The regional usage profiles aggregate data to show the number of passenger journeys within a region and to/from that region. They provide a fascinating insight into changes in travel patterns within Britain and are sufficiently detailed to show (for example) that although the increase in the number of journeys to outside the West Midlands area had slowed to its lowest level in a decade at 3.9%, travel to London and the North West from the West Midlands grew by 5.1% (2013-14 figures). Even more forensically, it can show remarkable localised spikes, such as a 17.8% increase in journeys starting or ending in Bridgend.
ORR also publishes data on station usage, collated by Steer Davies Gleave.
Much of this data is derived from LENNON (Latest Earnings Networked Nationally Over Night), the settlement system managed by the Rail Settlement Plan on behalf of train operators. The matrix covers roughly 2,500 stations. LENNON allocates revenue from the previous day’s transactions to the TOCs, but its data also allows MOIRA (a modelling tool to forecast the impact of service changes) to create a picture of daily average flows and allocates them to particular trains, thereby giving a picture of how full they are.
Looking beyond the rail sector at all modes of transport is the DfT’s National Travel Survey (NTS), a household survey begun in 1988 and designed “to monitor long-term trends in personal travel and to inform the development of policy”.
The survey collects information on how, why, when and where people travel, as well as factors affecting travel such as car availability and driving licence holding. The data is collected by face-to-face interviews with people in their homes and from a seven-day travel diary. It covers people in all age groups, including children.
It is from the NTS that the modal split can be evaluated - most recently it has shown the continuing strong growth in rail travel, greater modal share of public transport generally, plus a fall in the annual mileage of cars, which has encouraged debate over the notion of ‘peak car’. Although it has been suggested that the data is not analysed as extensively as it could be, the NTS is used to forecast patterns of travel and in transport modelling - for example, in looking at the siting of HS2 stations and their catchment areas.
Supplementing the NTS are reports such as On the Move: Making sense of car and train travel trends in Britain, commissioned by the ORR, the Independent Transport Commission, Transport Scotland and the RAC Foundation.
Its object was “to identify the patterns of behaviour which underlie the observed national levelling off in car traffic in Great Britain - after decades of growth - and the continuing strong growth in rail passenger mileage, even during the current recession”. Its analysis was based largely on the NTS and therefore its remit excluded causality.
Regional organisations also add to the store of information about travel behaviour. For TfL’s London Travel Demand Survey (LTDS), 8,000 households are randomly selected to complete three questionnaires: household (giving demographic information such as vehicle ownership, income and housing tenure); individual (covering use of transport modes, driving licences, public transport tickets); and trip sheets for each household member aged five and over (detailing the mode, end points, duration and purpose of each trip). It is interviewer-led because it was found that without occasional prompts, people would forget making certain journeys.
Transport Scotland extracts the transport and travel-related questions from the Scottish Household Survey to produce Transport and Travel in Scotland. This looks at trends, echoing the NTS in recording a reduction in car traffic and significant increases in rail passengers and cycling (2013). The annual Scottish Transport Statistics are accompanied by some imaginative infographics.
Finally, there are the external sources of data that are of value to the railway.
At a Smarter Travel Forum organised by the Campaign for Better Transport, O2 showed work it had done examining smartphone data. The project aggregated what O2 calls the ‘exhaust emissions’ from the phones, to discern travel patterns between Edinburgh and London. They revealed that rail had a 25% market share and most of the rest was air, but the 25% was split - 17% travelled with East Coast, but 8% drove to Carlisle to pick up Virgin. Mapping of such clusters provides evidence for targeted marketing campaigns. ‘Big Data’ has the potential to play a significant role in planning changes to services and creating better networks.
The second type of data is qualitative, usually obtained either by email or face-to-face questionnaires, and which seeks to discover passenger perceptions of their journey experience. A network-wide approach is used by Passenger Focus, which consults more than 50,000 passengers a year to produce biannual reports from a representative sample of journeys on all franchise TOCs, with voluntary data contributions from four open access operators.
PF’s National Rail Passenger Survey (NRPS) gives a picture of trends on a variety of factors that influence a passenger’s experience, such as punctuality, cleanliness, seat availability, helpfulness of staff, station facilities and information. And it provides TOCs with pointers for action. For example, the autumn 2014 study highlighted yet again the high level of dissatisfaction with the way TOCs handle delays or cancellations. More usefully, it dug deeper and found that while the information before arrival at stations and once at stations is trusted, there is a low opinion of on-train information and automated announcements in particular.
However, while this gives TOCs a sense of whether aspects of their service are improving or deteriorating, it is of limited value when seeking an understanding of more local assessments. Consequently most TOCs carry out additional, more targeted research.
The Southern and Southeastern TOCs within the Go-Ahead Group, which also encompasses London Midland, Gatwick Express and GTR (Govia Thameslink Railway, taking in Thameslink and Great Northern), use the free online survey software SurveyMonkey to devise customer surveys to gain a deeper insight. Obviously this can only be done with those customers who have accessed those TOCs online, but surveys can be targeted to a specific station or area. These surveys often focus on the quality of information provided by the TOC and whether the right communication channels are being used.
To gain a wider picture of their customers and non-rail users, Southern and Southeastern use YouGov to hold online panels. These gather data on quality of service, perceptions of value for money, brand, fares, cleanliness and staff helpfulness, and examine the reasons why people do not use rail. Although comparable with PF’s NRPS, these surveys are more frequent and more detailed. They also provide socio-demographic information that helps a deeper analysis of their findings.
The third type of data, and the one that offers perhaps the greatest scope for innovation, surrounds ticketing and the information that sophisticated forms of ticketing provide about customer behaviour.
The Edmondson ticket and its thinner card successors provided the railway with no information except origin and destination. Season tickets, introduced as early as the 1830s on the Stockton & Darlington Railway, provided the first contact with passengers on a regular basis, although little more than address and gender would have been available. But it was the development of computer-based ticketing systems that laid the foundations for the data revolution.
