Project

Spotting or Creating Success? Evaluating Business Support

SME technology adoption Experimental research

Small and medium-sized enterprises (SMEs) account for a large share of economic activity, but over the space of a few years a select few high-growth businesses disproportionately drive job creation and prosperity. As this evidence emerged policymakers increasingly focused on supporting businesses thought to have the potential for high growth (aka scale-ups). However, little is known either about how effectively we can identify high-growth businesses ahead of time, about how best to nurture them or whether such an approach is truly beneficial. Despite significant public investment in business support programmes, there have been few rigorous evaluations of these activities, leaving policymakers struggling to determine which interventions truly boost growth and productivity.

With support from UKRI’s “Creating Opportunities Trial Accelerator Fund”, IGL has partnered with the UK Department for Business and Trade and Innovate UK to assess the long-term impacts of three of their programmes that were aimed at supporting businesses with high growth potential. This involves following up on the initial analysis of outcomes of the Innovation Vouchers Programme, carrying out the first analysis of the randomised trial of the Growth Impact Pilot, and using quasi-experimental methods to evaluate the outcomes of the large-scale GrowthAccelerator programme.

The results will provide policymakers with robust evidence on how best they can drive  growth and innovation, at both a local and a national level. 

Generating high-quality evidence is challenging, and any evaluation of business support programmes is only as valuable as it is accurate. Achieving this is a challenging endeavour and there is much to be learnt from the process. To this end, we are working to develop a robust scientific approach to our analysis. Our goal is to be as precise and transparent as possible, employing both the most credible statistical methods and good practices from open science. We will share our approach – for example, pre-registration of our analyses and our use of a prediction survey to test how surprising and informative our findings are – and will document our experience of implementing these steps. In so doing, we hope to inform future experimental research and provide useful insights for practitioners.

Read UKRI’s official press release.

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