Big Data Can Save Billions in Transportation Delays

Viewed as a cohesive machine, the Earth’s transportation infrastructure is a smoky, inefficient bumbling mess. Lots of people get where they need to go every day, but with more delays and mishaps than necessary. Airport delays alone cost the U.S. economy $6 billion annually. But a report from McKinsey and Company says that increased use of big data could save the world economy $400 billion annually without building any new infrastructure.

Using data to influence human behavior in ways that reduce strain on the world’s infrastructure can be found in many replicable projects today. 

Israel, for instance, uses real-time pattern recognition on Highway 1 found between Tel Aviv and the Ben Gurion Airport to adjust tolls according to traffic congestion, increasing throughput.

Brazil uses GPS data analysis to optimize its limited airspace, fitting more airplanes in the air and shortening routes, according to the report. Enabling many different airlines to share the air without wasting large swathes of unused airspace means air traffic controllers must know the capabilities and routes of each aircraft, requiring a diverse and complex set of data.

Some European railway operators use big data to make more efficient use of their track capacity. By attributing tracks and trains different speed profiles, delays can be side-stepped by allowing trains to swap positions on the itinerary. Operational innovations like these can increase railway traffic capacity by 10 percent, according to the report.

By increasing data transparency, aligning goals across organizations and reducing regulatory barriers, the report states, big data can lead to big savings for the entire world, both in money and time saved.