and cons of the different term sheets the company has received for its Series C round. The case then informs the reader about some changes in circumstances that affected the terms of the shortlisted offers. At the end, the case poses this question: Being faced with worsening terms in a volatile environment, should Ozbugutu go ahead with the round, or should he wait and try again at a later point in time?

This short case, meant for pairing with HBS case 615-013 "AmazonFresh: Rekindling the Online Grocery Market," explores Amazon's rationale for acquiring Whole Foods.

Supplement to case UV7726 When Justin Thomas began as principal of Shining Star Academy, an elementary school in Alabama, the school had been failing for eight years and was in serious risk of state takeover. One of Thomas's innovations was to implement data-driven instruction, but teachers struggled to change their routines. As hard as everyone was working, progress was minimal after a year. Thomas was heartbroken, and he didn't know what else to try. The B case follows Thomas in his second year, as he continues to lead the school through its transformation. This case is used at Darden in executive programs for leaders in education and second-year MBA courses on leading change. It would also be suitable in courses covering data-driven instruction, school transformation, leadership, and change processes.

Supplement to case UV7729 Maxine Hall, the new principal at Northwest Middle School, knew when she started that the school was suffering from a sense of distrust between teachers and administration, as well as a high degree of student disengagement and absenteeism. To unlock student achievement and instill much-needed consistency and alignment across the school, Hall implemented data-driven instruction, but her efforts were stymied by an unwillingness to change among staff and teachers. The B case follows Hall in her second year, as she continues to lead the school through structural changes. This case is used at Darden in executive programs for leaders in education and second-year MBA courses on leading change. It would also be suitable in courses covering data-driven instruction, school transformation, leadership, and change processes.

In the A case, Rose Matthews, vice president for patient advocacy at University Hospital, must decide how to handle a startling discovery about patient risk. Weeks after a patient dies, lab results revealed the cause was prion disease, a deadly condition similar to mad cow disease. Since the diagnosis of this very rare condition was not known at the time of the patient's brain biopsy, surgical instruments used for the procedure were conventionally sterilized (rather than using special methods required to kill prions) and reused in up to 100 other surgeries. Now Matthews and her team must decide an ethical communication dilemma: (1) disclose the potential, though very low risk that patients may years later develop the disease; or (2) choose to protect patients from mental anguish related to worrying about a disease they most likely will not develop. The B case reveals that the medical team decided not to disclose this news to patients, only to have the news leaked to the media by a disgruntled hospital employee. The forthcoming teaching note offers three potential teaching plans for this case depending on the desired learning objectives: (1) writing a risk or crisis communication plan; (2) setting up a two-minute role-play of an oral statement delivered at the beginning of an internal meeting or for a press conference; and (3) responding to the media leak.

A bank manager is thinking about how to manage the new private banking advisers (PBA) practice in her region. For that she needs to determine how many PBAs she needs, where they should be located, and to which branches each of them should be assigned. This three-case series exposes students to the underlying sequence of analytical tasks, which culminate in solving an integer-programming optimization model-a main tool of prescriptive analytics. The assignment part of the problem (e.g., given the home-base locations of advisers, how should branches be assigned) is solvable in Excel, but the higher-level problem of where the PBAs should be located is beyond the scale of the built-in Excel solver. The case's teaching note recommends the Gurobi solver (which is available to students for free), that is controlled through a Python interface (which is on track to becoming world's most popular programming language). The (A) case presents the problem and data ""as they are."" The (B) case focuses on the descriptive analytics task of visualizing the branch locations to gain intuition. Tableau software is used with default and advanced mapping functionality. The (C) case focuses on the predictive analytics task of estimating travel times between branches. Python code for that is provided, which repeatedly calls Google Maps to obtain the travel times-a task known as the application programming interface (API). By following the A-B-C sequence, the students will have all they need to build the optimization model. With A-B, they have a lot of intuition but still need to estimate travel times. With just the A case, the situation is mostly open ended: it is up to the students to decide what to do, in addition to how to do it. The case is suitable for advanced undergraduate or MBA electives on analytics, or for fast-growing Masters in Analytics programs.

A bank manager is thinking about how to manage the new private banking advisers (PBA) practice in her region. For that she needs to determine how many PBAs she needs, where they should be located, and to which branches each of them should be assigned. This three-case series exposes students to the underlying sequence of analytical tasks, which culminate in solving an integer-programming optimization model-a main tool of prescriptive analytics. The assignment part of the problem (e.g., given the home-base locations of advisers, how should branches be assigned) is solvable in Excel, but the higher-level problem of where the PBAs should be located is beyond the scale of the built-in Excel solver. The case's teaching note recommends the Gurobi solver (which is available to students for free), that is controlled through a Python interface (which is on track to becoming world's most popular programming language). The (A) case presents the problem and data ""as they are."" The (B) case focuses on the descriptive analytics task of visualizing the branch locations to gain intuition. Tableau software is used with default and advanced mapping functionality. The (C) case focuses on the predictive analytics task of estimating travel times between branches. Python code for that is provided, which repeatedly calls Google Maps to obtain the travel times-a task known as the application programming interface (API). By following the A-B-C sequence, the students will have all they need to build the optimization model. With A-B, they have a lot of intuition but still need to estimate travel times. With just the A case, the situation is mostly open ended: it is up to the students to decide what to do, in addition to how to do it. The case is suitable for advanced undergraduate or MBA electives on analytics, or for fast-growing Masters in Analytics programs.

Formula E's season three is nearly complete. CEO Alejandro Agag needs to examine his business model to ensure the racing series is positioned to grow sustainable in the years to come.

The case starts by describing the transformation of ING Netherlands from a traditional bank with functional hierarchies to an organization that embraces digitalization and 'Agile' principles. Then it illustrates how the bank is re-organized around self-managed teams without traditional managers. Finally, the narrative recounts how employees are empowered to make decisions.

Supplement to case IN1530 and IN1533

Supplement to case IN1530 and IN1533

Supplement to case IN1530 and IN1533

Supplement to case IN1530 and IN1533

Supplement to case IN1530 and IN1533

Supplement to case W18733

Additional Supplement to accompany product 9B18A064.