Every day about 24 million journeys are made across Transport for London’s (TfL) network. The public sector organisation manages London’s buses, the Underground, Docklands Light Railway, Overground and Tramlink, as well as Barclays Cycle Hire, London River Services and the Emirates Air Line.
It has to support just short of 30,000 people internally who use TfL services and it employs 517 full-time IT staff, with up to a further 300 who can be contracted to the organisation at any time. Now, more than ever, the organisation needs to make sure that its employees are making the most of the huge volumes of data at their disposal.
According to TfL’s CIO Steve Townsend, the firm is now ready to exploit that data, something that it hasn’t done before because the organisation failed to realise how powerful the information was.
“We’ve got an awful lot of data within TfL, much of which is shared, but we don’t necessarily exploit the information to the full within the organisation,” he says.
For this to change, TfL has selected Tibco’s services to bring together all the data across the organisation with its XIS platform.
“We want to be able to store and make it available across the organisation, whether you’re looking at congestion between stations, locations or buses or activity of Oyster card users,” he states.
In the past, departments – such as road space management – had never shared data with other departments like the London Underground. But Townsend believes that if these data sources were brought together, it could mean that better decisions could be made across the organisation.
And sharing this data internally could also open up new avenues externally, for both developers and advertisers.
TfL currently shares much of its data with the London Data Store, which is popular for developers who want to create apps for smartphone and tablet devices, and it hopes that more information will enable the travelling public to make better decisions for their journeys thanks to the apps that developers can release for smartphones.
Data analysis, meanwhile, should mean that TfL’s contractors are better prepared to sell advertisements across London, said Townsend.
“Through analysing some of the data we’ve got, without knowing who it is, but how many people you’ve got in a particular station, travelling down a particular corridor at a particular time of the day, advertisers could look at that and say ‘we will advertise our product because we know that’s a popular spot, and we can do it at different times of the day’,” he suggested.
Townsend believes that when this information is combined with Oyster data, and data from TfL’s Wi-Fi network, he will be able to build an accurate picture of traffic flow, not just on the Underground but across the whole of London.
His organisation will then be able make better decisions on when and where its staff should be deployed to help with maintenance works, for example.
Townsend said that during the recent industrial action, data enabled TfL to predict which stations would be busiest and the number of train drivers it needed for the day. It also uses data in the same way for big events such as the Tour de France and the Olympics.
TfL’s web analytics team uses a combination of in-house and third-party software, much of which is focused around end-user experience rather than data modelling.
“We want to make sure data is presented so it can be absorbed in the best possible way,” Townsend explains. “So, for example, one of the providers we are using is an organisation called ‘We Are Experience’, who help with the presentation of information and our application design”.
Managing data flow in the back end
TfL has been a SAP-based organisation for many years – with its core ERP services all provided
by the German software giant.
The company is currently exploiting SAP’s HANA in-memory analytics platform.
“We’re using it because there is so much data [and if we could] manage it in real time, it could help this organisation make different decisions and outcomes,” Townsend said.
But he insisted that he would not take a “big-bang approach and throw HANA across the organisation” because TfL needs to fully understand how it can drive value out of the platform first.
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