Case study C: The Frontline Researcher

Researcher C manages research at a small branch of a national charity that offers support services for people struggling with poverty and related issues. Nearly all of the employees in their office are frontline support workers—Researcher C is the only one at the office responsible for research and data analysis.  

Most of the time, their analytical needs relate to the internal data the branch collects on its clients, but they do make regular use of publicly available data that can help illuminate new dimensions of problems for which clients seek support. They sometimes also use public data combined with internal data to inform advocacy campaigns on behalf of their clients. 

For most of their public data needs, Researcher C tends to go to Stat-Xplore as a first option, since DWP is often the relevant data holder and this is the platform through which they make data for official statistics available for public use. Researcher C noted that there is very valuable information available via this tool and it is something that they have relied on repeatedly in their work. 

At the same time, Researcher C noted that there are “a lot of gaps” when it comes to Stat-Xplore data. For example, a longstanding desire for Researcher C’s team is to get good data on the most common reasons why people are sanctioned by DWP. That information would be useful for the branch when advising clients about avoiding sanctions, but it would also help in their advocacy work since it would—ideally—offer a transparent view of the decisions made by DWP and against whom. 

Unfortunately, sanctions data available on Stat-Xplore only go so far. On the positive side of things, there are fields that indicate the reason behind adverse sanction decisions, and data can often go down to the level of local authorities or sometimes more granular geographies. On the negative side, Researcher C mentioned several factors that they would like to have that are absent: 

• Breakdowns by English as an Additional Language (EAL) status. This is absent for all benefits. 
• Breakdowns by parental status, such as the percentage of people under sanction who have children in the household. 
• Figures for the amount of money that the government saves through sanctions. This information would be of interest in its own right for Researcher C’s advocacy work, but also as a key component in any sort of economic modelling of the cost-benefit analysis of sanctions decisions. 

Each of these gaps represents an angle of analysis that is inaccessible to Researcher C. There will be others that come up in the course of their work, too, but “there’s so much on there it can take a long time to understand where to find what you need,” and they don’t always know that there is a gap until they discover they need the data. This is especially true for others like Researcher C who work in small offices and who may not be supported by additional analytical staff. 

When gaps like these are encountered, Researcher C will often resort to using FOI requests to get information. We discussed some of the issues with this “access” route in other case studies, but it is worth noting some unique elements here.  

For instance, Researcher C at one point attempted to use FOI requests to fill the gap left by the aforementioned lack of sanctions data by parental status. However, this was eventually denied by DWP, with the stated reason being that fulfilling the request would require the department to spend more time than was mandated by the relevant legislation. 

This is a fairly standard type of response to receive, and we recognise that DWP do have immense time and resource constraints that can make fielding complicated requests challenging. At the same time, it is noteworthy that, in conversation with Researcher C, they suspected that the information would be readily available due to the number of children in the household being named on a Universal Credit claim.  

Furthermore, this information would directly support the government's child poverty strategy to highlight how many sanctions impact on families with children. When generalising from their past experiences, Researcher C believes that there is a lot of gate-keeping of this kind of data and that there is a lack of transparency when answering FOI requests. 

The consequence of gaps in Stat-Xplore is therefore researcher and administrative resource being poured into the tedious and opaque FOI system, with neither the users nor producers saving time—all while potentially generating suspicion and defensiveness between them.