modern digital business and less of a traditional manufacturer (Laudon, 2018). GE has committed $1 billion to installing sensors on gas turbines, jet engines, and other machines. GE has also committed to enabling these sensors to connect to cloud-based storage for analyzing the
Chapter 12 Case Study Questions3resulting data to identify ways to improve machine productivity and reliability. GE looks to be committed to invest and allocate resources into software and the Internet of Things (IoT) (Laudon, 2018).12-15 Describe three kinds of decisions that can be supported using Predix. What is the value to the firm of each of those decisions? Explain.GE uses Predix to support high-performance analytics which GE used to determine why jet aircraft engines were beginning to require more frequent unscheduled maintenance. A single engine’s operating data will only tell you there’s a problem with that engine. But by collecting massive amounts of data and analyzing the data across its entire fleet of machines, GE was able to cluster engine data by operating environment. The company found that the hot and harsh environments in the Middle East and China caused engines to clog, heat up, and lose efficiency, so they required more maintenance. GE found that engines had far fewer of these problems if they were washed more frequently. Fleet analytics helped GE increase engine lifetime and reduceengine maintenance. The company thinks it can save its customers an average of $7 million of jetairplane fuel annually because their engines will be more efficient. Predix’s robust data and analytics platform made it possible for GE to use data across every GE engine all over the world and cluster fleet data (Laudon, 2018).
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