Telepass, until very recently the sole processor of electronic toll payments on Italy's highways, has ambitions beyond tolling. Since the mid-2010s, the company has been expanding into adjacent services. In 2017, Telepass launched TelepassPay-a mobile payment application (app) that allows subscribers to pay for dozens of mobility-related services and products from their smartphones. In 2019, Telepass launched a car insurance brokerage service. Using Telepass data, the brokerage service offers tailored insurance products to existing customers on behalf of insurance companies for a commission on converted leads. Now, in September 2020, Telepass's senior leaders are considering a new, insurance-related growth opportunity: moving beyond the brokerage model to become the primary insurance seller. It is unclear, however, whether Telepass's data provides sufficient insights into individual drivers' risk profiles to build competitive, customized insurance products. Alternatively, Telepass could continue to improve the brokerage model and focus its resources on adding new mobility services to TelepassPay. This case is paired with a supplementary dataset (courseware no. 622-701), which provides a data analysis opportunity for students.
Telepass, until very recently the sole processor of electronic toll payments on Italy's highways, has ambitions beyond tolling. Since the mid-2010s, the company has been expanding into adjacent services. In 2017, Telepass launched TelepassPay-a mobile payment application (app) that allows subscribers to pay for dozens of mobility-related services and products from their smartphones. In 2019, Telepass launched a car insurance brokerage service. Using Telepass data, the brokerage service offers tailored insurance products to existing customers on behalf of insurance companies for a commission on converted leads. Now, in September 2020, Telepass's senior leaders are considering a new, insurance-related growth opportunity: moving beyond the brokerage model to become the primary insurance seller. It is unclear, however, whether Telepass's data provides sufficient insights into individual drivers' risk profiles to build competitive, customized insurance products. Alternatively, Telepass could continue to improve the brokerage model and focus its resources on adding new mobility services to TelepassPay. This case is paired with a supplementary dataset (courseware no. 622-701), which provides a data analysis opportunity for students.
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case.
Lexoo, a UK-based online marketplace for legal services, was facing the strategic choice of how to grow from early start-up to mature platform. Daniel van Binsbergen, Lexoo's CEO, and web developer Chris O'Sullivan, CTO, had set up Lexoo to help Small and Medium-Sized Enterprises (SMEs) to find legal advice at low prices. At the time of the case in 2018, Lexoo had just started attracting larger companies in need of specialized legal advice as new customers. Larger companies had higher value and more frequent needs. Lexoo could become their "go-to" place across a broad range of legal services. Nevertheless, larger companies also required a more personalized approach and were more difficult to acquire than SMEs. Van Binsbergen and O'Sullivan were debating whether Lexoo should diversify to serve both SMEs and larger companies, or whether to pivot their focus toward larger companies altogether.
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust secondary market that bore similarities to the stock market. Inspired by these similarities, StockX's co-founders created a secondary platform that tracked sneaker resale prices over time and that emphasized authenticity, anonymity, and transparency. In 2017, StockX began to experiment with ways to expand from the secondary market into the primary market, using a new type of online auction known as an initial product offering (IPO). Based on the results of its first IPOs, was StockX on the right track with its strategy to expand into the primary market?
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust secondary market that bore similarities to the stock market. Inspired by these similarities, StockX's co-founders created a secondary platform that tracked sneaker resale prices over time and that emphasized authenticity, anonymity, and transparency. In 2017, StockX began to experiment with ways to expand from the secondary market into the primary market, using a new type of online auction known as an initial product offering (IPO). Based on the results of its first IPOs, was StockX on the right track with its strategy to expand into the primary market?
The supplementary dataset (courseware number 619-702) provides a disguised dataset to students. At the end of the case, summary data from that dataset is mentioned. (Bottom of page 13: Rahematpura, who had been running numbers, interjected: "According to some back-of-the-envelope calculations, by not increasing wait times now, we stand to lose $1.6 million in the six launch cities. That might outweigh the data collection concerns.")
Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This product offers a reduced price to riders willing to carpool, walk a short distance to/from their pick-up and drop-off points, and wait a few minutes before being matched to a driver. Two weeks after the launch of Express POOL in six U.S. cities, Uber's product managers discover that if riders are made to wait five minutes to be matched to a driver-rather than the standard two minutes-rider cancellation rates increase, but Uber's costs per ride are reduced. Together with data scientists, engineers, and product operations specialists, the product managers must decide whether to keep rider wait times at two minutes or increase wait times to five minutes in the six newly launched cities. The decision is complicated by the fact that Uber's data science team normally places a five-week moratorium on changes to any new product, to allow robust data to be collected on its performance. This case is paired with a supplementary dataset from Uber (HBS No. 619-702). In advance of the class discussion, students can analyze the data and draw their own conclusions about the trade-offs of maintaining the standard wait times or increasing them.
Lexoo, a UK-based online marketplace for legal services, was facing the strategic choice of how to grow from early start-up to mature platform. Daniel van Binsbergen, Lexoo's CEO, and web developer Chris O'Sullivan, CTO, had set up Lexoo to help Small and Medium-Sized Enterprises (SMEs) to find legal advice at low prices. At the time of the case in 2018, Lexoo had just started attracting larger companies in need of specialized legal advice as new customers. Larger companies had higher value and more frequent needs. Lexoo could become their "go-to" place across a broad range of legal services. Nevertheless, larger companies also required a more personalized approach and were more difficult to acquire than SMEs. Van Binsbergen and O'Sullivan were debating whether Lexoo should diversify to serve both SMEs and larger companies, or whether to pivot their focus toward larger companies altogether.
The case examines how Marriott should respond to the potential threats from new home-sharing platforms and the rise of on-line travel agencies. In 2017 Marriott was the largest hotel chain, with more than one million rooms and 7% of worldwide room supply. In the previous decade the growing ubiquity of internet-based commerce had facilitated the rise of technology platforms such as Expedia and Airbnb. The case enables students to explore the forces that might lead to industry transformation and the appropriate response strategies of a large incumbent.