In November 2017, Students for Fair Admissions Inc. filed a complaint alleging that Harvard College violated Title VI of the Civil Rights Act, which prohibited racial discrimination in institutions that received federal funding. The complaint alleged that Harvard College engaged in intentional discrimination against Asian American applicants in its admissions process. Harvard College acknowledged its use of race in the admissions process but maintained that it was only one of many factors the school considered. It also claimed that using race as a “plus factor” was supported by the law. Both sides used a large set of data to plead their cases and both hired econometrics experts to argue their positions, who reached opposite conclusions. The trial judge needed to assess the two experts’ findings and reach a decision about the story the data was telling.
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.
In December 2022, after the independent film distributing company levelFILM Inc. experienced several box office failures, the company’s manager of sales strategy was wondering if the company needed to re-examine its portfolio strategy. Based in Toronto, Ontario, levelFILM Inc. operated in the highly uncertain film industry, in which it was almost impossible to predict how any one film would perform at the box office. The various distributors in the industry employed different strategies for managing risk, including building a large diversified portfolio of projects or pursuing a blockbuster strategy with heavy investment in fewer projects. The company’s manager was wondering which strategy would be most appropriate for levelFILM Inc. and how he might use extensive historical data that he had available to determine optimal risk management and investment returns options for the company.
Maya Fonseca, the marketing analyst for video streaming service FilmCast, and her colleague Rupert Cruz had to interpret the results of a conjoint analysis conducted by their company. FilmCast was a large company, competing against Videosource and Webflickstream. The marketing analysts were debating whether it made sense to lower the price of their services and if the conjoint analysis results supported this idea.
Technology is advancing at a rapid rate, changing various aspects of our everyday lives. Businesses and governments are trying to adapt to this change by embracing positive aspects, while remaining attentive to negative aspects. This note focuses on technologies such as artificial intelligence, machine learning, and big data, considering the ethical issues that these technologies create within our society and also how these ethical issues are being addressed.
An actuarial intern at World Reinsurance Company was casually checking his e-mail and noticed that he had received a request from his manager to develop a quote for an upcoming request for proposal from one of World Reinsurance Company’s larger clients, Ontario Life. The request for proposal would have to contain a quote for an excess-of-loss policy to reinsure Ontario Life’s 10-year-term life insurance policy, consisting of 100 high-risk policyholders, for retention limits over CA$250,000 on a per-loss basis. The quote was to be submitted for review by the end of the day, so the intern had to get started on it immediately.
An investment manager at Glitz Investments, a firm based in the United States with a focus on the entertainment industry, wanted to identify potential blockbuster movies in the Indian film industry for the firm’s potential investment purposes. The investment manager received a report compiled by analysts at the firm indicating that Bollywood would be an attractive industry for investment. The firm’s analysts had collected data but could the manager determine a quantitative relationship between box office performance and the factors the team had identified? Could Glitz Investments choose movies based on this analysis alone? The investment manager's boss was looking for more specific data on which to base the firm’s investment decisions.
In April 2020, amid the global pandemic resulting from the spread of Covid-19, the president of the Broadway League, which represented theatre owners, producers, presenters, and general managers for Broadway and across North America, faced a challenge. On March 12, 2020, Broadway had suspended all plays and musicals. The president and her team needed to determine when Broadway might be able to reopen, what the Broadway League should be communicating to producers and guests, and what the reopening of Broadway would look like amid the global coronavirus pandemic. However, to reach these decisions, she first needed to determine the reliability of the recently released New York State antibody study and estimate the true prevalence of antibodies in the population.
In December 2019, a member of a fantasy hockey league had to decide whether to trade away his top talent in exchange for draft picks in the following year’s fantasy draft or to continue to compete for a position in the playoffs. If he traded his top players, he would forfeit his chances at competing for a championship; however, this move might put his team in a better position for the following year’s fantasy hockey season. He had access to the league’s historical data to help determine the likelihood of his team making the playoffs. He wanted to conduct an analysis to make an informed decision grounded by numbers.