The best interventions

Data can help ensure that resources are directed to the right travel behaviour change programmes, writes Tony Duckenfield

Smarter TravelStyle is used by Steer Davies Gleave to target behaviour change projects. It classifies the population and postcodes into 10 segments based on travel and behaviour change characteristics

Smarter TravelStyle is used by Steer Davies Gleave to target behaviour change projects. It classifies the population and postcodes into 10 segments based on travel and behaviour change characteristics

One of the outcomes of the Local Sustainable Transport Fund (LSTF) is that a substantial body of evidence now exists highlighting the factors that contribute to a successful travel behaviour change programme. What emerged is the importance of targeting interventions where they are most likely to have an impact. But how can this targeting be achieved, and what impact does successful targeting have?

Good targeting pays off

One of the very clear and consistent messages from the recent round of LSTF funded projects is that the outcomes vary substantially from place to place, as well as between one type of intervention and another. 

For example, when Steer Davies Gleave reviewed the six Personalised Travel Planning (PTP) projects we had undertaken in 2013 we found that the location with the greatest change achieved five times the car use reduction compared with the location with the least change. 

When we analysed the differences we found that around half were due to each area’s demographics. Another key influence was the quality of the available alternatives to car. In each case the intervention was the same, although there were some local differences in the application of the PTP.    

The economic benefits of targeting are reflected in the reduced cost per car trip (or km) eliminated, or cost per additional mile by active modes. So, for example, in our review of the cost effectiveness of PTP projects we undertook in 2014 the costs varied to the extent that the cost per additional active travel mile of the most cost-efficient project was 20% of that of the least cost-efficient. In other words, by targeting the right area it is possible to increase the impact of PTP by a factor of five, for the same cost. This is particularly relevant in the current funding climate since it means that by applying the lessons from the LSTF funded projects the same kind of change can be achieved with a much reduced investment. 

Another benefit is the ability to direct efforts where they will have the greatest impact on the specific objectives of the programme. These objectives can be more than just a reduction in car trips or they could include improved access to jobs, reduced social exclusion and improved activity levels and the associated health outcomes.

Identifying good locations

The concept of targeting is all very well, but how do you know in advance which is the right area to target? Fortunately, we now have an extensive body of evidence obtained from monitoring our behaviour change projects that enables us to identify locations more susceptible to particular interventions. 

Conversely, the same lessons can be used to identify, given a particular locality, what the most effective interventions would be. 

One way in which we are able to apply the lessons from previous projects is through some bespoke tools we have developed, particularly Smarter TravelStyle. This is a geodemographic classification system that is appended to data on travel behaviour and behaviour change from more than 20 projects. 

Geodemographic-based targeting systems are more powerful than simpler approaches, such as those based on age or social group. 

These geodemographic profiling and targeting systems are only part (around half) of the answer to targeting. Amongst the other factors are the quality of the public transport network and the facilities for cycling and walking. 

The factors that ‘push’ people out of their cars, such as road congestion, are worth noting. Again, there is data available to assess this – we use TomTom data, but this isn’t the only source.

This is now the age of data, not just ‘Big Data’ but a range of different sources that can be turned into practical tools for making decisions – in this case, decisions on where to do what in terms of travel behaviour change. 

Tony Duckenfield is head of insight, Steer Davies Gleave