Alf Cherry

CIO, Commercial Engines & Services , GE Aviation

Supernova Award Category: 

Data-Driven Digital Networks (DDNs) and Business Models

The Organization: 

GE Aviation (GEA) is a world leader in providing aircraft engines, systems, and avionics. We rise to the challenge of building a world that works.

Having recently celebrated 100 years of leadership in the Aviation industry, GEA has over 65,000 military and commercial engines in service (pre-COVID). With its global partners, GE has built the world's largest operational engine fleet and established a firm business foundation. GEA has more than 80 facilities across the globe, with customers and operations in 130 countries.

The Problem: 

GEA is a world leader in providing aircraft engines, systems, and avionics. The installed base of commercial aircraft engines from GEA and its partners has grown significantly over the past two decades. Today's aircraft engines, equipped with sensors, have the ability to generate considerable quantities of data as they fly. The performance & availability of these engines is critical to airline customers. Any disruption to flights negatively impacts their revenue, support costs, & customer loyalty & satisfaction. As the engine OEM, GEA must ensure that its customers' engines remain in excellent condition so as not to negatively impact airline operations, financials, or the safety of passengers and crew. Turning data generated by engines into insights to help customers achieve safe and stable operations is a key component of GEA's business model.The size of GEA's installed base of engines, the amount of data generated by these engines per flight, the sophistication of the analytics (through a significant investment in Data Science), and customer reliance on GEA to support its operations, were all growing exponentially at the same time. As a result, the legacy diagnostics and analytics platform that GEA was running for the last 10 years, built on a physical infrastructure model, was neither scaling effectively nor performing to requirements. It was also not meeting the needs of stakeholders within GE or airline customers.

The Solution: 

GEA required an analytics platform to 1. Satisfy the growing appetite for information from stakeholders 2. Support the increasing volume & complexity in analytics data with the size of its fleet.To deliver , GEA built a next gen analytics ecosystem consisting of products called RUDR Data Parser, SOAR, LDP & FMX .These products work together to gather real-time engine performance data, run rapid engine diagnostics & make maint. recommendations often before a plane takes off.Due to the platform's modern architecture & cloud-based infra, GEA seamlessly processes an impressive variety of data: structured, unstructured image & video data, even environmental & mfg. data. This enables data scientists to develop significantly differentiated outcomes.Hence, a dedicated team ~ 100 GE employees & contractors worked for 2+ years to develop a platform that leverages the latest in cloud. The team applied Agile while embracing the Lean concept of Kaizen.

The Results: 

Enabled by this dynamic diagnostics and analytics ecosystem, GE Aviation was able to develop solutions driving significant benefits for airline customers. The result of using the GE analytics platform for one significant operator in the Middle East was:

56% decrease in operational engine disruptions

15% decrease in overhauls

12 additional days of utilization (per engine, prior to service removal)

When aggregated across the fleet, this ecosystem was able to drive:

32% shorter lead time to deliver analytic insights / notifications to customers

Fleet coverage increase to 56%

Increased accuracy (true positives by +33%)


Data processed from 1.5M flight records per week – 1.5 TB of data processed through SOAR each year. 42k+ engines monitored 24/7. 150+ analytics running on two new, cloud-based analytic runtimes

150K annual alerts to 9K industry stakeholders; 17k annual notifications to customers

1,000+ unplanned engine events avoided, worth ~$80MM in customer cost avoidance

The Technology: 

The nextgen analytics platform was built on AWS. Technologies will be abandoned in favor of having the analytics ecosystem on AWS, allowing data to flow into other downstream digital products to ensure flight analytics drives value through the entire Aviation Commercial franchise. This platform will train & run advanced ML models at scale.The spectrum of these algorithms includes neural net models, probabilistic graph models, time eries, NLP & deep learning models.

Disruptive Factor: 

GE's ability to monitor and provide critical insights to customers is a differentiator for its products and services, and a key piece of the businesses’ go-to-market strategy.  With over $200B in services contracts in their backlog, the ability to delight customers, understand operational dynamics, and ensure the right service products, technology, and cost-levers are available is critical to the long-term viability of the business.

Shining Moment: 

In addition to the outcomes and metrics listed above, a key shining moment was when the new diagnostics and analytics platform was patched with zero downtime.  Historically, a similar patching exercise resulted in hours of platform downtime, during which the flow of engine performance data was halted.

About GE Aviation

The Commercial Engines and Services Digital Technology org helps GEA invent the future of flight. The team uses pillar techs such as, SAP, and AWS to create a connected digital & data ecosystem to manage an installed base of ~42K commercial engines, $14B+ of annual revenue, 15 MRO Service shops, and a contract backlog of ~$200B.