Transport for London (TfL) oversee a network of buses, trains, taxis, roads, cycle hire bikes, cycle paths, footpaths and even ferries which are used by millions every day. Running these vast networks, so integral to so many people’s lives in one of the world’s busiest cities, gives TfL access to huge amounts of data – and the company are now embracing Big Data analytics in a big way.
As Lauren Sager Weinstein, head of analytics at TfL, points out: “London is growing at a phenomenal rate. The population is currently 8.6 million and is expected to grow to 10 million very quickly. We have to understand how [customers] behave and how to manage their transport needs.” With this in mind, TfL have two priorities for collecting and analysing data: planning services and providing information to customers. Sager Weinstein explains: “Passengers want good services and value for money from us, and they want to see us being innovative and progressive in order to meet those needs.”
TfL use Big Data analytics in three main ways: mapping customer journeys, managing unexpected events and providing personalized travel information. Let’s look at each area in turn.
The introduction of the Oyster smartcard ticketing system in 2003 has enabled a huge amount of data to be collected about precise journeys that are ...