Showcasing our data tools

Local authorities collect data on all aspects of their services, from early years and education to housing and the environment. And this data has huge untapped potential. Many local authorities store data in disparate places and rarely link it to other data, even for services that fall under the same directorate. Aggregated figures may be collected for government reports but are rarely analysed in a more granular way. By looking at statistics and datasets in different ways, it’s possible to create valuable insights that are easy to analyse and visualise.

What did we do?

In our work with City of York Council, we demonstrated some new ways to use figures and statistics, focusing on data about the uptake of the two-year-old-health review. Typically, this data is used for staff performance and measuring KPIs. The team in York had not previously had the chance to explore the data with a different lens. Our work provided this analysis – by focussing on whether there is a relationship between demographics and locations of lower uptake. This enabled York to view the city in more detail, and shift the delivery model accordingly.

How did we do it?

We created interactive maps and graphs so people with domain expertise could explore data in an informed way. We explored the data in different ways, breaking down take-up of the health review by ethnicity, gender, ward and Lower Super Output Area (LSOA). We also provided comparisons in trends over different time frames, enabling York to view changes in their two-year-old health review attendance as the seasons and years progress.

Realising the value that these visualisations had, we combined them in a prototype to show what might be possible. The video below shows the interactivity between the graphs and the ability to filter the data. By looking at figures in real time in this way, managers will be able to identify issues with attendance and respond quickly. They also noticed an additional opportunity – combining this data with other early years data, for example to look at the take-up of the free educational entitlement.

How else can data affect change?

The pilot trial also collected qualitative data. This included feedback forms for those attending the health review and information on why parents were rearranging or not attending their designated visit. This data will be incorporated into our prototype as it evolves so that in addition to the attendance trends, managers can respond to feedback and alter delivery in response to feedback. For example, if parents were forgetting or having to move appointments due to the school run, the team could send appointment reminders or shift the appointment times so they do not overlap with the start or end of the school day.

To continue the work, York’s Business Intelligence team will recreate the dashboard in their own system, drawing on other statistics from across the city.

This work is the beginning of a prototype for a much larger project for York, changing ways of working to be more data driven and responding to the needs of their population in near real time. There is optimism about the potential that this process has to improve early years outcomes across York, including for those children that were once missed and who the data analysis has now highlighted. Other local authorities could also find inspiration in this use of data, recreating their own options and expanding the impact this kind of data analysis could have across the country.

Author

Rachel Wilcock

Rachel Wilcock

Rachel Wilcock

Embedded Data Scientist, Data Analytics Practice

Rachel is an Embedded Data Scientist in the Fairer Start mission and the Data Analytics Practice.

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