Disney+ and Machine Learning in the Streaming Age
Machine learning has been used to create value in various ways across a broad swath of industries. In this case, students will explore uses for machine learning in the context of the launch of the Disney+ streaming service in November 2019. At the time of the case, Disney already operated two streaming platforms, Hulu and ESPN+. Its new streaming service would launch with an archive of roughly 7,500 TV episodes and 500 films, including wildly popular titles from Marvel, Star Wars, and Pixar. Yet Disney+ would be entering an increasingly competitive industry dominated by Netflix. Since its pivot from mail-order video to streaming in the early 2000s, Netflix had extensively used machine-learning algorithms to optimize customer experience and retention.
In this case, students will assume the (fictitious) role of Margaret Gupta, a senior data scientist, as she ideates machine-learning use cases for Disney's management team. In addition to background information on Disney and Netflix, the case provides students with basic information on use cases and data sources for machine learning. The overarching goal is to give students a general understanding of how machine learning works, learn to recognize potential use cases from a managerial lens, the data required to fuel it, and the possible sources of bias that can arise from that data.
Kevin McTigue, Theo Anderson
AI and machine learning, Algorithms, Analytics and data science, Data science, Data-driven decision making, Digital marketing, Digital strategy, Marketing, Marketing analytics, Statistical bias
McTigue, Kevin, and Theo Anderson. Disney+ and Machine Learning in the Streaming Age. Case 5-123-001 (KE1251).PREVIEW or BUY