As it did with Six Sigma for process improvements in the 1990s, GE is setting a precedent for manufacturers globally with its Industrial Internet initiative. The company is making a significant commitment to big data analytics to participate in cloud, mobile and social megatrends that are impacting every sector of the economy. Is big data analytics GE’s new Six Sigma?
During the past two years, GE has hired nearly 300 data scientists and software engineers, with plans to increase that workforce to 400 by 2014 as part of a $1 billion investment. That commitment was accelerated by the surprise announcement that GE made a $105MM investment in EMC spin-out Pivotal, which is comprised of assets from VMWare and its parent EMC.
GE plans to take advantage of Pivotal’s cloud management, analytics and application development platform to capture, correlate and analyze sensor data from its products to achieve cost savings and productivity gains through better decision analytics. Like other global manufacturers such as Honeywell, Emerson Electric and Siemens, GE has been installing smaller, more powerful and cheaper sensors on every product it makes across all of the industries it competes in, including aircraft engines, gas turbines used in power plants, rail locomotives, HVAC (heating, ventilation, air conditioning) systems and medical diagnostic equipment.
As an example of the potential, Boeing reports that jet engines generate 10 terabytes of operational information for every 30 minutes they turn. A four-engine jumbo jet can create 640 terabytes of data on just one trans-Atlantic flight. Multiply that by over 25,000 flights each day, and one can understand the impact that sensor and machine-produced data can have.
GE’s Silicon Valley team will collaborate with Pivotal on research projects for industrial applications. At the announcement of its Pivotal investment, GE CEO Jeff Immelt said, “It’s about smart machines, big data and analytics, and mobile workforces, and those coming together for airlines, utilities, oil and gas companies, and healthcare providers to provide great applications like no unplanned downtime, asset optimization and enterprise optimization”.
By gathering and analyzing machine data generated by its products, the company can realize significant improvements in product design, performance and support services. GE estimates that across all of its industrial products, efficiency gains can amount to $150 billion. As was the case with its Six Sigma initiative in the 1980s, we expect more manufacturing industries to follow GE’s practices in machine data analytics.
