The Welfare Reform PIT is undertaking a collaborative inquiry exploring how better information and data sharing can improve services and support arrangements for people in Kirkcaldy affected by changes to the social security system. The Stat-Xplore sub-group will feed back the learning and suggestions for what changes can be introduced.
In this blog Hayley Bennett from What Works Scotland, Coryn Barclay (Policy coordinator) and Gary Smith (Partnership analyst) from Fife Council reflect on the learning from this session.
What does the database offer? Hayley Bennett, What Works ScotlandIn recent years reforms to the delivery of social security payments aimed at supporting people of working age have involved the introduction of conditionality rules and a sanctioning regime that removes access to payments if citizens break these rules. (Further information on welfare conditionality can be found here). In practice, 'sanctioning' in this context refers to the decision to remove social security payments from individuals who are considered to have broken the job seeking rules they agree to when they sign up to access out of work benefits. Not all decisions lead to the act of benefit removal; some are clerical errors, some are overturned by internal decision makers at Jobcentre Plus, others are overturned after an appeal. Many individuals cease the relationship with Jobcentre Plus at the start of a the sanctioning process and at this point disappear from the official data register. As such, understanding the sanctioning process and translating the data available into useful knowledge for decision making at the local can be a difficult task.
Understanding the number of individuals who have experienced the sanctioning process and the extent to which this plays a part in the services offered to those out of the labour market is made possible through the DWPs' Stat-Xplore database. There isn’t space to cover the database in detail but in short, it offers a range of tables providing information on the numbers of sanctions based on benefit category (e.g. Jobseeker’s Allowance or Employment Support Allowance), the reasons for a decision, various geographical levels, and a breakdown of whether decisions led to a sanction being implemented (and thus a citizen temporarily losing social security payments).
Once you are familiar with the interface of the Stat Xplore database you can spend hours changing the variables and creating tables to interrogate the insight and trends you may be witnessing at the front-line. Before committing this time and energy the sub-group wanted to have a brief exploration to see if it offers what they might need. Working with this sub-group is the first time I’ve had the opportunity to research and understand first-hand how practitioners are trying to apply the information from this database to improve the lives of those they are trying to support and to help shape service delivery planning. Over the next few months we will produce some insight into how local actors could use this data, and share learning about the process we go through together.
How low can you go? Coryn Barclay, Policy Coordinator, Fife CouncilMy first thought with any new data source is ‘What level can I take this down to in order to get information that is meaningful at a local neighbourhood level?’
It is possible to pull data out at Datazone (areas of around 700 to 1,000 people, and the building block of Scottish Neighbourhood Statistics) or Interzones (areas with a population of around 2,500- 4,000 people that represent a good way of looking at natural neighbourhoods within large towns). However, it is likely that at the lowest level available there will be gaps in what you are able to draw out of the system.
There’s also a question of developing sufficient familiarity with the data to know what you can and can’t do with it. This doesn’t happen overnight, but comes from exploring the data, reading associated notes, asking colleagues who have knowledge of DWP systems, reading reports, and asking questions of experts, such as Do benefit sanctions help people get back in to work? and Are there any geographic patterns in levels of sanctions? As Hayley has used StatXplore before, she was able to shine light on both the potential and the limitations of the data, and highlight some useful features of the data tool.
There’s more of a time lag than expected with sanctions data (latest available data is June 2015), and data is not updated that often (at most twice a year). The aspiration of being able to have a timely download of information on a monthly basis falls at the first hurdle.
There is scope however to use the data in the system to undertake some contextual analysis, explore and identify issues, and use this to confirm or challenge what people think they know about benefit sanctions in Fife, and in particular neighbourhoods of Fife.
We can do this through a phased approach to what data is available for Fife, for Kirkcaldy (the focus area for collaborative action research), for different neighbourhoods, and where possible, explore how different groups of people are affected by benefit sanctions. This can be used to inform local discussions, create a shared understanding of the data around benefit sanctions, and identify areas where action may be needed.
Gary Smith, Partnership analyst, Fife CouncilI was keen to explore this system and see the range of data that was available, and how it could help inform the future work of our PIT group. Much of the information I had previously gathered about sanctions was anecdotal, and I was interested in whether the available data supported this, particularly in a local (Kirkcaldy) context.
The range of data available for analysis suggests that there are a number of opportunities to explore and identify issues relating to sanction data, including how different groups of people are affected by sanctions. The opportunity to compare data across areas of Kirkcaldy, and then place this within a Fife and Scottish context, may help illustrate local variations and identify areas for further action.
While there appear to be some questions over the completeness of data available and the frequency with which it is updated, the system appears to offer the user a variety of ways in which to interpret, analyse and compare data, all of which will hopefully be of great use going forward in providing direction and context to the work of the Welfare PIT group.