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Case HBS Case Collection November 2019 DeepMap: Charting the Road Ahead For Autonomous Vehicles |
Founded in 2016, DeepMap developed high definition (HD) mapping software and localization services for Level 4+ autonomous vehicles. Traditional navigational maps were accurate to a few meters, which was sufficient for drivers, but not for machine-driven vehicles which required centimeter level accuracy. Autonomous vehicles required a new form of map that was highly precise, produced a 3D representation of the surrounding area, enabled vehicles to locate themselves within the map, provided information for how to navigate safely using the correct rules of the road, and was updated continuously as road conditions changed. DeepMap was not selling a static mapping database, but rather licensing its software under a software-as-a-service model. As a startup with limited resources navigating a nascent market, DeepMap faced uncertainty across several dimensions: the timing of overall AV market adoption, which countries would adopt fastest, which AV segments would move most rapidly, which sensor technologies would become standard, and what impact regulation would have. They also faced the challenge of serving customers on a global scale. As DeepMap looked ahead, it had to decide how and where to focus and allocate its funding in order to achieve its short and long-term objectives.
Keywords: mapping software; autonomous vehicles; Business Startups; Software; Technological Innovation; Technology Adoption; Service Delivery; Global Range; Resource Allocation; Strategic Planning; Technology Industry; Auto Industry;
Greenstein, Shane, and Nicole Tempest Keller. "DeepMap: Charting the Road Ahead For Autonomous Vehicles." Harvard Business School Case 620-047, November 2019.
