Universal Credit and Employers: Exploring the Demand Side of UK Active Labour Market Policy, 2021-2022

Active labour market policies (ALMPs) are government interventions traditionally focused on moving unemployed people into work. As those ultimately in control of the employment opportunities participants are seeking to access, employers are fundamental to ALMP outcomes. However, research and policy relating to ALMP has tended to ignore employers. Focusing on UK ALMP, as enacted through Universal Credit, this research helps to advance knowledge of this topic by focusing on employer perspectives of ALMP and the conditionality that underpins it for unemployed people and workers on a low income. The research explored how ALMP is understood and experienced by UK employers, how it impacts on how businesses are run, and how employment services can work more effectively with employers, leading to better outcomes for individuals and the wider economy. The UK's main vehicle for ALMP, and flagship policy of recent welfare reforms is Universal Credit (UC). UC is the new working age benefit for those who are either out of work or on a low income. Under UC, social security for unemployed people is conditional on claimants demonstrating work search and other work-related activities. This is underpinned by a 'Work First' approach, emphasising high volumes of applications and fast work re-entry. It also potentially involves the extension of conditionality to those in work, blurring the traditional distinction between social security claimants who are in and outside of the paid labour market . Aims and objectives The project had four main aims. Through qualitative semi-structured interviews with employers, policymakers and other key stakeholders, this research project: 1. explored how UK ALMP is understood and experienced by employers 2. identified how ALMP impacts UK businesses, including how they recruit, retain and progress their staff (including differences between sectors) 3. explored how the impact of ALMP on employers varies in different low pay sectors 4. explored how the public employment service can work effectively with employers to lead to better employment outcomes for claimants The final project report is available via Related Resources.

Research context: Active labour market policies (ALMPs) are government interventions traditionally focused on moving unemployed people into work. As those ultimately in control of the employment opportunities participants are seeking to access, employers are fundamental to ALMP outcomes (Bredgaard; 2017; Sissons and Green, 2017). However, research and policy relating to ALMP has tended to ignore employers. Focusing on UK ALMP, as enacted through Universal Credit, this research will help to advance knowledge of this topic by focusing on employer perspectives of ALMP and the conditionality that underpins it for unemployed people and workers on a low income. The research will explore how ALMP is understood and experienced by UK employers, how it impacts on how businesses are run, and how employment services can work more effectively with employers, leading to better outcomes for individuals and the wider economy (McCollum, 2012). The UK's main vehicle for ALMP, and flagship policy of recent welfare reforms is Universal Credit (UC). UC is the new working age benefit for those who are either out of work or on a low income (DWP, 2010). Under UC, social security for unemployed people is conditional on claimants demonstrating work search and other work-related activities. This is underpinned by a 'Work First' approach, emphasising high volumes of applications and fast work re-entry. It also potentially involves the extension of conditionality to those in work, blurring the traditional distinction between social security claimants who are in and outside of the paid labour market (Dwyer and Wright, 2014). Aims and objectives The project has four main aims. Through qualitative semi-structured interviews with employers, policymakers and other key stakeholders, this research project will: 1. explore how UK ALMP is understood and experienced by employers 2. identify how ALMP impacts UK businesses, including how they recruit, retain and progress their staff (and explore differences between sectors) 3. explore how the impact of ALMP on employers varies in different low pay sectors 4. explore how the public employment service can work effectively with employers to lead to better employment outcomes for claimants To realise these aims, the project is underpinned by four related objectives: 1. To generate new qualitative data on how ALMP impacts on employers and firm behaviour through consultation with employers, policy makers and other key stakeholders 2. To expand scholarly understanding of ALMP and its impact, beyond a traditional supply side focus on unemployed claimants 3. To identify ways in which public employment services (i.e. Jobcentre Plus and other contracted providers) could work with employers to help Universal Credit claimants enter and progress in work 4. To inform policy development and debate relating to ALMP for both unemployed and working Universal Credit claimants Potential applications and benefits This research has been designed to have clear benefits for multiple stakeholders: policymakers in the Department for Work and Pensions (DWP) will benefit through the insight it will provide into employer interactions with ALMP; employers will benefit as it will enable their voices to be heard on policy which impacts them and their staff; employer representative organisations will benefit through greater awareness of how UC impacts on the businesses they represent; employment and skills agencies, unions and other organisations supporting UC claimants will benefit from a greater awareness of how UC interacts with employment practices, which can help to shape their advice and support; Universal Credit claimants will benefit through more informed public debate and policy development which better reflects the realities of work, thereby enhancing the effectiveness of support for claimants; and academics will benefit through new insights and the creation of a new dataset.

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