An update on ‘Data Labs’

The ability to understand what impact an intervention has had is very important in the charity sector. This is often very difficult for individual organisations to assess however. For a while now, we have been championing the use of ‘Data Labs’, which allow organisations to get a measure of the impact of their work and an answer to the all-important question: did we make a difference?

Our Data Labs project aims to open up government administrative data to the charity sector. That way, charities, funders, social enterprises and government bodies can better understand the impact of their services on beneficiaries. So far, we have supported the creation of the Justice Data Lab, which is still going strong after nearly ten years. More recently, we have been focusing on establishing a Data Lab on employment.

The story so far

The Employment Data Lab would be a service provided by the Department for Work and Pensions, designed to enable the evaluation of training and employment related interventions. We have good relations with analysts at the Department for Work and Pensions, who have been looking into the possibility of setting up the Employment Data Lab, and to date we have been sitting on an advisory group and helping the department to design the scheme in a way that would be useful to all potential providers.

At its most basic, the Employment Data Lab would use benefit and employment data to compare the outcomes of people who have received an intervention to those of a similar comparison group who did not receive the intervention. This would enable us to estimate the impact of different interventions on various outcomes. In all cases, the results would be shared with any partner organisations and published online.

How does a Data Lab work in practice?

The Employment Data Lab would be free and easy to use. Accessing this service would be simple and can be summarised as follows: an organisation (this is the treatment group) sends individual level data about an intervention to the Data Lab team, the data is matched up to relevant Department for Work and Pensions data and compared with data about those who did not receive an intervention (the control group), and finally the Data Lab team carry out analysis and an impact report is produced and published.

Data Labs provide access to and learning from statistical evaluations that would normally be prohibitively costly or simply out of reach for many organisations. Many charities for instance do not have easy access to comparison groups or grey data (for example, official data gathered by government bodies). This is, however, just one part of the intrinsic potential of the Employment Data Lab.

By unlocking access to data that is not readily available, the Employment Data Lab could in fact provide a way to measure the effectiveness of activities that are not traditionally evaluated. For example, it could help to measure the impact of interventions related to apprenticeships and career advice. What’s more, by triangulating different datasets, the Data Lab will create the conditions to understand what interventions are being most successful (and least successful) in helping beneficiaries to secure employment and achieve better career and salary progression.

Next steps

The pandemic has inevitably had an impact on our progress with the Employment Data Lab, with many civil servants from the Department for Work and Pensions being re-directed to other priorities for most of 2020. The pilots, planned for late 2020, had to be postponed. However, work resumed in the early months of 2021 and the Department for Work and Pensions has reiterated its commitment to the project.

NPC will continue to support this initiative, working closely with the department and the organisations involved in the advisory group (ERSA, Youth Futures Foundation, Institute for Employment Studies, Impetus and Learning and Work Institute), to ensure that this new Data Lab gets up and running and to help create an even stronger case for more Data Labs across the UK public sector and beyond.