Article

Informed insight

We have more data and information available to us than ever before, much of it available at a low cost.

By Steer

We have more data and information available to us than ever before, much of it available at a low cost. But keeping track of it all and working out how to make use of it can seem an overwhelming challenge. Where do you start? Sometimes it helps to get ideas from what others are doing. Here, Steer Davies Gleave introduces ‘Informed Insights’ – examples which we hope will illustrate and inspire how to make use of the data that is now all around us. Here we give you an idea of the different topics we cover – to read the full articles, just click on the link next to each summary.

Utilising Google search data

Searching the internet using Google (“Googling”) has become a way of life, so can we learn from what people are searching for? The answer seems to be “yes” and the  example we have used to demonstrate the concept is based on job seekers.
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Public Transport Accessibility Level (PTAL) Calculator

Using data that is now available on bus services we have developed a tool which measures and illustrates the accessibility to or within an area. Those working in London will be familiar with the PTAL database and mapping which has been available for the capital for many years: now the same is available to the rest of the country.
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TravelStyle and the underlying demand for transport services

We have used our TravelStyle geodemographic profiling and analysis tool for many years, and in many different contexts. In the current funding climate it seems to be more relevant than ever, since it is a means of evaluating potential new transport services and infrastructure at a comparatively low cost by making use of existing data, combined with our experience. The example we have used to illustrate this is based on the demand for rail travel, and in the example we have looked again at the cuts proposed by Beeching in the light of this new analysis.
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The information impact of smartcards

Smartcards (such as Oyster) generate a vast amount of data which can be used to understand travel patterns at a level of scale, detail and accuracy unimagined before: they are the transport equivalent of the Tesco Clubcard. Using just a small (publicly  available) extract of Oyster data we provide a couple of illustrations of the types of analysis possible, focussing on the issue of when people travel as well as where.
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Travel to school and deprivation

The school census is a very rich data source which includes data on how pupils travel to school. Our example of how this data can be utilised is based on comparing it with wealth and deprivation using another publicly available data source, the Index of Multiple Deprivation (IMD). In the article on our website, the hypothesis that the level of walking to school is related to deprivation is tested and explored.
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