Analytics Is the Ticket for a Better RideBy Samuel Greengard Print
Big data analytics beckons with the promise of making life easier and better. A prime example is public transportation, which often disrupts people's lives.
It's difficult to ignore the near-constant buzz over analytics and big data. Discussions about it permeate enterprise strategy meetings and fill the pages of publications. And for good reason.
These technologies open the door to a far greater understanding of business conditions and customers. In some cases, this takes an organization to a place that would have been unimaginable a decade ago.
But analytics also beckons with the promise of making life easier and better for society. A prime example is public transportation. In today's world, buses and trains too often run late, people miss their connections and, as a result, riders wind up wasting huge amounts of time and effort getting from Point A to Point B. Recently, for example, the Long Island Railroad experienced three major disruptions in eight days.
However, if an operator could better coordinate individual trains, buses and boats, possibilities begin to emerge.
Using Big Data to Forecast Train Disruptions
One organization taking direct aim at the problem is Stockholmståg, the commuter train operator for Stockholm, Sweden. It has built a predictive model that uses big data to visualize the entire train network two hours into the future. By forecasting disruptions, it keeps passengers better informed, while avoiding the ripple effect that contributes to most delays.
Of course, any problem or delay rapidly multiplies over an entire transportation network. In some cases, it can even spill over to roadways. The holy grail of transportation is to introduce a connected and smart grid that can reduce congestion, reduce fuel consumption and increase safety.
In Stockholm's case, "The 'commuter prognosis' works like a seismograph," explains Mikael Lindskog communications director at Stockholmståg. "When a train runs late, the algorithm uses historical data to forecast the risks of delay and how it affects the entire network."
This allows operators at a control center to adjust schedules or add trains, when necessary. In some cases, adjustments may occur automatically. The system, which is about to go live, uses a mathematical model that sifts through big data to build real-time forecasts for each train in the network.
Stockholmståg invented the algorithm that drives this system by working with mathematician and data scientist Wilhelm Landerholm. The algorithm can be adapted for use with other public transportation modes in other cities in the future. Commuters can access updates and other data via a smartphone app.
Let's hope that government agencies, businesses and others will work together to build smarter transportation networks. Analytics is clearly the ticket to a better future.
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