MAST conference focuses on Contributory Factors analysis

12.00 | 18 March 2014 | | 5 comments

The fourth annual MAST Conference once again attracted a wide range of road safety professionals from across the country to look at new trends in road casualty analysis.

The 2014 MAST Conference was held on 11 March at Dunchurch Park Hotel in Rugby. The conference focuses on MAST Online, a web based road safety data analysis tool created by Road Safety Analysis, which provides stakeholders with national crash data for user-customised in-depth analysis, and also offers unique insights into people involved in crashes with the help of Mosaic Public Sector.

The day started with a keynote presentation by Dr Simon Christmas in which he looked critically at the way in which segmentation can be used to help deliver value for money.

A central plank of the 2014 conference was the introduction of a host of new features in MAST Online, including Contributory Factor (CF) analysis in MAST Professional.

Delegates heard that the introduction of CF data gives users the power to look in far greater detail at the underlying causes of collisions, assessing the impact of issues such as excessive speed, road condition and impairment by alcohol.

Road Safety Analysis also used the conference to unveil the new Highway Authority Network Classification System which enables users to compare performance between authorities on the basis of the similarity of their road networks.

The day finished with a first look at some of the new dashboard features that the MAST team is working on which are designed to facilitate powerful comparative analysis, delivered in an easy-to-use clickable interface.

Click here for video, presentations and photos from the conference.

Road Safety Analysis
Road Safety Analysis is a leading supplier of creative and competitive services to the road safety sector. Built on the principles of social enterprise, Road Safety Analysis is focussed on developing and delivering a range of road safety services that are evidence based and highly cost effective.




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    I can tell you of at least one matter that is to my mind a contributory factor. That is the wrong road surface being put down, with reduced financial costs in mind.

    First there is the fast resurface dressing where tar is poured and aggregate thrown on it. That is the cheapest and least safe, but most cost effective, method of surfacing. The second and most prevalent is with the total resurfacing of the top surface. This is with the cheapest, smallest aggregate available which whilst by structure will stop water penetration for slightly longer but with that quality and smoothness of surface unfortunately it allows water to reside on the surface much longer. Longer than if a rougher, larger aggregate was used. It also enables a diesel spill to spread over a wider area and presents a larger dangerous surface patch for motorcycle tyres to lose grip on.

    bob craven Lancs
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    I agree with Duncan’s caveat that just because data is available doesn’t mean it has any significance or that it must therefore be analysed to the nth degree in the hope that a ‘hidden secret’ will be unlocked. I don’t think the subject needs to be this complicated and sometimes it’s better to take a step back from something, look again and consider the more obvious and simpler explanations.

    Hugh Jones, Cheshire
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    I think the problem Dan, is that we have lots of data but no theory to provide a framework of understanding. Similar things happened with Plate Tectonics and Evolution where there was lots of data, but none of it made much sense until the theory was proposed. Once a theory was in place all the data suddenly fell into place and great leaps forward were made in uderstanding. It’s a common failing that instead of asking for a theory people ask for more and more data in the hope that this might somehow reveal the hidden secrets.

    I couldn’t fail to notice when watching the presentations that nobody bothered to point out any unusual patterns in the data such as clusters that couldn’t be explained by statistical variability or any commonalities between crash locations. Even without an overall theory the data will give you some useful insight, but it seems that even that opportunity has been wasted.

    Duncan MacKillop, Stratford on Avon
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    Duncan makes an important point, that if we only have a limited amount of available data it can lead us to draw out conclusions that lack balance. This is precisely why we have invested so much time and effort in integrating a wider array of data sets (Mosaic, IMD, annual average mileage) into MAST and focussed so much attention in the last couple of years on supporting users to carry out comparative analysis, using national, regional, socio-demographic and now network similarity comparators.

    The desire for better data, drawing from a wider array of sources and facilitating more meaningful analysis is something that the MAST team are certainly striving for & strongly encouraging the national road safety community to pursue as well. One of the emerging themes from the day was, even with the quality of data that we can retrieve from MAST, how can we draw on data and expertise in other areas to deepen our understanding and improve our insight into the problems we are trying to address? The very reason for starting the day with a social researcher being provocative about how we approach segmentation.

    I think the Practitioner Profiles stand as fine examples of how far the road safety community has come in developing interventions on the basis of as detailed analysis as the data and projects permit – a huge step on from where most of were 10 years ago.

    Dan Campsall, Director, Road Safety Analysis
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    In the interests of research and in the hope I might learn something I have just watched all the videos from the conference. Dr Christmas gave a very good presentation which probabaly set the cat amongst the pigeons a bit as what he said was certainly what the audience didn’t want to hear.

    As for the other presentations I recommend that everybody watches them as they are a perfect example of the ‘data availability heuristic’ where people draw conclusions from data that is easily available rather than remembering that if different data had been collected then they would probably draw different conclusions.

    Duncan MacKillop, Stratford on Avon
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