Research Highlight

Internet of Things in Motion: Analytics and Transportation

Vast amounts of data are being analyzed to literally help trains run on time. With digitization capturing data on everything from the weight of connected rail cars to the quality of tracks to the terrain trains are traveling through, railway companies are now able to predict when breakdowns might occur and fix those trains proactively. The results are breathtaking: nearly 100% availability of operational trains.

Gerhard Kress and Bruce Posner Reading Time: 6 min 

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As director of Mobility Data Services for Siemens, Gerhard Kress literally helps the trains run on time. Specifically, he and his team of data scientists work to keep European trains and rail schedules operating at the most optimum levels.

As an example, Kress’ team has worked with the Spanish national railway, Renfe, with a goal of ensuring on-time operations on the high-speed rail line between Madrid and Barcelona. The rail trip takes two and a half hours, and it competes with air flights of about an hour and twenty minutes. Renfe upped its ante by promising train passengers a complete refund if the train is delayed by 15 minutes or more. Kress’ team helped Renfe achieve nearly flawless service, with only one major delay in 2,300 trips. Other rail clients for Siemens’ data services include the Bangkok Metro, the Russian rail service between Moscow and St. Petersburg, and trans-European Eurostar service.

Kress’ task in the digital transformation of rail service is to identify the right kinds of data and then use it to manage better. Kress’ team keeps track of trains in real time (including details on mileage, how elements such as brakes are working, the behavior of compressors, the weight of connected rail cars, and the status of automatic control processes), forecasts wear and tear on components (based in part on the quality of the rails, the terrain trains are traveling on, and weather conditions during operation), and — crucially — predicts when breakdowns might occur. The data team builds maintenance scheduling around its data, helping to ensure that service teams are ready with a full array of information and a prescriptive plan for what maintenance to perform when trains arrive at service centers.

Siemens is one of the world’s largest producers of energy-efficient technologies, with customers in power and gas, healthcare, and financial services. Based in Germany, the company focuses on automation and digitalization. As of September 30, 2015, Siemens had around 348,000 employees in more than 200 countries, with revenues in fiscal 2015 of €75.6 billion.

On April 26, 2016, MIT Sloan Management Review hosted a webinar, made possible with sponsorship support from Teradata, with Kress. He talked how his team wrangles so much information — a fleet of 100 modern rail cars produces between 100 to 200 billion data points annually — and what lessons his experience provides for others.

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About the Authors

Gerhard Kress is director of Mobility Data Services for Siemens, where he oversees a team of 30 data scientists. He has been with Siemens since 2002. Bruce Posner is a senior editor at MIT Sloan Management Review.

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