This post describes how analytics was successfully implemented and used to develop the new online Carer’s Allowance service.
Our experience of many of the existing digital services showed that analytics was thought of as an ‘add-on’ towards the end of the build project, if at all. This meant that the data collected was often incomplete and not rich enough to provide actionable information to the team.
So from the start of developing the exemplar service, performance analysts worked very closely with the team in the Carer’s Allowance Unit in Preston. This ensured that digital analytics was considered from the start and embedded in the development of the new service.
As a result, we were able to identify exactly where in the process users were dropping out and how changes made to the service affected their behaviour. This was crucial in driving improvements to the service.
Being able to demonstrate that the service team makes good use of analytics is essential for your service to pass the Digital by Default service standard assessment.
In November 2014 the Carer’s Allowance service passed the Live assessment, the first DWP service to do so. It’s now being run completely without GDS assistance, and there is a DWP performance analyst embedded in the team. High level data on its performance is displayed on the GDS performance platform.
This detailed case study explores how the service team set up and used analytics on the Carer’s Allowance service. It includes best practice examples of implementation and ways of working to help other services pass item 18 of the service standard: “Use analytics tools that collect performance data.”
Analytics case study: Carer's Allowance service (pdf, 25 pages)
Ashraf Chohan is a performance analyst in GDS
2 comments
Comment by Joshua Mouldey posted on
Fantastic how-to guide Ashraf, thanks for posting this.
Comment by Dominic Hurst posted on
Nice post Ashraf. Great idea to use campaign tracking to validate and thus segment/ filter data during testing stage. Could use this technique when rolling out batch beta release to certain clients.
Like the idea of project specific personas to segment the data too. Certainly helps with true insights.
All good stuff, and for those who don't already a lot of best practice tips/ techniques