Using data for insight, understanding and change


The Approach

The analysis required for this work was fairly simple and was about exploring the data. Two cuts of the main database were produced, one for entries with a gender flag and another for entries with an ethnicity entry. The analysis was mainly Excel based as opposed to R or Python because I wanted Contact to be able to work with the analysis and repeat it in future years or on different demographic data. The techniques used were Excel modelling and some data matching.

There were some data quality issues which required manual adjusting. When comparing demographic Contact data to published national statistics from the most recent Census, I had to make decisions about granularity to allow data matching but also have a large enough group in each category to ensure the people weren’t identifiable.

The report produced considers the results and identified areas of future research, for example qualitative surveys to find out why specific interaction methods are preferred for certain ethnic groups.

The Client

Contact support families with disabled children by offering guidance and advice, influencing policy and campaigns and offering training for practitioners.

The Client's Problem

Contact wanted a better view of the demographics of the people they reach as a charity, to highlight gaps in services and to inform future activities and analysis. The outputs had to be understandable to non-analysts and reproducible in future years.

The Solution

The solution was a report and presentation to their race & equality group, which answered the questions:

  • Who are Contact reaching, what are their demographics and how does it compare with the population?
  • Are there differences in service access for each of the demographic groups?
  • Is there any further data that would be useful to collect, or analysis that would capture a greater insight on service use and reach?

Time constraints meant only gender and ethnicity were focussed on, however further research would have allowed child age and condition to be investigated. These would enable Contact to see whether their services were accessible and ensure that they weren’t missing key areas of the population. The report will be used for future programme planning.

The Benefits


Contact can now see the demographics of users of their services, which can be fairly different to the population. It has already posed policy questions about whether men are underrepresented when using Contact services, as well as certain ethnic groups in specific locations.

There are a number of further research questions to look into around why certain people use the services they do. I will be presenting my findings to their internal race & equality group in a few weeks where I will be able to highlight the key findings and suggest further areas of research.