Case Studies GE Tackles the Industrial Internet

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	GE Tackles the Industrial Internet

GE Tackles the Industrial Internet

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics
Applicable Industries	Healthcare & Hospitals Transportation
Applicable Functions	Logistics & Transportation Quality Assurance
Use Cases	Process Control & Optimization Real-Time Location System (RTLS)
Services	Data Science Services System Integration
Challenge	Flight dynamics change quickly. From weather to gate conflicts, efficiently adapting to changing flight conditions can save millions of dollars in annual fuel costs, as well as reducing carbon emissions. Flight Quest tackled this real-time big data analysis challenge. In Flight Quest I, participants were given multi-source flight and weather data and asked to predict precise runway and gate arrival times for domestic flights in the United States. The winners produced a 40% accuracy improvement over industry standards—equivalent to saving 5 minutes at the gate per flight (an annual savings of $6.2 million for a mid-sized airline). Flight Quest II was even more challenging: Participants optimized flights in real time. The second phase included significantly more complex weather data—rain, wind, barometric pressure, ice, and more—as well as crew and passenger counts, airport traffic, and no-fly-zones. The winning solution was evaluated in a flight simulator and found to be a 12% efficiency and cost improvement over real flights. Read More
About Customer	General Electric (GE) is a multinational conglomerate headquartered in Boston, Massachusetts. Founded in 1892, GE operates in various sectors including aviation, healthcare, power, renewable energy, digital industry, additive manufacturing, and venture capital and finance. With a workforce of over 200,000 employees, GE is a leader in industrial technology and innovation. The company has been at the forefront of leveraging advanced technologies to solve complex industrial challenges. Since 2012, GE has pursued a multi-year initiative to leverage the “Industrial Internet” of smart machines and advanced analytics. This initiative aims to integrate machine learning, big data, and IoT to optimize industrial operations and drive efficiency. Read More
Solution	GE engaged Kaggle to organize and run three competitions, offering prizes totaling $600,000 to solve high-impact business problems from flight efficiency to hospital operations. In Flight Quest I, participants were given multi-source flight and weather data and asked to predict precise runway and gate arrival times for domestic flights in the United States. The winners produced a 40% accuracy improvement over industry standards. Flight Quest II was even more challenging: Participants optimized flights in real time. The second phase included significantly more complex weather data—rain, wind, barometric pressure, ice, and more—as well as crew and passenger counts, airport traffic, and no-fly-zones. The winning solution was evaluated in a flight simulator and found to be a 12% efficiency and cost improvement over real flights. For Hospital Quest, participants developed healthcare solutions that were evaluated by experts for quality, impact, and ease of implementation. The winning team implemented a referral management system to simplify hospital discharge workflows and greatly improve the quality of post-acute care. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Applicable Industries

Healthcare & Hospitals

Transportation

Applicable Functions

Logistics & Transportation

Quality Assurance

Use Cases

Process Control & Optimization

Real-Time Location System (RTLS)

Services

Data Science Services

System Integration

Challenge

Flight dynamics change quickly. From weather to gate conflicts, efficiently adapting to changing flight conditions can save millions of dollars in annual fuel costs, as well as reducing carbon emissions. Flight Quest tackled this real-time big data analysis challenge. In Flight Quest I, participants were given multi-source flight and weather data and asked to predict precise runway and gate arrival times for domestic flights in the United States. The winners produced a 40% accuracy improvement over industry standards—equivalent to saving 5 minutes at the gate per flight (an annual savings of $6.2 million for a mid-sized airline). Flight Quest II was even more challenging: Participants optimized flights in real time. The second phase included significantly more complex weather data—rain, wind, barometric pressure, ice, and more—as well as crew and passenger counts, airport traffic, and no-fly-zones. The winning solution was evaluated in a flight simulator and found to be a 12% efficiency and cost improvement over real flights.

About Customer

General Electric (GE) is a multinational conglomerate headquartered in Boston, Massachusetts. Founded in 1892, GE operates in various sectors including aviation, healthcare, power, renewable energy, digital industry, additive manufacturing, and venture capital and finance. With a workforce of over 200,000 employees, GE is a leader in industrial technology and innovation. The company has been at the forefront of leveraging advanced technologies to solve complex industrial challenges. Since 2012, GE has pursued a multi-year initiative to leverage the “Industrial Internet” of smart machines and advanced analytics. This initiative aims to integrate machine learning, big data, and IoT to optimize industrial operations and drive efficiency.

Solution

GE engaged Kaggle to organize and run three competitions, offering prizes totaling $600,000 to solve high-impact business problems from flight efficiency to hospital operations. In Flight Quest I, participants were given multi-source flight and weather data and asked to predict precise runway and gate arrival times for domestic flights in the United States. The winners produced a 40% accuracy improvement over industry standards. Flight Quest II was even more challenging: Participants optimized flights in real time. The second phase included significantly more complex weather data—rain, wind, barometric pressure, ice, and more—as well as crew and passenger counts, airport traffic, and no-fly-zones. The winning solution was evaluated in a flight simulator and found to be a 12% efficiency and cost improvement over real flights. For Hospital Quest, participants developed healthcare solutions that were evaluated by experts for quality, impact, and ease of implementation. The winning team implemented a referral management system to simplify hospital discharge workflows and greatly improve the quality of post-acute care.

Impact #1	The winning solutions from Flight Quest I and II demonstrated significant improvements in flight efficiency and cost savings.
Impact #2	The competitions fostered innovation and collaboration among data scientists and industry experts.
Impact #3	The Hospital Quest competition led to the development of a referral management system that improved hospital discharge workflows and post-acute care quality.

Impact #1

The winning solutions from Flight Quest I and II demonstrated significant improvements in flight efficiency and cost savings.

Impact #2

The competitions fostered innovation and collaboration among data scientists and industry experts.

Impact #3

The Hospital Quest competition led to the development of a referral management system that improved hospital discharge workflows and post-acute care quality.

Benefit #1	40% accuracy improvement in predicting runway and gate arrival times.
Benefit #2	5 minutes saved at the gate per flight, equivalent to an annual savings of $6.2 million for a mid-sized airline.
Benefit #3	12% efficiency and cost improvement over real flights.

Benefit #1

40% accuracy improvement in predicting runway and gate arrival times.

Benefit #2

5 minutes saved at the gate per flight, equivalent to an annual savings of $6.2 million for a mid-sized airline.

Benefit #3

12% efficiency and cost improvement over real flights.

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Overview

GE Tackles the Industrial Internet

Operational Impact

Quantitative Benefit