Google Skybox: Monitoring Planet Earth in High Definition

Google Skybox designed and managed small satellites that captured high-definition images of the Earth's surface. The company then sold the images or the analysis of the images to commercial and government customers.<br><br>The founders initially intended to use the satellites for societal purposes, such as monitoring carbon emissions, but quickly refocused on profit-making applications when they realized that the viability of the project depended on the ability to sell products to commercial customers. Over time, the company has been increasingly diverging from its original purpose. The dilemma facing the founders is how to do the right thing, but also make a profit.

The case exposes students to the privacy and ethical concerns that can arise when working with massive data sets. The case illustrates that successful data analytics projects depend not only on the capabilities of technical solutions and good business strategy but also on the adherence to proper ethical standards. Students take the roles of executives and data analysts of Skybox (recently acquired by Google) and discuss business model and ethical considerations of mining imaging data collected from a new generation of highly capable satellites. Learning objectives include the following:<ul><li>Gaining knowledge about the right to privacy in the digital age.</li><li>Understanding the differences between data sources, specifically between volunteered and contributed data.</li><li>Developing guidelines for the ethical use of contributed data.</li><li>Examining key strategies to ensure privacy concerns are addressed adequately.</li><li>Analyzing and evaluating data-driven business strategies and understanding how to acquire and sustain competitive advantage from data analytic capabilities and data assets.</li><li>Examining how to build a business around some analysis capability, how to profit from accumulated data and how to sell predictive analytics as a product; determining viable “big data” business models</li></ul>

• Big data
• Operations analysis
• Ethical issues
• Generating profit from new technology