Streamlining data flows to improve data-driven insights in adult social care
Uncovering data-driven insights using AWS to help Skills for Care plan, monitor and fund adult social care more quickly and accurately.
The project
There are thousands of adult social care providers in England – that’s a huge amount of data to manage. Skills for Care collects and analyses data on the adult social care workforce. They provide this to the Department of Health and Social Care to help better inform the decisions made by government and other stakeholders. Skills for Care have been performing this role since 2006 via the Adult Social Care Workforce Data Set (ASC-WDS) service.
Many of their data analysis processes were manual. This takes considerable time and doesn’t maximise data-driven insights. We worked with Skills for Care to transform their data processes to better provide intelligence more quickly and accurately.
Our approach
We implemented the Amazon Web Services (AWS) data ecosystem. This helped us modernise Skills for Care’s data architecture and processing. The goal was to streamline processes, automate routine analysis and free up valuable analyst time.
We collaborated with the analytics team to implement best practices in data engineering. We also worked with them to apply machine learning to improve their workforce estimates. We then helped Skills for Care identify the system requirements needed to continue to develop this data pipeline. They’re now ready to continue to build their pipeline as new data becomes available long after we’ve left.
“The data engineering prototype developed in this project is the first step toward a new way of working. It will help us to report more frequently and accurately to support faster and better decision-making.”
The results
An analysis that used to take 2 days can be done in 15 minutes. The datasets available for review are also extended from one to 10 years. The team can now import data from many data sources automatically. This has helped enrich their data, fill data gaps and review at a more granular level – improving the quality of their workforce estimates.
Now there’s no need to manually process data, saving time and effort. And data visualisations inform analyses, making it much easier to see trends over time.
It’s increasingly quick and easy to test new ideas and identify and fix issues earlier when data changes outside of the organisation happen. Because the process is automated, it can be rerun with no extra effort.
Case studies
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We are helping the NHS Business Services Authority (BSA) to develop a centralised and GDS compliant NHS Jobs service.
