Association for Public Policy Analysis & Management

Globally, governments are increasingly keen to explore innovative ways of financing public services. An example of this is the development Social Impact Bonds (SIBs). SIBs are Pay-for-Performance schemes in which private or social investors provide up-front finance to fund the delivery of a public service and subsequently receive an outcomes-based rate of return. A great advantage of such schemes for the government is that they only pay for ‘what works’ (Mulgan, 2011). A great challenge of such schemes is generating evidence of ‘what works’ (Warner, 2013; Fraser et al, 2016). A concern for ‘what works’ builds on longer-term trends around Evidence Based Policy and Practice (EBPP) for policy makers and practitioners (Davies, Nutley & Smith, 2000). These developments occur within a context of increasing sophistication in data collection, information technology and management systems and align closely with the key theme of the APPAM Conference about how we can generate better data for better decisions. In this paper we explore the following research question: what are the implications of innovative public services financing mechanisms such as SIBs for EBPP? This is a very important question which has been hitherto underexplored in both theoretical and empirical terms.

Methods

We draw on data from a largescale evaluation of the first Health and Social Care SIB ‘Trailblazers’ developed in the National Health Service in England over 2014-17 funded by the English Department of Health. Qualitative comparative case study data of five Health and Social Care SIB ‘Trailblazer’ projects drawing on 180 interviews conducted over three years and documentary evidence including contracts between key stakeholders are analysed to explore the relationship between the mobilisation of evidence, interpretation of outcomes data and the structure of payments across a diverse set of interventions.

Results

We identify and discuss a number of themes across the Trailblazer sites. There is diversity in the extent to which these Trailblazers seek to ‘scale up’ proven, explicitly evidence based interventions at one end of the spectrum, or offer policy makers and practitioners the freedom to ‘innovate’ and try new ideas out at the other. Such distinctions have financial implications for SIB design and the delicate balance between calculations of risk and rates of return for investors. These distinctions are novel and raise interesting epistemological questions around how we generate and interpret data to demonstrate the effectiveness of interventions on the one hand and cost effectiveness on the other.

Implications

SIBs appear to have an equivocal relationship with EBPP. They may encourage policy makers to have a closer engagement with evidence based interventions. However, concerns around the expense and technical difficulty of measuring outcomes and attribution remain. SIBs also have the capacity to generate large volumes of data – how we deal with these data and indeed, who we trust to deal with these data are important questions which deserve deep consideration.